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Business & Systems Analysis · Playbook · Foundation · ~4 min read
BUSINESS & SYSTEMS ANALYSIS · PLAYBOOK · FOUNDATION

Draft User Stories from Evidence, Then Gate Every One Through INVEST

AI turns a synthesized evidence pack into a page of well-formed user stories in minutes — and every one of them reads plausible, which is the trap. This playbook adds the INVEST gate and the "who benefits, and why do we believe that?" challenge that stories must pass before they touch the backlog.

Workflow area: Requirements Quality · Tier: Foundation · Hands-on time: ~25 minutes

Story drafting is mechanical once the evidence exists: actor, need, outcome, in your team's format. That is exactly the work AI does well — and exactly where quality erodes, because generated stories are uniformly fluent whether they trace to a stakeholder need or to the model's idea of what a system like yours usually has. The discipline is a two-stage gate: INVEST for structural quality, and an evidence trace for legitimacy. A story that cannot name who asked for it and where does not get an ID.

When to use — and when not to

  • Use it when you have a validated evidence packsynthesized findings from pb-01, corrected process models, confirmed pain points — and need them decomposed into backlog-ready stories.
  • Use it when converting a legacy requirements doca BRD moving to an agile delivery team can be exploded into stories fast, with each story citing its source section.
  • Use it when story quality is driftinga team whose stories keep bouncing back from refinement ("too big", "not testable") benefits from the INVEST gate as a standing pre-check.
  • Skip it when the evidence is thingenerating stories from a one-line feature idea produces confident fiction; do the elicitation first (pb-01, pb-02).
  • Skip it for spikes and enablers that don't fit the templateforcing "As a developer, I want a database migration" through user-story format is theater; write a plain task.

The recipe

  1. Stage the evidence. Gather the synthesis document, relevant findings with their citations, and your team's story conventions — format, definition of ready, story-point norms, and two or three examples of stories the team considers good.

  2. Generate stories bound to evidence.

    You are a business analyst drafting user stories for an agile team.
    Team format: [PASTE 2-3 EXAMPLE STORIES SHOWING YOUR CONVENTIONS]
    Definition of ready: [PASTE OR SUMMARIZE]
    
    From the evidence pack below, draft user stories.
    
    For each story produce:
    - TITLE
    - STORY: As a [specific role], I want [capability], so that
      [outcome the evidence supports].
    - EVIDENCE: which finding(s) this story traces to, quoted — e.g.
      "[S1, Ops lead, 14:32] ..." — copied exactly from the pack.
    - NOTES: open questions, dependencies, assumptions marked
      (ASSUMED).
    
    Rules:
    - Every story MUST trace to at least one finding. If a capability
      seems obviously needed but has no evidence, put it in a separate
      list titled UNSUPPORTED CANDIDATES — do not dress it as a story.
    - One user-visible outcome per story. Split anything compound.
    - The role must be a real role from the evidence, never "user".
    - Do not invent business rules, thresholds, or process steps that
      are not in the pack.
    
    Evidence pack:
    [PASTE SYNTHESIZED FINDINGS]
    
  3. Run the INVEST gate as a separate pass. Do not let drafting and critique share a prompt — the model grades its own homework leniently. Start a fresh conversation:

    You are a skeptical agile coach reviewing user stories. For each
    story below, score it against INVEST:
    
    - Independent: can it ship without waiting on another story here?
    - Negotiable: does it specify a solution instead of a need?
    - Valuable: WHO benefits, and does the cited evidence actually
      show they want this? Challenge weak "so that" clauses.
    - Estimable: could a team size this without a spike?
    - Small: deliverable within one sprint?
    - Testable: could acceptance criteria be written with a clear
      pass/fail?
    
    Output per story: PASS or FAIL per letter, one-line reason for
    each FAIL, and a suggested split or rewrite where applicable.
    Be strict: a story that names no specific beneficiary FAILS V.
    
    Stories:
    [PASTE DRAFTED STORIES]
    
  4. Read a sample of good gated output and act on it.

    STORY: As an intake clerk, I want duplicate vendor detection at
    entry, so that I stop reconciling duplicates at month-end.
    - I: PASS · N: PASS · V: PASS — traces to [S1, Ops lead, 19:04]
      "we found 340 duplicate vendors last quarter"
    - E: PASS · S: FAIL — detection plus merge workflow is two
      sprints; split merge into its own story.
    - T: PASS
    

    Apply the splits and rewrites yourself — you are the editor, not the courier. Anything in UNSUPPORTED CANDIDATES goes to your elicitation backlog, not the product backlog.

  5. Human-verify the trace before backlog entry. For each surviving story, open the cited finding and confirm the story says what the stakeholder meant — not a plausible generalization of it. Then load stories into Jira or Azure DevOps with the evidence citation in the description. Future-you, defending a story in refinement, will need it.

Make it yours

  • Claude Project as the team's story mill: pin team conventions, definition of ready, and the two prompts in a Project; every analyst then drafts and gates in the same house style.
  • Jira + Rovo / Azure DevOps Copilot: once stories are in the tool, use the native assistant for in-place edits and duplicate detection against the existing backlog — but keep the INVEST gate in your chat tool, where you control the rubric.
  • ChatGPT for the compact variant: merge steps 2 and 3 into one prompt with an explicit "draft, then critique in a second section" instruction when working solo on small batches — accept slightly softer critique as the price of speed.
  • Gemini in Workspace: teams living in Sheets can run the gate as a rubric table — stories in rows, INVEST letters in columns — which product owners find easy to scan in refinement prep.

Quality check

  • Every story traces to real evidencethe citation exists, is quoted accurately, and the stakeholder actually meant this; a story with a decorative citation is worse than one with none.
  • No invented specificsthresholds, field names, and business rules in stories all come from the pack, not from the model's sense of the typical.
  • The beneficiary is named and plausible"as a user" or a "so that" clause restating the "I want" clause means the value case is missing.
  • Splits happenedif every drafted story passed S on the first try, your gate is too soft; evidence-dense stories almost always hide a compound.
  • UNSUPPORTED CANDIDATES stayed out of the backlogthey are elicitation questions for the next stakeholder session, and validating them there closes the loop.
  • The product owner reviewed value, you reviewed traceabilitythe gate assists prioritization; it never replaces the human owner's call.
Warning

Evidence packs quote stakeholders by role and sometimes carry volumes, costs, and vendor names — run story generation in your organization's approved AI workspace, and keep verbatim stakeholder quotes out of externally shared backlog tools unless your consent terms cover it.

Pro Tip

Keep the INVEST critique output attached to each story through refinement — when a developer asks "why is this split so small?", the FAIL line that caused the split is the answer, and the team learns the gate's standards by osmosis.

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