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Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debat...\n\nTags: latest:1.0.5\n\nVersion history:\n\nv1.0.5 | 2026-07-16T18:03:44.748Z | user\n\nDescription tail link + agents machine-readable metadata line (deciqai.com/s/jobs-to-be-done.json)\n\nv1.0.4 | 2026-07-09T11:18:26.899Z | user\n\nRefresh: 2024-2026 AI-era worked examples added (strategy/leadership + systems/game-theory batch)\n\nv1.0.3 | 2026-07-08T11:06:29.309Z | user\n\nFooter now uses /c/ short link (fixes UTM truncation when SKILL.md is read in a terminal)\n\nv1.0.2 | 2026-07-08T00:51:24.299Z | user\n\nRefreshed content + GitHub star link in footer\n\nv1.0.1 | 2026-07-07T20:34:08.211Z | user\n\nAdd catalog categories and topics\n\nv1.0.0 | 2026-06-29T08:17:49.551Z | user\n\nInitial publish\n\nArchive index:\n\nArchive v1.0.5: 6 files, 14282 bytes\n\nFiles: examples/christensen-and-the-milkshake-study-2003.md (5713b), examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md (9858b), references/sources.md (1690b), skill-card.md (2315b), SKILL.md (8394b), _meta.json (134b)\n\nFile v1.0.5:SKILL.md\n\n---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice. More: deciqai.com/c/jobs-to-be-done\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with `pmf-crossing-the-chasm`, `mvp`, `switching-costs`, `first-principles`.\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n- Building an AI-native product or \"AI wrapper\": are users hiring us for output/features, or for progress (get unblocked, ship faster) — and are we losing to AI adoption, the base model's own app, or non-consumption?\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) First thought — when did you first realize you needed something different? (2) Circumstance — what was going wrong? (3) What else did you consider? (4) Push — what was actively wrong with the old? (5) Pull — what attracted the new? (6) Anxiety — what almost stopped you? (7) Habit — what behavior had to change? (8) First use — how did you feel?\n\n**Step 3 — Extract job statement:** *When [circumstance], I want to [motivation], so I can [outcome].*\n\n**Step 4 — Identify actual competitor set:** Direct (same category) / Adjacent (different category, same job) / Non-consumption (do nothing) / Surprising non-obvious.\n\n**Step 5 — Map all three dimensions:** Functional (practical task) / Emotional (how they want to feel) / Social (how they want to be seen).\n\n**Step 6 — Diagnose churn or wins:** Churn: what job? what did they hire instead? what did the new hire do better? Wins: what did they fire? what became unbearable? what anxiety was overcome?\n\n**Step 7 — Design from the job.** Every feature: does it help progress in the specific circumstance? does it serve functional/emotional/social dimensions? does it reduce Push/Pull/Anxiety/Habit barriers?\n\n## Output Template\n```\nJTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track\n```\n\n*→ Method in Action: [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)*\n\n*→ 2026 lens: [What People Hire an AI Assistant to Do (2023–2026)](examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md)*\n\n## Pack: Common JTBD Patterns\n\n| Domain | Job shape | Non-obvious competitor |\n|---|---|---|\n| Productivity SaaS | \"Under deadline, make artifact look credible to boss\" | Boss not asking; meeting cancelled |\n| Consumer food | \"Tired after work, feed kids without feeling like failure\" | Ordering delivery; cereal |\n| Banking/fintech | \"Worried about money, feel like I have a plan\" | Calling a parent; not checking balance |\n| Dating apps | \"Lonely Tuesday night, feel like there are possibilities\" | Re-watching a show; texting an ex |\n\n## Applying It Well\n\n- Customers articulate the job reliably; they cannot reliably predict which features serve it. Ask \"what were you trying to accomplish when you switched?\" not \"what should we build?\"\n- The most dangerous competitor is usually outside your category — a different way of doing the job, or non-consumption.\n- Most products serve 3-7 distinct jobs. Discovering the second and third explains cohort behavior differences.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"We surveyed customers and they want X feature\" | Customers articulate jobs, not features. Re-interview using Switch methodology. |\n| [D] \"Our customer is millennials / mid-market companies\" | Demographic categories are not jobs. Same person has 5 different jobs across her day. |\n| [D] \"We don't have competitors\" | Every job has alternatives, including non-consumption. Can't name the competitor = don't understand the job. |\n| [D] \"JTBD is just user-needs research\" | User-needs lists features; JTBD reconstructs the switching moment. Different output. |\n| [D] Treating the job as functional only | Emotional and social dimensions are where premium pricing and brand loyalty live. |\n| [D] Skipping Switch Interviews because \"we already know\" | If you can't name Push/Pull/Anxiety/Habit for 10 recent switchers, you don't already know. |\n| [D] Treating churn as \"they lost interest\" | Customers fire your product because something else does the job better. Identify the new hire. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Segmentation is purely demographic; competitor set lists only same-category products\n- Roadmap features justified by \"customers asked\" without job context\n- Churn analysis stops at \"less engaged\" instead of identifying the new hire\n- Job statements without a circumstance; functional dimension only; no Switch Interview ever run\n\n## Verification\n\n- [ ] 5-10 Switch Interviews conducted (not feature surveys)\n- [ ] Job statement: When/I want to/So I can with explicit circumstance\n- [ ] Functional, emotional, social dimensions named\n- [ ] Competitor set includes adjacent, non-consumption, and surprising alternatives\n- [ ] Push, Pull, Anxiety, Habit forces identified\n- [ ] Product implications derived from the job; primary job chosen if multiple exist\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 227 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/jobs-to-be-done** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\n*Agents: latest version & machine-readable metadata → https://www.deciqai.com/s/jobs-to-be-done.json*\n\nFile v1.0.5:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.5\",\n \"publishedAt\": 1784225024748\n}\n\nFile v1.0.5:references/sources.md\n\n# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n- Stack Overflow. *Developer Survey* (2023 and 2024 editions). https://survey.stackoverflow.co — documents rapid adoption of AI coding tools among professional developers (majority using or intending to use AI in their workflow), evidence for the 2023–2026 AI-assistant JTBD example.\n- GitHub. Public reporting and research on AI-assisted development / Copilot adoption and productivity (2023–2024). https://github.blog — supports the \"get unblocked, ship faster\" job framing for AI coding assistants.\n\nFile v1.0.5:examples/christensen-and-the-milkshake-study-2003.md\n\n# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometimes, without being a parent who gives them too much sugar.\" A smaller, less sugar-dense shake won this job. The same product was being hired for two entirely different jobs by the same chain's customers — and the demographic-based \"milkshake buyers\" segmentation had been blind to both.\n\nChristensen first told the milkshake story at length in a 2007 *Harvard Business School Working Knowledge* interview, \"Clay Christensen's Milkshake Marketing,\" and it became the central case study in his 2016 book with Taddy Hall, Karen Dillon, and David Duncan, *Competing Against Luck: The Story of Innovation and Customer Choice* (HarperBusiness, ISBN 978-0062435613).\n\nThe framework's deeper claim — and the reason it caught on widely — was Christensen's quotation that captures the entire reframing:\n\n> \"When we buy a product, we essentially 'hire' something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we 'fire' it and look around for something else we might hire to solve the problem.\"\n\n— Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck.* HarperBusiness. p.13. Originally articulated in Christensen's HBS course material from the early 2000s.\n\nThe earlier intellectual root is Theodore Levitt's marketing-classic 1960 *Harvard Business Review* paper \"Marketing Myopia,\" which contained the often-paraphrased line: people don't want a quarter-inch drill, they want a quarter-inch hole. Christensen and colleagues credited Levitt as the conceptual ancestor; the JTBD framework extended the insight from a slogan into an operational research method (the Switch Interview) and a structured framework (Forces of Progress, job dimensions, circumstance-bound competition).\n\nThree operational lessons from extensive application across consumer products, B2B SaaS, and services:\n\n**First, customers reliably articulate the job, not the features.** Asking \"what do you want us to build?\" produces feature-survey theater. Asking \"what were you trying to accomplish when you switched?\" produces actionable job statements.\n\n**Second, the competitor set is wider than the category.** The most dangerous competitor is usually outside the category — a different way of doing the job, or doing nothing. Category-based competitive analysis is structurally blind to this.\n\n**Third, the same product serves multiple jobs.** A SaaS tool used for \"make my weekly report look professional\" and \"share data with my team\" is two different products from the customer's perspective. Product roadmaps that try to serve both jobs equally end up serving neither well.\n\nFile v1.0.5:examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md\n\n# Method in Action: What People Hire an AI Assistant to Do (2023–2026)\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nIn the years after the launch of ChatGPT in late 2022, many \"AI wrapper\" products shipped: an interface, a system prompt, and a call to an underlying model such as OpenAI's GPT family, Anthropic's Claude, or Google's Gemini. A large share of them reportedly struggled to retain users, even when the model underneath was excellent. This case runs the JTBD process on a recurring, non-obvious question: **what job does a knowledge worker actually hire an AI assistant/agent to do — and why do so many wrappers misread it?**\n\n## Step 1 — State product + assumed customer\n\nProduct: an AI assistant/agent (a chat product or an agentic coding/writing tool) built on top of a frontier model. Assumed customer, as most 2023-era wrappers framed it: \"people who want AI-generated text / answers.\" The implicit assumption baked into most products was that the job is *\"produce good output\"* and that the winner is whoever wraps the smartest model with the most features. This is the starting point we will dismantle.\n\n## Step 2 — Switch Interviews\n\nReconstructing the switching moment from widely-reported adoption patterns across 2023–2025 (developers adopting AI coding assistants; writers, analysts, and support teams adopting chat assistants):\n\n1. **First thought:** \"I'm stuck / this will take me all afternoon / I dread starting this.\" The trigger is rarely \"I wish I had AI-written text\" — it's a moment of being blocked, behind, or facing drudgery.\n2. **Circumstance:** a blank page, an unfamiliar codebase, a deadline, a repetitive task (reformatting, boilerplate, first-draft email), or a question whose answer is buried in docs.\n3. **What else they considered:** searching the web, asking a colleague, copying an old template, reading documentation, or simply grinding through it manually.\n4. **Push (what was wrong with the old way):** searching returns generic results that still need synthesis; the colleague is busy; the manual path is slow and boring; getting started is the hardest part.\n5. **Pull (what attracted the new hire):** it gets me *unblocked in seconds*, produces a *good-enough starting point* I can edit, and handles the parts I don't want to do myself.\n6. **Anxiety:** \"Will it hallucinate and embarrass me? Will I ship something wrong? Do I have to check every line — and if so, did it even save me time?\" Trust and verification cost are the dominant anxieties.\n7. **Habit:** having to phrase things as prompts, learning to paste in context, changing where the work starts (in the assistant vs in the IDE/doc).\n8. **First use:** the products that retained users delivered a *\"whoa, that unblocked me\"* moment fast; the ones that didn't left users with plausible-looking output they still had to redo.