bulletproof

name	bulletproof
description	Use when building a feature, refactoring, fixing a complex bug, changing architecture, or starting any non-trivial coding task. 12-stage verified dev workflow from research to deploy.

Bulletproof — Adaptive Development Workflow

Author: Artemiy Miller (@artemiimillier) · Telegram · [e-mail] · TG Channel Version: 5.0 · March 2026 License: MIT Compatible: Claude Code, Codex, Gemini CLI, Cursor, Windsurf, OpenCode

Core Principle

Code to solve problems, not code for code's sake.

Before EVERY change ask: "Does this actually solve our problem? Is this the most efficient solution?" If the answer isn't clear — stop, research alternatives, pick the best one.

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Pick Your Mode

Not every task needs the full pipeline.

Size	Examples	Mode	Stages
S	Bug fix, small edit, 1-2 files	Lightweight	1 → 4 → 5 → 6 → 7 → Gates (skip spec/plan)
M	New feature, module refactor, 3-10 files	Standard	Stages 1-10
L	Architecture change, new service, 10+ files	Full	Stages 1-12 (all)

How stages relate: Stages 5-6-7 (Self-Audit, Verification, Impact) run inside each implementation phase as an inner loop. Stages 8-12 run once after all phases complete as an outer loop.

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Context Management (ALWAYS applies)

The 40% Rule

Code quality degrades when context fills beyond 40% ("Dumb Zone"). Rules:

• Stay within 40-60% of the context window
• Manual /compact at 50% — don't wait for auto
• If overloaded: save progress → /clear → fresh start

Fresh Context Between Stages

Every major stage = clean context window:

1. Save stage artifact (research / spec / plan / handoff)
2. /clear
3. Start new stage pointing the agent to the artifact path

Handoff Protocol

Before /clear always create progress/<task>-handoff.md. See templates/handoff.md for format.

Progressive Disclosure

Don't dump the entire codebase into context:

• Research: sub-agents → compact summary
• Planning: summary + key interfaces only
• Implementation: only files for current phase
• In CLAUDE.md: "For details, see path/to/docs.md" (not @file)

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Stage 1: Deep Research

Mode: Read-Only. No code. No changes.

• Launch parallel Explore agents (1 per area: structure, patterns, deps, tests)
• WebSearch: Who has already solved this problem? How did they solve it? What is the most efficient known solution? Don't reinvent — find the best existing approach first.
• Analyze all findings and make a conclusion: which solution is the BEST and why. The research artifact must end with a clear recommendation, not just a list of options.
• Save to thoughts/research/YYYY-MM-DD-<task>.md (see templates/research.md for format)

→ /clear

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Stage 2: Spec / PRD

Mode: Read + Write only in specs/. No code.

Spec = WHAT and WHY. Not how. Spec = contract.

• Read Research Artifact from thoughts/research/
• Create specs/YYYY-MM-DD-<name>.md (see templates/spec.md for format)
• Key sections: Problem, Goal, Scope, Acceptance Criteria, Constraints, Non-Goals

Skip for size S tasks. → /clear

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Stage 3: Planning + Questions

Mode: Read + Write only in plans/. No code yet.

• Read both Spec (specs/) and Research (thoughts/research/)
• Launch Plan agents to check the approach
• Find gaps: what's unthought? What edge cases? What could break?
• Be creative and proactive: anticipate ALL possible problems BEFORE writing code. Think several steps ahead. What could go wrong in a week? A month? Under load? With unexpected user behavior? Solve problems before they exist.
• WebSearch: How have others solved this exact problem? What libraries/patterns exist? What's the proven best practice? Choose the most efficient solution, not the first one that comes to mind.
• After Plan agents verify the approach — rewrite the plan into an improved version incorporating all findings, edge cases, and research results. Not just patch it — rewrite it better.

Challenge Loop (mandatory before finalizing plan)

Before finalizing the plan, answer 3 questions:

1. DOES THIS SOLVE THE PROBLEM?
   Compare every plan item against acceptance criteria from spec.
   If any criterion is uncovered — the plan is incomplete.

