dogfooding
Run an internal dogfooding program: scenario map, routines, triage spec, ship/no-ship gate.
What it does
Dogfooding
Scope
Covers
- Designing and running a dogfooding loop where the product team uses the product like a real user would
- Creating "creator commitments" when the product is for creators (e.g., publish a podcast, ship a workflow, run weekly reports)
- Capturing issues as reproducible artifacts (not vibes): logs, severity, decisions, owners, and follow-through
When to use
- "Set up a dogfooding program / dogfooding sprint for our product team."
- "We’re shipping soon—make sure we’re using the product daily and fixing the biggest pain."
- "We built this for creators; our team needs to be creators to understand the workflow."
- "Create an internal beta plan and a weekly dogfooding report template."
When NOT to use
- You need to validate market demand or solve who is the customer / what is the problem (do discovery first)
- The product team cannot realistically represent the workflow (e.g., regulated roles, hardware constraints) without proxies
- You’re looking for user research replacement (dogfooding complements -- not replaces -- external user feedback)
- The only goal is "QA everything" (use a QA/test plan; dogfooding is for experience + value + workflow realism)
- You need structured usability testing with real external users, task completion metrics, and think-aloud protocols (use
usability-testing) - You’re planning the actual product launch/release rollout (use
shipping-products) - You need a design critique session to evaluate visual/interaction quality (use
running-design-reviews) - You want to build a framework for developing product taste and quality intuition (use
product-taste-intuition)
Inputs
Minimum required
- Product summary + target user persona (who it’s for; what job it does)
- 1–3 core workflows to dogfood (end-to-end)
- Time box + cadence (e.g., 1 week sprint; 20 min/day; weekly triage)
- Participants (roles) + any "creator commitments" required
- Environment constraints (prod vs staging; data/privacy constraints; access constraints)
Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md.
- If answers aren’t available, proceed with explicit assumptions and label unknowns. Offer 2 scope options (lean vs thorough).
Outputs (deliverables)
Produce a Dogfooding Pack in Markdown (in-chat; or as files if requested):
- Context snapshot (product, persona, workflows, constraints, time box)
- Dogfooding charter (goals, participants, rules, cadence, definitions)
- Scenario map + routines (daily/weekly tasks + "creator commitments")
- Dogfooding log + triage board spec (fields, severity scale, decision rules)
- Weekly dogfooding report (insights, decisions, shipped fixes, next experiments)
- Risks / Open questions / Next steps (always included)
Templates: references/TEMPLATES.md
Workflow (7 steps)
1) Frame the dogfooding goal (experience, not just bugs)
- Inputs: Product summary; desired outcomes; references/INTAKE.md.
- Actions: Define what "success" means for this cycle (e.g., "team can complete workflow A in <10 min without workarounds"). Set constraints (environment, data, access).
- Outputs: Context snapshot + explicit success criteria.
- Checks: Success criteria are measurable and tied to a real workflow outcome (not "feel better").
2) Define representative scenarios + "creator commitments"
- Inputs: Target persona + workflows.
- Actions: Create 3–8 scenarios that represent real user goals. If the product is for creators, define a publish cadence (e.g., "each PM publishes 1 artifact/week").
- Outputs: Scenario map + routine plan.
- Checks: At least 1 scenario is "from scratch → shipped/published" end-to-end.
3) Set up the capture system (log, severity, triage)
- Inputs: Existing tools (Jira/Linear/Notion/Sheets) or "none".
- Actions: Define the dogfooding log schema, severity scale, and triage rules. Decide labels/tags to link issues to scenarios and workflow steps.
- Outputs: Dogfooding log + triage board spec.
- Checks: Any issue can be reproduced with a clear "steps to reproduce + expected vs actual + evidence".
4) Run daily dogfooding sessions (time-boxed)
- Inputs: Scenario map + routines.
- Actions: Each participant runs 1–2 scenarios/day, captures friction immediately, and attaches evidence (screens, logs, timestamps). Record "workarounds used".
- Outputs: Daily log entries + a rolling "top pains" list.
- Checks: Entries are concrete (repro steps) and prioritized by impact on completing the workflow.
5) Triage weekly: decide, assign, and protect focus
- Inputs: Log + top pains.
- Actions: Run triage: cluster duplicates, classify (bug/UX debt/gap/docs), assign owners, and decide "fix now / schedule / won’t fix (with reason)". Update scenario map if it was unrealistic.
- Outputs: Prioritized backlog + decision notes.
- Checks: Top 3–5 issues map directly to blocked/slow scenarios and have an owner + next action.
6) Ship loop: verify fixes by dogfooding again (no-ship gate)
- Inputs: "Fix now" items + release plan.
- Actions: For each fix, re-run the scenario end-to-end. Apply a simple gate: "We can complete the scenario with no hidden workarounds in the chosen environment."
- Outputs: Verified fixes list + any regressions.
- Checks: The gate is based on completing scenarios, not just closing tickets.
7) Report + quality gate + next cycle plan
- Inputs: Final log + triage outcomes.
- Actions: Produce the weekly report. Run references/CHECKLISTS.md and score with references/RUBRIC.md. Add Risks/Open questions/Next steps and propose the next dogfooding cycle focus.
- Outputs: Final Dogfooding Pack.
- Checks: Report contains decisions (what changed) and shows evidence-backed learning (not just a bug list).
Anti-patterns (common failure modes)
- Bug-list-only dogfooding. Treating the dogfooding program as a QA bug bash instead of an experience evaluation. The team files cosmetic bugs but never evaluates whether the core workflow is coherent and valuable.
- Tourist mode. Participants click around casually instead of committing to real end-to-end scenarios. The feedback is shallow ("looks fine") because nobody completed a meaningful task.
- Internal-user bias blindness. Assuming internal team members represent real users without acknowledging their expert knowledge, muscle memory, and workaround tolerance. Findings don’t transfer to actual users.
- Log without triage. Capturing hundreds of issues in a spreadsheet but never running a triage session. Issues pile up, owners are never assigned, and the dogfooding program loses credibility.
- One-and-done sprint. Running a single dogfooding sprint before launch and never repeating. The program produces a snapshot but no continuous improvement loop.
Quality gate (required)
- Use references/CHECKLISTS.md and references/RUBRIC.md.
- Always include: Risks, Open questions, Next steps.
Examples
Example 1 (Creator product): "We’re building a podcast creation tool. Create a dogfooding program where the whole team publishes 1 short episode/week, and produce a weekly report template." Expected: scenarios from "idea to published episode", creator commitments, log schema, triage cadence, and ship gate tied to publishing.
Example 2 (B2B workflow product): "Set up a 2-week dogfooding sprint for our AI meeting notes tool focused on ‘record to summary to share to action items’." Expected: scenario map, daily routine, severity scale, triage rules, weekly report, and a verified-fixes list.
Boundary example (usability testing): "Run a usability study with 5 external users to measure task completion rates."
Response: use usability-testing for structured external user research; dogfooding is for internal team experience evaluation.
Boundary example (launch planning): "We finished dogfooding; now plan the rollout to real users."
Response: use shipping-products to plan the launch; dogfooding validates internal readiness, not external release execution.
Boundary example (no artifact): "Dogfood this idea we haven’t built yet." Response: dogfooding requires a usable artifact; propose discovery + prototype/usability testing first, then a dogfooding sprint once there’s something to run end-to-end.
Capabilities
Install
Quality
deterministic score 0.47 from registry signals: · indexed on github topic:agent-skills · 49 github stars · SKILL.md body (8,622 chars)