\n\n## Step 3 — Extract job statement\n\n> **When** I'm blocked, behind, or facing tedious work I don't want to do, **I want to** make concrete progress right now with far less effort, **so I can** get unstuck and ship the actual thing I'm responsible for — without introducing errors I'll have to answer for later.\n\nThe functional core is not \"generate text.\" It is **progress** — get unblocked, ship faster, offload drudgery — under a hard constraint of **trust** (I remain accountable for the result).\n\n## Step 4 — Identify actual competitor set\n\n- **Direct (same category):** other AI assistants and the raw model's own first-party app.\n- **Adjacent (different category, same job):** web search, Stack Overflow, documentation, templates, a helpful colleague, hiring a freelancer.\n- **Non-consumption (do nothing / do it manually):** the single biggest competitor — grinding through the task by hand, or not starting at all.\n- **Surprising / non-obvious:** the user's own habit and identity (\"real engineers write it themselves\"), and *the frontier model's own default chat interface*, which many wrappers competed against without noticing. A wrapper that only adds a nicer UI is often being fired the moment the base model's app closes the same gap.\n\n## Step 5 — Map all three dimensions\n\n- **Functional:** get unblocked, produce a usable first draft/answer, automate tedious steps, do it in the flow of existing work.\n- **Emotional:** relief from dread and overwhelm; confidence that \"I've got this\"; reduced anxiety about being wrong. Verification burden that erases the relief is why some tools feel worse than doing it manually.\n- **Social:** be seen as fast, capable, and on top of the work — *not* as someone who \"let the AI do it\" and shipped something sloppy. The social need cuts both ways, which is why trust and editability matter as much as raw capability.\n\n## Step 6 — Diagnose churn or wins (why many wrappers misread the job)\n\nApplying the fire/hire diagnosis to the wrappers that churned:\n\n- **What job were they hired for?** Progress-under-accountability. **What got them fired?** Output that looked plausible but required as much verification/rework as doing it manually — the trust constraint was violated, so the net progress was near zero.\n- **They optimized the wrong variable.** Many wrappers competed on *feature count* and *access to the smartest model*, reading the job as \"produce impressive output.\" But the customer's binding constraint was trust and time-to-unblocked, not raw eloquence.\n- **They ignored non-consumption and the base model.** A wrapper whose only advantage was a friendlier prompt box was competing against both \"do it manually\" and the model vendor's own app — and lost to whichever closed the progress gap for free.\n- **They treated one product as one job.** As with the milkshake serving a commuter and a parent, an AI assistant serves several distinct jobs — \"get me unstuck on a hard problem,\" \"do this boring task for me,\" \"help me learn/understand,\" \"make my draft look credible.\" A roadmap that averages across all of them serves none well.\n\nThe tools that *won* (notably AI coding assistants and agents adopted heavily across 2024–2025) leaned into the real job: they met the user in their existing workflow (the editor, the terminal, the repo), reduced verification cost (showing diffs, running tests, citing sources), and were honest about uncertainty — directly attacking the trust anxiety rather than papering over it with confident prose.\n\n## Step 7 — Design from the job\n\nEvery feature judged against the job:\n\n- **Helps progress in the circumstance?** Meet the user where the work already happens; deliver a usable starting point in seconds. Cut features that add options but not progress.\n- **Serves functional/emotional/social dimensions?** Reduce dread (fast unblock), build confidence (make output easy to verify and edit), protect reputation (make it easy to ship something the user can stand behind).\n- **Reduces Push/Pull/Anxiety/Habit barriers?** Attack **anxiety** first — the dominant force here. Verifiability (diffs, tests, citations, calibrated \"I'm not sure\"), editability, and staying inside the existing habit-flow do more for retention than a marginally smarter model.\n\n## Output template, filled\n\n```\nJTBD Analysis: AI assistant / agent for knowledge workers (2023–2026)\nJob statement: When I'm blocked, behind, or facing tedious work, I want to make real\n progress now with far less effort, so I can ship what I'm accountable for — without\n introducing errors I'll have to answer for.\nCompetitor set:\n Direct: other AI assistants, the base model's own app\n Adjacent: web search, docs, Stack Overflow, templates, a colleague, a freelancer\n Non-consumption: do it manually / don't start (the biggest competitor)\n Surprising: the user's own \"I should write this myself\" identity; the frontier\n model's default chat UI\nDimensions:\n Functional: unblock, first draft, automate drudgery, in-workflow\n Emotional: relief from dread; confidence; low residual anxiety\n Social: seen as fast and capable, not as sloppy \"AI did it\"\nForces of progress:\n Push: manual work is slow/boring; search returns generic results; blank-page dread\n Pull: unblocked in seconds; good-enough starting point; offloads the tedious part\n Anxiety: hallucination, shipping errors, verification cost erasing the time saved\n Habit: prompting; pasting context; where the work starts\nImplications:\n Build: in-workflow integration, verifiability (diffs/tests/citations), easy editing,\n honest uncertainty\n Cut: feature bloat that adds options but not progress; \"smartest model\" as the pitch\n Marketing angle: \"get unblocked / ship faster,\" not \"AI-generated content\"\n Competitive set to track: non-consumption and the base model's first-party app\n```\n\nThe lesson is the milkshake lesson one layer up: the buyer is not hiring \"AI text,\" any more than the commuter was hiring \"a milkshake.\" They are hiring **progress under accountability**. Wrappers that read the feature list instead of the job optimized eloquence and model access, and got fired the moment a free first-party app — or the user doing it manually — did the actual job at least as well.\n\n*Sources: Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). Competing Against Luck (HarperBusiness) — the JTBD \"hire/fire\" and Forces-of-Progress framework applied here. OpenAI's ChatGPT launched November 30, 2022, catalyzing the wave of AI assistant products discussed. The rapid 2023–2025 adoption of AI coding assistants and agentic developer tools by professional developers is widely documented in industry surveys such as the Stack Overflow Developer Survey (2023–2024 editions reporting majority developer use or intended use of AI tools) and GitHub's public reporting on AI-assisted coding adoption. Specific product-retention outcomes are described qualitatively; no proprietary figures are asserted.*\n\nFile v1.0.5:skill-card.md\n\n## Description:\n\nGuides agents through Jobs to Be Done analysis for product strategy, customer switching behavior, churn diagnosis, competitor framing, and feature implications.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[deciqai](https://clawhub.ai/user/deciqai)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nProduct teams, founders, marketers, and agents use this skill to analyze what customers are hiring a product to do, reconstruct switching moments, identify non-obvious competitors, and translate the job into product and messaging decisions.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The artifact asks agents to add observed real-use entries back into SKILL.md, which could persist user or session content into future instructions.\n\nMitigation: Keep real-use observations in a separate reviewed notes file, prevent unreviewed edits to SKILL.md, and avoid pasting customer, confidential, credential-like, or prompt-like text into the skill file.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/deciqai/skills/jobs-to-be-done)\n- [Primary sources](references/sources.md)\n- [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)\n- [What People Hire an AI Assistant to Do (2023-2026)](examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md)\n- [Clay Christensen's Milkshake Marketing](https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing)\n- [Stack Overflow Developer Survey](https://survey.stackoverflow.co)\n- [GitHub Blog](https://github.blog)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, guidance]\n\n**Output Format:** [Markdown with structured analysis sections and interview prompts]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May include wait points for step-by-step coaching and a JTBD analysis template with job statement, competitor set, dimensions, forces of progress, and implications.]\n\n## Skill Version(s):\n\n1.0.5 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.4: 6 files, 14272 bytes\n\nFiles: examples/christensen-and-the-milkshake-study-2003.md (5713b), examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md (9858b), references/sources.md (1690b), skill-card.md (2587b), SKILL.md (8253b), _meta.json (134b)\n\nFile v1.0.4:SKILL.md\n\n---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice.\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with `pmf-crossing-the-chasm`, `mvp`, `switching-costs`, `first-principles`.\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n- Building an AI-native product or \"AI wrapper\": are users hiring us for output/features, or for progress (get unblocked, ship faster) — and are we losing to AI adoption, the base model's own app, or non-consumption?\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) First thought — when did you first realize you needed something different? (2) Circumstance — what was going wrong? (3) What else did you consider? (4) Push — what was actively wrong with the old? (5) Pull — what attracted the new? (6) Anxiety — what almost stopped you? (7) Habit — what behavior had to change? (8) First use — how did you feel?\n\n**Step 3 — Extract job statement:** *When [circumstance], I want to [motivation], so I can [outcome].*\n\n**Step 4 — Identify actual competitor set:** Direct (same category) / Adjacent (different category, same job) / Non-consumption (do nothing) / Surprising non-obvious.\n\n**Step 5 — Map all three dimensions:** Functional (practical task) / Emotional (how they want to feel) / Social (how they want to be seen).\n\n**Step 6 — Diagnose churn or wins:** Churn: what job? what did they hire instead? what did the new hire do better? Wins: what did they fire? what became unbearable? what anxiety was overcome?\n\n**Step 7 — Design from the job.** Every feature: does it help progress in the specific circumstance? does it serve functional/emotional/social dimensions? does it reduce Push/Pull/Anxiety/Habit barriers?\n\n## Output Template\n```\nJTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track\n```\n\n*→ Method in Action: [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)*\n\n*→ 2026 lens: [What People Hire an AI Assistant to Do (2023–2026)](examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md)*\n\n## Pack: Common JTBD Patterns\n\n| Domain | Job shape | Non-obvious competitor |\n|---|---|---|\n| Productivity SaaS | \"Under deadline, make artifact look credible to boss\" | Boss not asking; meeting cancelled |\n| Consumer food | \"Tired after work, feed kids without feeling like failure\" | Ordering delivery; cereal |\n| Banking/fintech | \"Worried about money, feel like I have a plan\" | Calling a parent; not checking balance |\n| Dating apps | \"Lonely Tuesday night, feel like there are possibilities\" | Re-watching a show; texting an ex |\n\n## Applying It Well\n\n- Customers articulate the job reliably; they cannot reliably predict which features serve it. Ask \"what were you trying to accomplish when you switched?\" not \"what should we build?\"\n- The most dangerous competitor is usually outside your category — a different way of doing the job, or non-consumption.\n- Most products serve 3-7 distinct jobs. Discovering the second and third explains cohort behavior differences.