2. IS THIS THE MOST EFFICIENT SOLUTION?
   Search: who has already solved this problem? What approach did they use?
   Name 2-3 alternative approaches (including ones found via research).
   For each: pros, cons, effort.
   Justify why the chosen approach is better than all alternatives.

3. IS THERE "CODE FOR CODE'S SAKE"?
   Every change must directly serve acceptance criteria.
   If a change isn't tied to solving the problem — remove it.
   Drive-by refactoring = separate task, not part of this one.

Annotation Cycle

1. Claude drafts the plan
2. Ctrl+G — plan opens in editor
3. User adds > NOTE: annotations
4. Claude: "Address all notes, don't implement yet"
5. Repeat until no notes remain

Questions for User

• Only for real forks where there's a genuine decision to make
• Use AskUserQuestion with options
• For each question: recommend which option you think is best and why
• Don't ask the obvious

Final Plan

Create plans/YYYY-MM-DD-<name>.md (see templates/plan.md for full template with Challenge Log, phases, prompts)

→ /clear

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Stage 4: Phased Implementation

Each phase = separate session, fresh context, feature branch.

Phases can be run in parallel via separate Claude Code sessions/terminals when they don't depend on each other. Check the plan for dependencies before parallelizing.

Guard phrase to start coding: Only begin implementation after the plan is finalized and all annotation notes are addressed. The trigger: "Implement Phase N according to plan."

Order within each phase:

1. Create/switch to feature branch: feature/<task>
2. Update status → in_progress
3. TDD: tests FIRST (red)
4. Implement: code to make tests pass (green)
5. Refactor (if needed)
6. Self-Audit (Stage 5)
7. Verification (Stage 6)
8. Impact Analysis (Stage 7)
9. Gates (see Gates section)
10. Commit (checkpoint)
11. Status → completed, write to Changelog
12. Handoff → /clear

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Stage 5: Self-Audit (after each phase)

Mandatory BEFORE marking completed:

Check the phase implementation:

1. SPEC COMPLIANCE
   Open spec. Walk through every acceptance criterion.
   For each: implemented? Where exactly in code?
   If any not covered — finish it.

2. CHALLENGE THE SOLUTION
   Look at the written code with fresh eyes.
   Does this actually solve the problem from spec?
   Is there a simpler/more efficient way?
   Any "code for code's sake" — changes unrelated to the task?

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Stage 6: Verification — Deep Bug Hunt

Not just linting. Thoughtful review with false-positive filtering.

Step 1: Find errors

Check ALL code from this phase for:
- Logic errors (wrong conditions, off-by-one, race conditions)
- Data handling (null/undefined, type mismatches)
- Security (injection, auth bypass, exposed secrets)
- Performance (N+1 queries, memory leaks, unnecessary re-renders)

Step 2: Verify bugs are REAL

For EACH found bug:
1. Is this a REAL bug or a false positive?
2. Can you prove this bug is reproducible?
3. If you can't prove it — it's NOT a bug. Don't touch it.

RULE: Don't fix code "for beauty" or "just in case".
Fix ONLY proven bugs that actually affect functionality.
Every "fix" without proof = risk of introducing a new bug.

Step 3: Logic and efficiency check

Final code cleanliness check:
- Logic: is the data flow correct from input to output?
- Efficiency: any redundant operations?
- Readability: is the code understandable without comments?
BUT: don't refactor "for beauty". Only if it affects correctness.

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Stage 7: Impact Analysis — "Did we break anything?"

The most underestimated stage. 75% of AI agents break previously working code.

MANDATORY CHECK BEFORE MERGE:

1. REGRESSION
   What other modules/functions depend on changed files?
   Run ALL project tests (not just current phase).
   If anything broke — this is priority #1.

2. SIDE EFFECTS
   Did any contracts/interfaces change (API, props, types)?
   If yes — who uses them? Are all consumers updated?

3. THINK AHEAD
   What problems could these changes cause in a week/month?
   Edge cases we haven't tested?
   What happens with: zero data? Huge data? Concurrent requests?
   What if the user does something unexpected?