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"We surveyed customers and they want X feature\" | Customers articulate jobs, not features. Re-interview using Switch methodology. |\n| [D] \"Our customer is millennials / mid-market companies\" | Demographic categories are not jobs. Same person has 5 different jobs across her day. |\n| [D] \"We don't have competitors\" | Every job has alternatives, including non-consumption. Can't name the competitor = don't understand the job. |\n| [D] \"JTBD is just user-needs research\" | User-needs lists features; JTBD reconstructs the switching moment. Different output. |\n| [D] Treating the job as functional only | Emotional and social dimensions are where premium pricing and brand loyalty live. |\n| [D] Skipping Switch Interviews because \"we already know\" | If you can't name Push/Pull/Anxiety/Habit for 10 recent switchers, you don't already know. |\n| [D] Treating churn as \"they lost interest\" | Customers fire your product because something else does the job better. Identify the new hire. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Segmentation is purely demographic; competitor set lists only same-category products\n- Roadmap features justified by \"customers asked\" without job context\n- Churn analysis stops at \"less engaged\" instead of identifying the new hire\n- Job statements without a circumstance; functional dimension only; no Switch Interview ever run\n\n## Verification\n\n- [ ] 5-10 Switch Interviews conducted (not feature surveys)\n- [ ] Job statement: When/I want to/So I can with explicit circumstance\n- [ ] Functional, emotional, social dimensions named\n- [ ] Competitor set includes adjacent, non-consumption, and surprising alternatives\n- [ ] Push, Pull, Anxiety, Habit forces identified\n- [ ] Product implications derived from the job; primary job chosen if multiple exist\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 189 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/jobs-to-be-done** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.4:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.4\",\n \"publishedAt\": 1783595906899\n}\n\nFile v1.0.4:references/sources.md\n\n# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n- Stack Overflow. *Developer Survey* (2023 and 2024 editions). https://survey.stackoverflow.co — documents rapid adoption of AI coding tools among professional developers (majority using or intending to use AI in their workflow), evidence for the 2023–2026 AI-assistant JTBD example.\n- GitHub. Public reporting and research on AI-assisted development / Copilot adoption and productivity (2023–2024). https://github.blog — supports the \"get unblocked, ship faster\" job framing for AI coding assistants.\n\nFile v1.0.4:examples/christensen-and-the-milkshake-study-2003.md\n\n# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometimes, without being a parent who gives them too much sugar.\" A smaller, less sugar-dense shake won this job. The same product was being hired for two entirely different jobs by the same chain's customers — and the demographic-based \"milkshake buyers\" segmentation had been blind to both.\n\nChristensen first told the milkshake story at length in a 2007 *Harvard Business School Working Knowledge* interview, \"Clay Christensen's Milkshake Marketing,\" and it became the central case study in his 2016 book with Taddy Hall, Karen Dillon, and David Duncan, *Competing Against Luck: The Story of Innovation and Customer Choice* (HarperBusiness, ISBN 978-0062435613).\n\nThe framework's deeper claim — and the reason it caught on widely — was Christensen's quotation that captures the entire reframing:\n\n> \"When we buy a product, we essentially 'hire' something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we 'fire' it and look around for something else we might hire to solve the problem.\"\n\n— Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck.* HarperBusiness. p.13. Originally articulated in Christensen's HBS course material from the early 2000s.\n\nThe earlier intellectual root is Theodore Levitt's marketing-classic 1960 *Harvard Business Review* paper \"Marketing Myopia,\" which contained the often-paraphrased line: people don't want a quarter-inch drill, they want a quarter-inch hole. Christensen and colleagues credited Levitt as the conceptual ancestor; the JTBD framework extended the insight from a slogan into an operational research method (the Switch Interview) and a structured framework (Forces of Progress, job dimensions, circumstance-bound competition).\n\nThree operational lessons from extensive application across consumer products, B2B SaaS, and services:\n\n**First, customers reliably articulate the job, not the features.** Asking \"what do you want us to build?\" produces feature-survey theater. Asking \"what were you trying to accomplish when you switched?\" produces actionable job statements.\n\n**Second, the competitor set is wider than the category.** The most dangerous competitor is usually outside the category — a different way of doing the job, or doing nothing. Category-based competitive analysis is structurally blind to this.\n\n**Third, the same product serves multiple jobs.** A SaaS tool used for \"make my weekly report look professional\" and \"share data with my team\" is two different products from the customer's perspective. Product roadmaps that try to serve both jobs equally end up serving neither well.\n\nFile v1.0.4:examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md\n\n# Method in Action: What People Hire an AI Assistant to Do (2023–2026)\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nIn the years after the launch of ChatGPT in late 2022, many \"AI wrapper\" products shipped: an interface, a system prompt, and a call to an underlying model such as OpenAI's GPT family, Anthropic's Claude, or Google's Gemini. A large share of them reportedly struggled to retain users, even when the model underneath was excellent. This case runs the JTBD process on a recurring, non-obvious question: **what job does a knowledge worker actually hire an AI assistant/agent to do — and why do so many wrappers misread it?**\n\n## Step 1 — State product + assumed customer\n\nProduct: an AI assistant/agent (a chat product or an agentic coding/writing tool) built on top of a frontier model. Assumed customer, as most 2023-era wrappers framed it: \"people who want AI-generated text / answers.\" The implicit assumption baked into most products was that the job is *\"produce good output\"* and that the winner is whoever wraps the smartest model with the most features. This is the starting point we will dismantle.\n\n## Step 2 — Switch Interviews\n\nReconstructing the switching moment from widely-reported adoption patterns across 2023–2025 (developers adopting AI coding assistants; writers, analysts, and support teams adopting chat assistants):\n\n1. **First thought:** \"I'm stuck / this will take me all afternoon / I dread starting this.\" The trigger is rarely \"I wish I had AI-written text\" — it's a moment of being blocked, behind, or facing drudgery.\n2. **Circumstance:** a blank page, an unfamiliar codebase, a deadline, a repetitive task (reformatting, boilerplate, first-draft email), or a question whose answer is buried in docs.\n3. **What else they considered:** searching the web, asking a colleague, copying an old template, reading documentation, or simply grinding through it manually.\n4. **Push (what was wrong with the old way):** searching returns generic results that still need synthesis; the colleague is busy; the manual path is slow and boring; getting started is the hardest part.\n5. **Pull (what attracted the new hire):** it gets me *unblocked in seconds*, produces a *good-enough starting point* I can edit, and handles the parts I don't want to do myself.\n6. **Anxiety:** \"Will it hallucinate and embarrass me? Will I ship something wrong? Do I have to check every line — and if so, did it even save me time?\" Trust and verification cost are the dominant anxieties.\n7. **Habit:** having to phrase things as prompts, learning to paste in context, changing where the work starts (in the assistant vs in the IDE/doc).\n8. **First use:** the products that retained users delivered a *\"whoa, that unblocked me\"* moment fast; the ones that didn't left users with plausible-looking output they still had to redo.\n\n## Step 3 — Extract job statement\n\n> **When** I'm blocked, behind, or facing tedious work I don't want to do, **I want to** make concrete progress right now with far less effort, **so I can** get unstuck and ship the actual thing I'm responsible for — without introducing errors I'll have to answer for later.\n\nThe functional core is not \"generate text.\" It is **progress** — get unblocked, ship faster, offload drudgery — under a hard constraint of **trust** (I remain accountable for the result).\n\n## Step 4 — Identify actual competitor set\n\n- **Direct (same category):** other AI assistants and the raw model's own first-party app.\n- **Adjacent (different category, same job):** web search, Stack Overflow, documentation, templates, a helpful colleague, hiring a freelancer.\n- **Non-consumption (do nothing / do it manually):** the single biggest competitor — grinding through the task by hand, or not starting at all.\n- **Surprising / non-obvious:** the user's own habit and identity (\"real engineers write it themselves\"), and *the frontier model's own default chat interface*, which many wrappers competed against without noticing. A wrapper that only adds a nicer UI is often being fired the moment the base model's app closes the same gap.\n\n## Step 5 — Map all three dimensions\n\n- **Functional:** get unblocked, produce a usable first draft/answer, automate tedious steps, do it in the flow of existing work.\n- **Emotional:** relief from dread and overwhelm; confidence that \"I've got this\"; reduced anxiety about being wrong. Verification burden that erases the relief is why some tools feel worse than doing it manually.\n- **Social:** be seen as fast, capable, and on top of the work — *not* as someone who \"let the AI do it\" and shipped something sloppy. The social need cuts both ways, which is why trust and editability matter as much as raw capability.\n\n## Step 6 — Diagnose churn or wins (why many wrappers misread the job)\n\nApplying the fire/hire diagnosis to the wrappers that churned:\n\n- **What job were they hired for?** Progress-under-accountability. **What got them fired?** Output that looked plausible but required as much verification/rework as doing it manually — the trust constraint was violated, so the net progress was near zero.\n- **They optimized the wrong variable.** Many wrappers competed on *feature count* and *access to the smartest model*, reading the job as \"produce impressive output.\" But the customer's binding constraint was trust and time-to-unblocked, not raw eloquence.\n- **They ignored non-consumption and the base model.** A wrapper whose only advantage was a friendlier prompt box was competing against both \"do it manually\" and the model vendor's own app — and lost to whichever closed the progress gap for free.\n- **They treated one product as one job.** As with the milkshake serving a commuter and a parent, an AI assistant serves several distinct jobs — \"get me unstuck on a hard problem,\" \"do this boring task for me,\" \"help me learn/understand,\" \"make my draft look credible.\" A roadmap that averages across all of them serves none well.\n\nThe tools that *won* (notably AI coding assistants and agents adopted heavily across 2024–2025) leaned into the real job: they met the user in their existing workflow (the editor, the terminal, the repo), reduced verification cost (showing diffs, running tests, citing sources), and were honest about uncertainty — directly attacking the trust anxiety rather than papering over it with confident prose.\n\n## Step 7 — Design from the job\n\nEvery feature judged against the job:\n\n- **Helps progress in the circumstance?** Meet the user where the work already happens; deliver a usable starting point in seconds. Cut features that add options but not progress.\n- **Serves functional/emotional/social dimensions?** Reduce dread (fast unblock), build confidence (make output easy to verify and edit), protect reputation (make it easy to ship something the user can stand behind).\n- **Reduces Push/Pull/Anxiety/Habit barriers?** Attack **anxiety** first — the dominant force here. Verifiability (diffs, tests, citations, calibrated \"I'm not sure\"), editability, and staying inside the existing habit-flow do more for retention than a marginally smarter model.\n\n## Output template, filled\n\n```\nJTBD Analysis: AI assistant / agent for knowledge workers (2023–2026)\nJob statement: When I'm blocked, behind, or facing tedious work, I want to make real\n progress now with far less effort, so I can ship what I'm accountable for — without\n introducing errors I'll have to answer for.\nCompetitor set:\n Direct: other AI assistants, the base model's own app\n Adjacent: web search, docs, Stack Overflow, templates, a colleague, a freelancer\n Non-consumption: do it manually / don't start (the biggest competitor)\n Surprising: the user's own \"I should write this myself\" identity; the frontier\n model's default chat UI\nDimensions:\n Functional: unblock, first draft, automate drudgery, in-workflow\n Emotional: relief from dread; confidence; low residual anxiety\n Social: seen as fast and capable, not as sloppy \"AI did it\"\nForces of progress:\n Push: manual work is slow/boring; search returns generic results; blank-page dread\n Pull: unblocked in seconds; good-enough starting point; offloads the tedious part\n Anxiety: hallucination, shipping errors, verification cost erasing the time saved\n Habit: prompting; pasting context; where the work starts\nImplications:\n Build: in-workflow integration, verifiability (diffs/tests/citations), easy editing,\n honest uncertainty\n Cut: feature bloat that adds options but not progress; \"smartest model\" as the pitch\n Marketing angle: \"get unblocked / ship faster,\" not \"AI-generated content\"\n Competitive set to track: non-consumption and the base model's first-party app\n```\n\nThe lesson is the milkshake lesson one layer up: the buyer is not hiring \"AI text,\" any more than the commuter was hiring \"a milkshake.\" They are hiring **progress under accountability**. Wrappers that read the feature list instead of the job optimized eloquence and model access, and got fired the moment a free first-party app — or the user doing it manually — did the actual job at least as well.\n\n*Sources: Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). Competing Against Luck (HarperBusiness) — the JTBD \"hire/fire\" and Forces-of-Progress framework applied here. OpenAI's ChatGPT launched November 30, 2022, catalyzing the wave of AI assistant products discussed. The rapid 2023–2025 adoption of AI coding assistants and agentic developer tools by professional developers is widely documented in industry surveys such as the Stack Overflow Developer Survey (2023–2024 editions reporting majority developer use or intended use of AI tools) and GitHub's public reporting on AI-assisted coding adoption. Specific product-retention outcomes are described qualitatively; no proprietary figures are asserted.*\n\nFile v1.0.4:skill-card.md\n\n## Description:
\nGuides product teams through Jobs-to-Be-Done analysis to identify customer jobs, switching forces, competitor sets, and product implications.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nProduct leaders, founders, marketers, and strategy teams use this skill to analyze why customers switch, churn, or fail to adopt a product. It helps turn customer circumstances into job statements, competitor maps, forces-of-progress analysis, and roadmap or positioning implications.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: JTBD analysis can produce incorrect or misleading product strategy if examples or customer claims are accepted without verification.
\nMitigation: Verify cited examples and validate conclusions with real switch interviews before making important business decisions.
\nRisk: Customer interview notes may contain private or sensitive customer information.
\nMitigation: Avoid pasting private customer interview details into shared skill notes or public artifacts.
\n\n\n## Reference(s):
\n- [ClawHub skill page](https://clawhub.ai/deciqai/skills/jobs-to-be-done)
\n- [Primary JTBD sources](references/sources.md)
\n- [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)
\n- [What People Hire an AI Assistant to Do (2023-2026)](examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md)
\n- [Clay Christensen's Milkshake Marketing](https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing)
\n- [Stack Overflow Developer Survey](https://survey.stackoverflow.co)
\n- [GitHub Blog](https://github.blog)
\n\n\n## Skill Output:
\n**Output Type(s):** [guidance, markdown]
\n**Output Format:** [Markdown analysis with structured job statements, competitor sets, dimensions, forces of progress, and implications]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [May pause for user input during coaching mode; produces advisory strategy analysis rather than executable code.]
\n\n## Skill Version(s):
\n1.0.4 (source: server release evidence)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.3: 5 files, 8995 bytes\n\nFiles: examples/christensen-and-the-milkshake-study-2003.md (5713b), references/sources.md (1180b), skill-card.md (2329b), SKILL.md (7899b), _meta.json (134b)\n\nFile v1.0.3:SKILL.md\n\n---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice.\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with `pmf-crossing-the-chasm`, `mvp`, `switching-costs`, `first-principles`.\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) First thought — when did you first realize you needed something different? (2) Circumstance — what was going wrong? (3) What else did you consider? (4) Push — what was actively wrong with the old? (5) Pull — what attracted the new? (6) Anxiety — what almost stopped you? (7) Habit — what behavior had to change? (8) First use — how did you feel?\n\n**Step 3 — Extract job statement:** *When [circumstance], I want to [motivation], so I can [outcome].*\n\n**Step 4 — Identify actual competitor set:** Direct (same category) / Adjacent (different category, same job) / Non-consumption (do nothing) / Surprising non-obvious.\n\n**Step 5 — Map all three dimensions:** Functional (practical task) / Emotional (how they want to feel) / Social (how they want to be seen).\n\n**Step 6 — Diagnose churn or wins:** Churn: what job? what did they hire instead? what did the new hire do better? Wins: what did they fire? what became unbearable? what anxiety was overcome?\n\n**Step 7 — Design from the job.** Every feature: does it help progress in the specific circumstance? does it serve functional/emotional/social dimensions? does it reduce Push/Pull/Anxiety/Habit barriers?\n\n## Output Template\n```\nJTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track\n```\n\n*→ Method in Action: [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)*\n\n## Pack: Common JTBD Patterns\n\n| Domain | Job shape | Non-obvious competitor |\n|---|---|---|\n| Productivity SaaS | \"Under deadline, make artifact look credible to boss\" | Boss not asking; meeting cancelled |\n| Consumer food | \"Tired after work, feed kids without feeling like failure\" | Ordering delivery; cereal |\n| Banking/fintech | \"Worried about money, feel like I have a plan\" | Calling a parent; not checking balance |\n| Dating apps | \"Lonely Tuesday night, feel like there are possibilities\" | Re-watching a show; texting an ex |\n\n## Applying It Well\n\n- Customers articulate the job reliably; they cannot reliably predict which features serve it. Ask \"what were you trying to accomplish when you switched?\" not \"what should we build?\"\n- The most dangerous competitor is usually outside your category — a different way of doing the job, or non-consumption.\n- Most products serve 3-7 distinct jobs. Discovering the second and third explains cohort behavior differences.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"We surveyed customers and they want X feature\" | Customers articulate jobs, not features. Re-interview using Switch methodology. |\n| [D] \"Our customer is millennials / mid-market companies\" | Demographic categories are not jobs. Same person has 5 different jobs across her day. |\n| [D] \"We don't have competitors\" | Every job has alternatives, including non-consumption. Can't name the competitor = don't understand the job. |\n| [D] \"JTBD is just user-needs research\" | User-needs lists features; JTBD reconstructs the switching moment. Different output. |\n| [D] Treating the job as functional only | Emotional and social dimensions are where premium pricing and brand loyalty live. |\n| [D] Skipping Switch Interviews because \"we already know\" | If you can't name Push/Pull/Anxiety/Habit for 10 recent switchers, you don't already know. |\n| [D] Treating churn as \"they lost interest\" | Customers fire your product because something else does the job better. Identify the new hire. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Segmentation is purely demographic; competitor set lists only same-category products\n- Roadmap features justified by \"customers asked\" without job context\n- Churn analysis stops at \"less engaged\" instead of identifying the new hire\n- Job statements without a circumstance; functional dimension only; no Switch Interview ever run\n\n## Verification\n\n- [ ] 5-10 Switch Interviews conducted (not feature surveys)\n- [ ] Job statement: When/I want to/So I can with explicit circumstance\n- [ ] Functional, emotional, social dimensions named\n- [ ] Competitor set includes adjacent, non-consumption, and surprising alternatives\n- [ ] Push, Pull, Anxiety, Habit forces identified\n- [ ] Product implications derived from the job; primary job chosen if multiple exist\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 164 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/jobs-to-be-done** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.3:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.3\",\n \"publishedAt\": 1783508789309\n}\n\nFile v1.0.3:references/sources.md\n\n# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n\nFile v1.0.3:examples/christensen-and-the-milkshake-study-2003.md\n\n# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometimes, without being a parent who gives them too much sugar.\" A smaller, less sugar-dense shake won this job. The same product was being hired for two entirely different jobs by the same chain's customers — and the demographic-based \"milkshake buyers\" segmentation had been blind to both.\n\nChristensen first told the milkshake story at length in a 2007 *Harvard Business School Working Knowledge* interview, \"Clay Christensen's Milkshake Marketing,\" and it became the central case study in his 2016 book with Taddy Hall, Karen Dillon, and David Duncan, *Competing Against Luck: The Story of Innovation and Customer Choice* (HarperBusiness, ISBN 978-0062435613).\n\nThe framework's deeper claim — and the reason it caught on widely — was Christensen's quotation that captures the entire reframing:\n\n> \"When we buy a product, we essentially 'hire' something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we 'fire' it and look around for something else we might hire to solve the problem.\"\n\n— Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck.* HarperBusiness. p.13. Originally articulated in Christensen's HBS course material from the early 2000s.\n\nThe earlier intellectual root is Theodore Levitt's marketing-classic 1960 *Harvard Business Review* paper \"Marketing Myopia,\" which contained the often-paraphrased line: people don't want a quarter-inch drill, they want a quarter-inch hole. Christensen and colleagues credited Levitt as the conceptual ancestor; the JTBD framework extended the insight from a slogan into an operational research method (the Switch Interview) and a structured framework (Forces of Progress, job dimensions, circumstance-bound competition).\n\nThree operational lessons from extensive application across consumer products, B2B SaaS, and services:\n\n**First, customers reliably articulate the job, not the features.** Asking \"what do you want us to build?\" produces feature-survey theater. Asking \"what were you trying to accomplish when you switched?\" produces actionable job statements.\n\n**Second, the competitor set is wider than the category.** The most dangerous competitor is usually outside the category — a different way of doing the job, or doing nothing. Category-based competitive analysis is structurally blind to this.\n\n**Third, the same product serves multiple jobs.** A SaaS tool used for \"make my weekly report look professional\" and \"share data with my team\" is two different products from the customer's perspective. Product roadmaps that try to serve both jobs equally end up serving neither well.\n\nFile v1.0.3:skill-card.md\n\n## Description:
\nGuides agents through Jobs to Be Done product strategy analysis to identify customer jobs, switching forces, competitor sets, and product implications.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nProduct teams, founders, and strategy agents use this skill to analyze customer switching behavior, churn, roadmap debates, and market-entry questions through the Jobs to Be Done lens.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: Product strategy guidance may be misleading if treated as a substitute for observed customer switching evidence.
\nMitigation: Validate outputs with recent switch interviews and confirm the job statement, competitor set, dimensions, and forces of progress before making roadmap decisions.
\nRisk: The skill may point users to external source links that can change or become unavailable.
\nMitigation: Review referenced links before relying on them and use the included local source and example files when external references are unavailable.
\n\n\n## Reference(s):
\n- [ClawHub Skill Page](https://clawhub.ai/deciqai/skills/jobs-to-be-done)
\n- [Primary Sources](references/sources.md)
\n- [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)
\n- [Clay Christensen's Milkshake Marketing](https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing)
\n\n\n## Skill Output:
\n**Output Type(s):** [Text, Markdown, Guidance]
\n**Output Format:** [Markdown JTBD analysis with a structured job statement, competitor set, dimensions, forces of progress, and product implications.]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [No code execution; may ask step-by-step clarification questions in coach mode.]
\n\n## Skill Version(s):
\n1.0.3 (source: server evidence release.version)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.2: 5 files, 9067 bytes\n\nFiles: examples/christensen-and-the-milkshake-study-2003.md (5713b), references/sources.md (1180b), skill-card.md (2326b), SKILL.md (8004b), _meta.json (134b)\n\nFile v1.0.2:SKILL.md\n\n---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice.\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with `pmf-crossing-the-chasm`, `mvp`, `switching-costs`, `first-principles`.\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) First thought — when did you first realize you needed something different? (2) Circumstance — what was going wrong? (3) What else did you consider? (4) Push — what was actively wrong with the old? (5) Pull — what attracted the new? (6) Anxiety — what almost stopped you? (7) Habit — what behavior had to change? (8) First use — how did you feel?\n\n**Step 3 — Extract job statement:** *When [circumstance], I want to [motivation], so I can [outcome].*\n\n**Step 4 — Identify actual competitor set:** Direct (same category) / Adjacent (different category, same job) / Non-consumption (do nothing) / Surprising non-obvious.\n\n**Step 5 — Map all three dimensions:** Functional (practical task) / Emotional (how they want to feel) / Social (how they want to be seen).\n\n**Step 6 — Diagnose churn or wins:** Churn: what job? what did they hire instead? what did the new hire do better? Wins: what did they fire? what became unbearable? what anxiety was overcome?\n\n**Step 7 — Design from the job.** Every feature: does it help progress in the specific circumstance? does it serve functional/emotional/social dimensions? does it reduce Push/Pull/Anxiety/Habit barriers?\n\n## Output Template\n```\nJTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track\n```\n\n*→ Method in Action: [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)*\n\n## Pack: Common JTBD Patterns\n\n| Domain | Job shape | Non-obvious competitor |\n|---|---|---|\n| Productivity SaaS | \"Under deadline, make artifact look credible to boss\" | Boss not asking; meeting cancelled |\n| Consumer food | \"Tired after work, feed kids without feeling like failure\" | Ordering delivery; cereal |\n| Banking/fintech | \"Worried about money, feel like I have a plan\" | Calling a parent; not checking balance |\n| Dating apps | \"Lonely Tuesday night, feel like there are possibilities\" | Re-watching a show; texting an ex |\n\n## Applying It Well\n\n- Customers articulate the job reliably; they cannot reliably predict which features serve it. Ask \"what were you trying to accomplish when you switched?\" not \"what should we build?\"\n- The most dangerous competitor is usually outside your category — a different way of doing the job, or non-consumption.\n- Most products serve 3-7 distinct jobs. Discovering the second and third explains cohort behavior differences.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"We surveyed customers and they want X feature\" | Customers articulate jobs, not features. Re-interview using Switch methodology. |\n| [D] \"Our customer is millennials / mid-market companies\" | Demographic categories are not jobs. Same person has 5 different jobs across her day. |\n| [D] \"We don't have competitors\" | Every job has alternatives, including non-consumption. Can't name the competitor = don't understand the job. |\n| [D] \"JTBD is just user-needs research\" | User-needs lists features; JTBD reconstructs the switching moment. Different output. |\n| [D] Treating the job as functional only | Emotional and social dimensions are where premium pricing and brand loyalty live. |\n| [D] Skipping Switch Interviews because \"we already know\" | If you can't name Push/Pull/Anxiety/Habit for 10 recent switchers, you don't already know. |\n| [D] Treating churn as \"they lost interest\" | Customers fire your product because something else does the job better. Identify the new hire. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Segmentation is purely demographic; competitor set lists only same-category products\n- Roadmap features justified by \"customers asked\" without job context\n- Churn analysis stops at \"less engaged\" instead of identifying the new hire\n- Job statements without a circumstance; functional dimension only; no Switch Interview ever run\n\n## Verification\n\n- [ ] 5-10 Switch Interviews conducted (not feature surveys)\n- [ ] Job statement: When/I want to/So I can with explicit circumstance\n- [ ] Functional, emotional, social dimensions named\n- [ ] Competitor set includes adjacent, non-consumption, and surprising alternatives\n- [ ] Push, Pull, Anxiety, Habit forces identified\n- [ ] Product implications derived from the job; primary job chosen if multiple exist\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 163 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/skills/jobs-to-be-done?utm_source=clawhub&utm_medium=marketplace&utm_campaign=knowledge-skills&utm_content=jobs-to-be-done** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.2:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.2\",\n \"publishedAt\": 1783471884299\n}\n\nFile v1.0.2:references/sources.md\n\n# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n\nFile v1.0.2:examples/christensen-and-the-milkshake-study-2003.md\n\n# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometimes, without being a parent who gives them too much sugar.\" A smaller, less sugar-dense shake won this job. The same product was being hired for two entirely different jobs by the same chain's customers — and the demographic-based \"milkshake buyers\" segmentation had been blind to both.\n\nChristensen first told the milkshake story at length in a 2007 *Harvard Business School Working Knowledge* interview, \"Clay Christensen's Milkshake Marketing,\" and it became the central case study in his 2016 book with Taddy Hall, Karen Dillon, and David Duncan, *Competing Against Luck: The Story of Innovation and Customer Choice* (HarperBusiness, ISBN 978-0062435613).\n\nThe framework's deeper claim — and the reason it caught on widely — was Christensen's quotation that captures the entire reframing:\n\n> \"When we buy a product, we essentially 'hire' something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we 'fire' it and look around for something else we might hire to solve the problem.\"\n\n— Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck.* HarperBusiness. p.13. Originally articulated in Christensen's HBS course material from the early 2000s.\n\nThe earlier intellectual root is Theodore Levitt's marketing-classic 1960 *Harvard Business Review* paper \"Marketing Myopia,\" which contained the often-paraphrased line: people don't want a quarter-inch drill, they want a quarter-inch hole. Christensen and colleagues credited Levitt as the conceptual ancestor; the JTBD framework extended the insight from a slogan into an operational research method (the Switch Interview) and a structured framework (Forces of Progress, job dimensions, circumstance-bound competition).\n\nThree operational lessons from extensive application across consumer products, B2B SaaS, and services:\n\n**First, customers reliably articulate the job, not the features.** Asking \"what do you want us to build?\" produces feature-survey theater. Asking \"what were you trying to accomplish when you switched?\" produces actionable job statements.\n\n**Second, the competitor set is wider than the category.** The most dangerous competitor is usually outside the category — a different way of doing the job, or doing nothing. Category-based competitive analysis is structurally blind to this.\n\n**Third, the same product serves multiple jobs.** A SaaS tool used for \"make my weekly report look professional\" and \"share data with my team\" is two different products from the customer's perspective. Product roadmaps that try to serve both jobs equally end up serving neither well.\n\nFile v1.0.2:skill-card.md\n\n## Description:
\nGuides agents through Jobs to Be Done product strategy analysis to uncover customer switching behavior, real competitor sets, job statements, forces of progress, and product implications.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nProduct teams, founders, and strategy agents use this skill to analyze why customers switch, churn, or choose alternatives. It turns product and customer context into a JTBD job statement, competitor set, progress forces, and product or marketing implications.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: The skill can shape product strategy recommendations without direct market validation.
\nMitigation: Use it as a coaching framework and validate job statements with switch interviews and product evidence before acting.
\nRisk: User-provided cases may include business-sensitive customer, churn, or roadmap information.
\nMitigation: Avoid sharing unnecessary confidential details and review any saved notes or outputs before reuse.
\n\n\n## Reference(s):
\n- [Jobs to Be Done (JTBD) ClawHub listing](https://clawhub.ai/deciqai/skills/jobs-to-be-done)
\n- [Sources - jobs-to-be-done](references/sources.md)
\n- [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)
\n- [Clay Christensen's Milkshake Marketing](https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing)
\n\n\n## Skill Output:
\n**Output Type(s):** [guidance, markdown, text]
\n**Output Format:** [Markdown analysis template with structured JTBD sections and interview prompts]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [May pause for user input during coach mode; no files, code, API calls, or shell commands are produced.]
\n\n## Skill Version(s):
\n1.0.2 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.1: 5 files, 8976 bytes\n\nFiles: examples/christensen-and-the-milkshake-study-2003.md (5713b), references/sources.md (1180b), skill-card.md (2300b), SKILL.md (7866b), _meta.json (134b)\n\nFile v1.0.1:SKILL.md\n\n---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice.\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with [`pmf-crossing-the-chasm`](../pmf-crossing-the-chasm/SKILL.md), [`mvp`](../mvp/SKILL.md), [`switching-costs`](../switching-costs/SKILL.md), [`first-principles`](../first-principles/SKILL.md).\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) First thought — when did you first realize you needed something different? (2) Circumstance — what was going wrong? (3) What else did you consider? (4) Push — what was actively wrong with the old? (5) Pull — what attracted the new? (6) Anxiety — what almost stopped you? (7) Habit — what behavior had to change? (8) First use — how did you feel?\n\n**Step 3 — Extract job statement:** *When [circumstance], I want to [motivation], so I can [outcome].*\n\n**Step 4 — Identify actual competitor set:** Direct (same category) / Adjacent (different category, same job) / Non-consumption (do nothing) / Surprising non-obvious.\n\n**Step 5 — Map all three dimensions:** Functional (practical task) / Emotional (how they want to feel) / Social (how they want to be seen).\n\n**Step 6 — Diagnose churn or wins:** Churn: what job? what did they hire instead? what did the new hire do better? Wins: what did they fire? what became unbearable? what anxiety was overcome?\n\n**Step 7 — Design from the job.** Every feature: does it help progress in the specific circumstance? does it serve functional/emotional/social dimensions? does it reduce Push/Pull/Anxiety/Habit barriers?\n\n## Output Template\n```\nJTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track\n```\n\n*→ Method in Action: [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)*\n\n## Pack: Common JTBD Patterns\n\n| Domain | Job shape | Non-obvious competitor |\n|---|---|---|\n| Productivity SaaS | \"Under deadline, make artifact look credible to boss\" | Boss not asking; meeting cancelled |\n| Consumer food | \"Tired after work, feed kids without feeling like failure\" | Ordering delivery; cereal |\n| Banking/fintech | \"Worried about money, feel like I have a plan\" | Calling a parent; not checking balance |\n| Dating apps | \"Lonely Tuesday night, feel like there are possibilities\" | Re-watching a show; texting an ex |\n\n## Applying It Well\n\n- Customers articulate the job reliably; they cannot reliably predict which features serve it. Ask \"what were you trying to accomplish when you switched?\" not \"what should we build?\"\n- The most dangerous competitor is usually outside your category — a different way of doing the job, or non-consumption.\n- Most products serve 3-7 distinct jobs. Discovering the second and third explains cohort behavior differences.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"We surveyed customers and they want X feature\" | Customers articulate jobs, not features. Re-interview using Switch methodology. |\n| [D] \"Our customer is millennials / mid-market companies\" | Demographic categories are not jobs. Same person has 5 different jobs across her day. |\n| [D] \"We don't have competitors\" | Every job has alternatives, including non-consumption. Can't name the competitor = don't understand the job. |\n| [D] \"JTBD is just user-needs research\" | User-needs lists features; JTBD reconstructs the switching moment. Different output. |\n| [D] Treating the job as functional only | Emotional and social dimensions are where premium pricing and brand loyalty live. |\n| [D] Skipping Switch Interviews because \"we already know\" | If you can't name Push/Pull/Anxiety/Habit for 10 recent switchers, you don't already know. |\n| [D] Treating churn as \"they lost interest\" | Customers fire your product because something else does the job better. Identify the new hire. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Segmentation is purely demographic; competitor set lists only same-category products\n- Roadmap features justified by \"customers asked\" without job context\n- Churn analysis stops at \"less engaged\" instead of identifying the new hire\n- Job statements without a circumstance; functional dimension only; no Switch Interview ever run\n\n## Verification\n\n- [ ] 5-10 Switch Interviews conducted (not feature surveys)\n- [ ] Job statement: When/I want to/So I can with explicit circumstance\n- [ ] Functional, emotional, social dimensions named\n- [ ] Competitor set includes adjacent, non-consumption, and surprising alternatives\n- [ ] Push, Pull, Anxiety, Habit forces identified\n- [ ] Product implications derived from the job; primary job chosen if multiple exist\n\n---\n\n*Part of **deciqAI Knowledge Skills** — open-source thinking skills that make rigor executable for AI agents. Built by deciqAI · https://deciqai.com · Contributions welcome — see the template at the repo root.*\n\nFile v1.0.1:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.1\",\n \"publishedAt\": 1783456448211\n}\n\nFile v1.0.1:references/sources.md\n\n# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n\nFile v1.0.1:examples/christensen-and-the-milkshake-study-2003.md\n\n# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometimes, without being a parent who gives them too much sugar.\" A smaller, less sugar-dense shake won this job. The same product was being hired for two entirely different jobs by the same chain's customers — and the demographic-based \"milkshake buyers\" segmentation had been blind to both.\n\nChristensen first told the milkshake story at length in a 2007 *Harvard Business School Working Knowledge* interview, \"Clay Christensen's Milkshake Marketing,\" and it became the central case study in his 2016 book with Taddy Hall, Karen Dillon, and David Duncan, *Competing Against Luck: The Story of Innovation and Customer Choice* (HarperBusiness, ISBN 978-0062435613).\n\nThe framework's deeper claim — and the reason it caught on widely — was Christensen's quotation that captures the entire reframing:\n\n> \"When we buy a product, we essentially 'hire' something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we 'fire' it and look around for something else we might hire to solve the problem.\"\n\n— Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck.* HarperBusiness. p.13. Originally articulated in Christensen's HBS course material from the early 2000s.\n\nThe earlier intellectual root is Theodore Levitt's marketing-classic 1960 *Harvard Business Review* paper \"Marketing Myopia,\" which contained the often-paraphrased line: people don't want a quarter-inch drill, they want a quarter-inch hole. Christensen and colleagues credited Levitt as the conceptual ancestor; the JTBD framework extended the insight from a slogan into an operational research method (the Switch Interview) and a structured framework (Forces of Progress, job dimensions, circumstance-bound competition).\n\nThree operational lessons from extensive application across consumer products, B2B SaaS, and services:\n\n**First, customers reliably articulate the job, not the features.** Asking \"what do you want us to build?\" produces feature-survey theater. Asking \"what were you trying to accomplish when you switched?\" produces actionable job statements.\n\n**Second, the competitor set is wider than the category.** The most dangerous competitor is usually outside the category — a different way of doing the job, or doing nothing. Category-based competitive analysis is structurally blind to this.\n\n**Third, the same product serves multiple jobs.** A SaaS tool used for \"make my weekly report look professional\" and \"share data with my team\" is two different products from the customer's perspective. Product roadmaps that try to serve both jobs equally end up serving neither well.\n\nFile v1.0.1:skill-card.md\n\n## Description:
\nGuides product teams through Jobs to Be Done analysis for switching behavior, churn diagnosis, customer segmentation, and feature prioritization.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nEmployees, external product teams, and founders use this skill to run Jobs to Be Done coaching, switch-interview analysis, competitor mapping, churn diagnosis, and product implications for a concrete customer behavior question.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: JTBD analysis can produce misleading product direction if users treat the framework as a substitute for real customer evidence.
\nMitigation: Conduct switch interviews, validate job statements with recent switchers, and review the cited methodology before making roadmap or positioning decisions.
\nRisk: The skill is not designed for commodity, regulatory-compliance, or no-choice purchase contexts.
\nMitigation: Check the skill's fit conditions before applying it and use another product strategy lens when customers have no meaningful switching choice.
\n\n\n## Reference(s):
\n- [ClawHub skill page](https://clawhub.ai/deciqai/skills/jobs-to-be-done)
\n- [Primary sources](references/sources.md)
\n- [Christensen and the Milkshake Study example](examples/christensen-and-the-milkshake-study-2003.md)
\n- [Clay Christensen's Milkshake Marketing](https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing)
\n\n\n## Skill Output:
\n**Output Type(s):** [Analysis, Markdown, Guidance]
\n**Output Format:** [Markdown]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Structured JTBD analysis with job statements, competitor sets, dimensions, forces of progress, and product implications.]
\n\n## Skill Version(s):
\n1.0.1 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.0: 5 files, 9004 bytes\n\nFiles: examples/christensen-and-the-milkshake-study-2003.md (5713b), references/sources.md (1180b), skill-card.md (2361b), SKILL.md (7866b), _meta.json (134b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice.\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with [`pmf-crossing-the-chasm`](../pmf-crossing-the-chasm/SKILL.md), [`mvp`](../mvp/SKILL.md), [`switching-costs`](../switching-costs/SKILL.md), [`first-principles`](../first-principles/SKILL.md).\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) First thought — when did you first realize you needed something different? (2) Circumstance — what was going wrong? (3) What else did you consider? (4) Push — what was actively wrong with the old? (5) Pull — what attracted the new? (6) Anxiety — what almost stopped you? (7) Habit — what behavior had to change? (8) First use — how did you feel?\n\n**Step 3 — Extract job statement:** *When [circumstance], I want to [motivation], so I can [outcome].*\n\n**Step 4 — Identify actual competitor set:** Direct (same category) / Adjacent (different category, same job) / Non-consumption (do nothing) / Surprising non-obvious.\n\n**Step 5 — Map all three dimensions:** Functional (practical task) / Emotional (how they want to feel) / Social (how they want to be seen).\n\n**Step 6 — Diagnose churn or wins:** Churn: what job? what did they hire instead? what did the new hire do better? Wins: what did they fire? what became unbearable? what anxiety was overcome?\n\n**Step 7 — Design from the job.** Every feature: does it help progress in the specific circumstance? does it serve functional/emotional/social dimensions? does it reduce Push/Pull/Anxiety/Habit barriers?\n\n## Output Template\n```\nJTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track\n```\n\n*→ Method in Action: [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)*\n\n## Pack: Common JTBD Patterns\n\n| Domain | Job shape | Non-obvious competitor |\n|---|---|---|\n| Productivity SaaS | \"Under deadline, make artifact look credible to boss\" | Boss not asking; meeting cancelled |\n| Consumer food | \"Tired after work, feed kids without feeling like failure\" | Ordering delivery; cereal |\n| Banking/fintech | \"Worried about money, feel like I have a plan\" | Calling a parent; not checking balance |\n| Dating apps | \"Lonely Tuesday night, feel like there are possibilities\" | Re-watching a show; texting an ex |\n\n## Applying It Well\n\n- Customers articulate the job reliably; they cannot reliably predict which features serve it. Ask \"what were you trying to accomplish when you switched?\" not \"what should we build?\"\n- The most dangerous competitor is usually outside your category — a different way of doing the job, or non-consumption.\n- Most products serve 3-7 distinct jobs. Discovering the second and third explains cohort behavior differences.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"We surveyed customers and they want X feature\" | Customers articulate jobs, not features. Re-interview using Switch methodology. |\n| [D] \"Our customer is millennials / mid-market companies\" | Demographic categories are not jobs. Same person has 5 different jobs across her day. |\n| [D] \"We don't have competitors\" | Every job has alternatives, including non-consumption. Can't name the competitor = don't understand the job. |\n| [D] \"JTBD is just user-needs research\" | User-needs lists features; JTBD reconstructs the switching moment. Different output. |\n| [D] Treating the job as functional only | Emotional and social dimensions are where premium pricing and brand loyalty live. |\n| [D] Skipping Switch Interviews because \"we already know\" | If you can't name Push/Pull/Anxiety/Habit for 10 recent switchers, you don't already know. |\n| [D] Treating churn as \"they lost interest\" | Customers fire your product because something else does the job better. Identify the new hire. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Segmentation is purely demographic; competitor set lists only same-category products\n- Roadmap features justified by \"customers asked\" without job context\n- Churn analysis stops at \"less engaged\" instead of identifying the new hire\n- Job statements without a circumstance; functional dimension only; no Switch Interview ever run\n\n## Verification\n\n- [ ] 5-10 Switch Interviews conducted (not feature surveys)\n- [ ] Job statement: When/I want to/So I can with explicit circumstance\n- [ ] Functional, emotional, social dimensions named\n- [ ] Competitor set includes adjacent, non-consumption, and surprising alternatives\n- [ ] Push, Pull, Anxiety, Habit forces identified\n- [ ] Product implications derived from the job; primary job chosen if multiple exist\n\n---\n\n*Part of **deciqAI Knowledge Skills** — open-source thinking skills that make rigor executable for AI agents. Built by deciqAI · https://deciqai.com · Contributions welcome — see the template at the repo root.*\n\nFile v1.0.0:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.0\",\n \"publishedAt\": 1782721069551\n}\n\nFile v1.0.0:references/sources.md\n\n# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n\nFile v1.0.0:examples/christensen-and-the-milkshake-study-2003.md\n\n# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometimes, without being a parent who gives them too much sugar.\" A smaller, less sugar-dense shake won this job. The same product was being hired for two entirely different jobs by the same chain's customers — and the demographic-based \"milkshake buyers\" segmentation had been blind to both.\n\nChristensen first told the milkshake story at length in a 2007 *Harvard Business School Working Knowledge* interview, \"Clay Christensen's Milkshake Marketing,\" and it became the central case study in his 2016 book with Taddy Hall, Karen Dillon, and David Duncan, *Competing Against Luck: The Story of Innovation and Customer Choice* (HarperBusiness, ISBN 978-0062435613).\n\nThe framework's deeper claim — and the reason it caught on widely — was Christensen's quotation that captures the entire reframing:\n\n> \"When we buy a product, we essentially 'hire' something to get a job done. If it does the job well, when we are confronted with the same job, we hire that same product again. And if the product does a crummy job, we 'fire' it and look around for something else we might hire to solve the problem.\"\n\n— Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck.* HarperBusiness. p.13. Originally articulated in Christensen's HBS course material from the early 2000s.\n\nThe earlier intellectual root is Theodore Levitt's marketing-classic 1960 *Harvard Business Review* paper \"Marketing Myopia,\" which contained the often-paraphrased line: people don't want a quarter-inch drill, they want a quarter-inch hole. Christensen and colleagues credited Levitt as the conceptual ancestor; the JTBD framework extended the insight from a slogan into an operational research method (the Switch Interview) and a structured framework (Forces of Progress, job dimensions, circumstance-bound competition).\n\nThree operational lessons from extensive application across consumer products, B2B SaaS, and services:\n\n**First, customers reliably articulate the job, not the features.** Asking \"what do you want us to build?\" produces feature-survey theater. Asking \"what were you trying to accomplish when you switched?\" produces actionable job statements.\n\n**Second, the competitor set is wider than the category.** The most dangerous competitor is usually outside the category — a different way of doing the job, or doing nothing. Category-based competitive analysis is structurally blind to this.\n\n**Third, the same product serves multiple jobs.** A SaaS tool used for \"make my weekly report look professional\" and \"share data with my team\" is two different products from the customer's perspective. Product roadmaps that try to serve both jobs equally end up serving neither well.\n\nFile v1.0.0:skill-card.md\n\n## Description:
\nGuides agents through Jobs to Be Done analysis for product strategy, customer switching behavior, churn diagnosis, competitor discovery, and roadmap implications.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nProduct managers, founders, marketers, and customer research teams use this skill to identify the real job customers hire a product to do, reconstruct switching moments, diagnose churn, and translate customer progress into product and positioning choices.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: User-provided customer interview notes, churn details, or business strategy examples may contain confidential or personally identifiable information.
\nMitigation: Avoid pasting confidential or personally identifiable information unless the agent is intended to use it in the analysis.
\nRisk: JTBD outputs can overstate conclusions if they are based on assumptions rather than recent switch interviews.
\nMitigation: Validate job statements, forces of progress, and competitor sets with 5-10 switch interviews before making high-impact product or positioning decisions.
\n\n\n## Reference(s):
\n- [ClawHub release page](https://clawhub.ai/deciqai/skills/jobs-to-be-done)
\n- [Sources - jobs-to-be-done](references/sources.md)
\n- [Christensen and the Milkshake Study, 2003](examples/christensen-and-the-milkshake-study-2003.md)
\n- [Clay Christensen's Milkshake Marketing](https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing)
\n\n\n## Skill Output:
\n**Output Type(s):** [guidance, markdown, text]
\n**Output Format:** [Markdown coaching response or structured JTBD analysis]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [May pause at explicit wait steps when coaching novices through a case.]
\n\n## Skill Version(s):
\n1.0.0 (source: server release evidence)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
","readmeExcerpt":"Skill: Jobs to Be Done (JTBD) Owner: deciqai Summary: Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debat... Tags: latest:1.0.5 Version history: v1.0.5 | 2026-07-16T18:03:44.748Z | user Description tail link + agents machine-readable metadata line (deciqai.com/s/jobs-to-be-done.json) v1.0.4 | 2026-07-09T11:18:26.","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"JTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track"},{"language":"text","snippet":"JTBD Analysis: AI assistant / agent for knowledge workers (2023–2026)\nJob statement: When I'm blocked, behind, or facing tedious work, I want to make real\n progress now with far less effort, so I can ship what I'm accountable for — without\n introducing errors I'll have to answer for.\nCompetitor set:\n Direct: other AI assistants, the base model's own app\n Adjacent: web search, docs, Stack Overflow, templates, a colleague, a freelancer\n Non-consumption: do it manually / don't start (the biggest competitor)\n Surprising: the user's own \"I should write this myself\" identity; the frontier\n model's default chat UI\nDimensions:\n Functional: unblock, first draft, automate drudgery, in-workflow\n Emotional: relief from dread; confidence; low residual anxiety\n Social: seen as fast and capable, not as sloppy \"AI did it\"\nForces of progress:\n Push: manual work is slow/boring; search returns generic results; blank-page dread\n Pull: unblocked in seconds; good-enough starting point; offloads the tedious part\n Anxiety: hallucination, shipping errors, verification cost erasing the time saved\n Habit: prompting; pasting context; where the work starts\nImplications:\n Build: in-workflow integration, verifiability (diffs/tests/citations), easy editing,\n honest uncertainty\n Cut: feature bloat that adds options but not progress; \"smartest model\" as the pitch\n Marketing angle: \"get unblocked / ship faster,\" not \"AI-generated content\"\n Competitive set to track: non-consumption and the base model's first-party app"},{"language":"text","snippet":"JTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track"},{"language":"text","snippet":"JTBD Analysis: AI assistant / agent for knowledge workers (2023–2026)\nJob statement: When I'm blocked, behind, or facing tedious work, I want to make real\n progress now with far less effort, so I can ship what I'm accountable for — without\n introducing errors I'll have to answer for.\nCompetitor set:\n Direct: other AI assistants, the base model's own app\n Adjacent: web search, docs, Stack Overflow, templates, a colleague, a freelancer\n Non-consumption: do it manually / don't start (the biggest competitor)\n Surprising: the user's own \"I should write this myself\" identity; the frontier\n model's default chat UI\nDimensions:\n Functional: unblock, first draft, automate drudgery, in-workflow\n Emotional: relief from dread; confidence; low residual anxiety\n Social: seen as fast and capable, not as sloppy \"AI did it\"\nForces of progress:\n Push: manual work is slow/boring; search returns generic results; blank-page dread\n Pull: unblocked in seconds; good-enough starting point; offloads the tedious part\n Anxiety: hallucination, shipping errors, verification cost erasing the time saved\n Habit: prompting; pasting context; where the work starts\nImplications:\n Build: in-workflow integration, verifiability (diffs/tests/citations), easy editing,\n honest uncertainty\n Cut: feature bloat that adds options but not progress; \"smartest model\" as the pitch\n Marketing angle: \"get unblocked / ship faster,\" not \"AI-generated content\"\n Competitive set to track: non-consumption and the base model's first-party app"},{"language":"text","snippet":"JTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track"},{"language":"text","snippet":"JTBD Analysis: \nJob statement: When [circumstance], I want to [motivation], so I can [outcome].\nCompetitor set: Direct / Adjacent / Non-consumption / Surprising\nDimensions: Functional / Emotional / Social\nForces of progress: Push / Pull / Anxiety / Habit\nImplications: Features to build / cut / Marketing angle / Competitive set to track"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: jobs-to-be-done\ndescription: \"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debating features instead of what the customer actually needs,' 'who is our real customer,' or mentions 'JTBD / jobs to be done / what are they hiring this for.'\n Do NOT activate when: product is a commodity with no job-level differentiation (electricity, raw materials); purchase is driven entirely by regulatory/legal compliance with no real customer choice. More: deciqai.com/c/jobs-to-be-done\"\n---\n\n# Jobs to Be Done (JTBD)\n\n## Overview\n\nPeople don't buy products — they **hire** products to do a job (make progress in a specific circumstance, across functional, emotional, and social dimensions). Customers switch when a new hire does the job better; they churn when your product stops serving the job. Developed by Christensen, Moesta, and Taddy Hall; codified in *Competing Against Luck* (2016). Rooted in Levitt's 1960 insight: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n\nComposes with `pmf-crossing-the-chasm`, `mvp`, `switching-costs`, `first-principles`.\n\n## When to Use\n\n- Product is technically excellent but customers don't switch from incumbents\n- Demographic segmentation produces segments that don't behave alike\n- Churn is high but exit surveys don't predict it; roadmap debate is feature-vs-feature\n- New market entry: \"who is our customer\" instead of \"what job\"\n- Building an AI-native product or \"AI wrapper\": are users hiring us for output/features, or for progress (get unblocked, ship faster) — and are we losing to AI adoption, the base model's own app, or non-consumption?\n\n**Not when:** commodity; regulatory-compliance purchase; org buyer with different motivations than end-user.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** concrete product/customer case → run The Process directly.\n- **Coach mode:** unfamiliar or no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. One-line: people hire products to do a job — the competitor set is *everything* the buyer considered, not just your category.\n2. Check fit: commodity / regulatory-buy / no-choice → not this lens.\n3. Elicit the real product and customer behavior they're trying to understand.\n> **[WAIT — do not advance until user responds]**\n4. One question at a time: what job is the customer hiring this for? what circumstance? what did they hire before?\n> **[WAIT — do not advance until user responds]**\n5. Close: job statement + the non-obvious competitor they're actually choosing between.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\n**Step 1 — State product + assumed customer** (starting point; will be dismantled).\n\n**Step 2 — Switch Interviews.** Interview recent switchers to/from your product. Reconstruct the switching moment: (1) Firs"},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"jobs-to-be-done\",\n \"version\": \"1.0.5\",\n \"publishedAt\": 1784225024748\n}"},{"path":"references/sources.md","content":"# Sources — jobs-to-be-done\n\n> *Primary sources for the [jobs-to-be-done](../SKILL.md) skill.*\n\n- Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). *Competing Against Luck: The Story of Innovation and Customer Choice.* HarperBusiness. ISBN 978-0062435613. The canonical book-length treatment.\n- Christensen, C. M., Anthony, S. D., Berstell, G., & Nitterhouse, D. (2007). \"Finding the right job for your product.\" *MIT Sloan Management Review*, 48(3), 38-47. Early academic articulation of the framework.\n- Levitt, T. (1960). \"Marketing Myopia.\" *Harvard Business Review*, 38(4), 45-56. The intellectual ancestor: \"People don't want a quarter-inch drill, they want a quarter-inch hole.\"\n- Moesta, B. & Spiek, C. (2020). *Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress.* Lioncrest. Practical Switch Interview methodology.\n- Ulwick, A. W. (2016). *Jobs to be Done: Theory to Practice.* Idea Bite Press. A parallel \"outcome-driven innovation\" school of JTBD with stronger quantitative emphasis.\n- \"Clay Christensen's Milkshake Marketing.\" *HBS Working Knowledge*, Feb 2007. https://hbswk.hbs.edu/item/clay-christensens-milkshake-marketing\n- Stack Overflow. *Developer Survey* (2023 and 2024 editions). https://survey.stackoverflow.co — documents rapid adoption of AI coding tools among professional developers (majority using or intending to use AI in their workflow), evidence for the 2023–2026 AI-assistant JTBD example.\n- GitHub. Public reporting and research on AI-assisted development / Copilot adoption and productivity (2023–2024). https://github.blog — supports the \"get unblocked, ship faster\" job framing for AI coding assistants."},{"path":"examples/christensen-and-the-milkshake-study-2003.md","content":"# Method in Action: Christensen and the Milkshake Study, 2003\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nThe most famous illustration of JTBD comes from a study Clayton Christensen and Bob Moesta conducted for a major fast-food chain in 2002-2003. The chain wanted to sell more milkshakes. They had spent considerable resources on the conventional approach: customer demographic surveys, segmentation into target customer profiles, focus groups asking \"would you buy more milkshakes if they were thicker / sweeter / cheaper / had more flavors?\"\n\nThe result of conventional research was a thicker, sweeter, more-flavored milkshake. Sales did not move.\n\nChristensen's team tried a different approach: they stood in the restaurant and observed who bought milkshakes and when. Two patterns emerged immediately:\n\n1. A surprisingly large share of milkshakes were sold *before 9 AM*.\n2. The before-9-AM buyers were almost all solo adults in business attire, buying just a milkshake and nothing else, drinking it in their car.\n\nThe team began interviewing the morning milkshake buyers as they left the restaurant. The question was not \"what could we add to make this better?\" but \"what *job* did you hire that milkshake for this morning?\"\n\nThe answers converged on a specific job statement:\n\n> *I have a long, boring drive to work. I need something to do with my hand and mouth that will make the commute less boring. It has to last the whole drive — about 20 minutes — so something I finish in 3 bites won't do. It has to not make a mess so I can eat it one-handed while driving. It has to not leave me hungry by 10 AM.*\n\nThe job framework reframed the entire competitive picture:\n\n- **Bagels** were a competitor — but bagels crumb, need cream cheese, and require two hands.\n- **Bananas** were a competitor — but bananas are eaten in 90 seconds.\n- **Donuts** were a competitor — but donuts leave the customer hungry within an hour.\n- **Coffee** was a competitor — but coffee doesn't fill you up.\n- **Doing nothing** was the most common competitor — many morning commuters were defaulting to a boring drive with nothing.\n\nThe milkshake won this competition because it was thick enough to last 20 minutes, dense enough to not leave the buyer hungry, and consumable one-handed without mess. The conventional research had been measuring whether the *milkshake* could be better — but the milkshake was already winning the morning job. **The optimization opportunity was to make the milkshake even more efficient at the existing job** (thicker, faster to serve so commuters didn't wait), not to make it taste like more flavors.\n\nCritically, the team also found a second morning shake-buyer pattern: a parent buying a milkshake for a child in the late afternoon, as a treat. **Same product, completely different job.** The afternoon shake needed to be small (the parent didn't want the child to get full), and the parent's emotional need was \"I want to be a good parent who treats my child sometim"},{"path":"examples/what-people-hire-an-ai-assistant-to-do-2023-2026.md","content":"# Method in Action: What People Hire an AI Assistant to Do (2023–2026)\n\n> *Example for the [jobs-to-be-done](../SKILL.md) skill.*\n\nIn the years after the launch of ChatGPT in late 2022, many \"AI wrapper\" products shipped: an interface, a system prompt, and a call to an underlying model such as OpenAI's GPT family, Anthropic's Claude, or Google's Gemini. A large share of them reportedly struggled to retain users, even when the model underneath was excellent. This case runs the JTBD process on a recurring, non-obvious question: **what job does a knowledge worker actually hire an AI assistant/agent to do — and why do so many wrappers misread it?**\n\n## Step 1 — State product + assumed customer\n\nProduct: an AI assistant/agent (a chat product or an agentic coding/writing tool) built on top of a frontier model. Assumed customer, as most 2023-era wrappers framed it: \"people who want AI-generated text / answers.\" The implicit assumption baked into most products was that the job is *\"produce good output\"* and that the winner is whoever wraps the smartest model with the most features. This is the starting point we will dismantle.\n\n## Step 2 — Switch Interviews\n\nReconstructing the switching moment from widely-reported adoption patterns across 2023–2025 (developers adopting AI coding assistants; writers, analysts, and support teams adopting chat assistants):\n\n1. **First thought:** \"I'm stuck / this will take me all afternoon / I dread starting this.\" The trigger is rarely \"I wish I had AI-written text\" — it's a moment of being blocked, behind, or facing drudgery.\n2. **Circumstance:** a blank page, an unfamiliar codebase, a deadline, a repetitive task (reformatting, boilerplate, first-draft email), or a question whose answer is buried in docs.\n3. **What else they considered:** searching the web, asking a colleague, copying an old template, reading documentation, or simply grinding through it manually.\n4. **Push (what was wrong with the old way):** searching returns generic results that still need synthesis; the colleague is busy; the manual path is slow and boring; getting started is the hardest part.\n5. **Pull (what attracted the new hire):** it gets me *unblocked in seconds*, produces a *good-enough starting point* I can edit, and handles the parts I don't want to do myself.\n6. **Anxiety:** \"Will it hallucinate and embarrass me? Will I ship something wrong? Do I have to check every line — and if so, did it even save me time?\" Trust and verification cost are the dominant anxieties.\n7. **Habit:** having to phrase things as prompts, learning to paste in context, changing where the work starts (in the assistant vs in the IDE/doc).\n8. **First use:** the products that retained users delivered a *\"whoa, that unblocked me\"* moment fast; the ones that didn't left users with plausible-looking output they still had to redo.\n\n## Step 3 — Extract job statement\n\n> **When** I'm blocked, behind, or facing tedious work I don't want to do, **I want to** make concrete progress"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debat... Skill: Jobs to Be Done (JTBD) Owner: deciqai Summary: Activate when: user says 'customers aren't switching to us even though we're better,' 'our churn surveys aren't predicting who actually leaves,' 'we're debat... 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