4. COMPATIBILITY
   Backward compatibility preserved?
   Data migrations needed?
   Feature flags needed for gradual rollout?

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Stage 8: Integration Check

• All phases completed → run gates across entire project
• Explore agents for audit: everything from spec implemented?
• Every acceptance criterion → fulfilled?

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Stage 9: Code Review (fresh context)

New session. No implementation bias.

• Launch @code-reviewer agent (see agents/code-reviewer.md)
• Checklist: edge cases, race conditions, backward compat, security, error handling, performance
• If possible: cross-model review (different model checks Claude's work)
• Warning: AI reviewing AI has shared blind spots. For critical code — human review is mandatory.

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Stage 10: Security Scan (for M and L)

semgrep --config=auto .
# or
/security-review    # built into Claude Code

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Stage 11: Fixes + Re-verification

If review/scan found issues:

1. Fix (only proven bugs — rule from Stage 6)
2. Re-run gates
3. Repeat Impact Analysis (Stage 7) — fixes didn't break anything else?
4. Re-review if major changes were made

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Stage 12: Cleanup + Deploy

• Archive plan: mv plans/<file> plans/archive/
• Keep spec as documentation
• Squash merge → main
• Deploy — ONLY on explicit user request

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Deterministic Gates

A phase CANNOT be completed without passing ALL required gates.

Tier 1: Required (block the phase)

# Frontend
cd frontend && npx tsc --noEmit          # 0 type errors
cd frontend && npm run lint               # 0 lint errors
cd frontend && npm test                   # all tests green

# Backend
cd backend && python -m py_compile app/main.py
cd backend && pytest --tb=short -q
cd backend && ruff check .

Tier 2: Recommended (for M and L)

npx madge --circular src/         # circular dependencies
npm audit --audit-level=high      # dependency vulnerabilities
pip-audit

Tier 3: Deep Security (for Security Scan stage)

semgrep --config=auto .
# or /security-review

If a gate fails — fix and re-run. Never skip.

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Hooks

Add to .claude/settings.json:

{
  "hooks": {
    "PreToolUse": [
      {
        "matcher": "Bash",
        "hooks": [{
          "type": "command",
          "command": "bash -c \"CMD=$(echo $TOOL_INPUT | jq -r '.command // empty'); echo \\\"$CMD\\\" | grep -qE '(git push.*(main|master)|rm -rf /|DROP TABLE)' && echo 'BLOCKED: Use feature branch / safe alternative.' >&2 && exit 2 || exit 0\""
        }]
      }
    ],
    "Stop": [
      {
        "hooks": [{
          "type": "prompt",
          "prompt": "You are a JSON-only evaluator. Respond ONLY with raw JSON, no markdown.\n\nReview the assistant's final response. Reject if:\n- Rationalizing incomplete work ('pre-existing', 'out of scope', 'follow-up')\n- Listing problems without fixing them\n- Skipping test/lint failures with excuses\n- Making changes unrelated to the stated problem ('code for code's sake')\n- Claiming completion without running verification gates\n\nRespond: {\"ok\": false, \"reason\": \"[issue]. Go back and finish.\"}\nor: {\"ok\": true}"
        }]
      }
    ]
  }
}

---

Git Discipline

• Each task = feature/<task> branch
• Commit after each passed gate (checkpoint for rollback)
• NEVER push to main directly (hook blocks it)
• Squash merge on completion

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Optional Enhancements

PostToolUse: Auto-format after every file write

{
  "matcher": "Write|Edit",
  "hooks": [{
    "type": "command",
    "command": "npx prettier --write \"$FILE_PATH\" 2>/dev/null || true"
  }]
}

Claude generates well-formatted code; the hook handles the last 10% to avoid CI failures.

PreToolUse: Block hardcoded secrets on file write

{
  "matcher": "Write|Edit",
  "hooks": [{
    "type": "command",
    "command": "bash -c \"CONTENT=$(echo $TOOL_INPUT | jq -r '.content // empty'); echo \\\"$CONTENT\\\" | grep -qiP '(api.?key|secret|password)\\s*=\\s*[\\x27\\\"][^\\x27\\\"]{10,}' && echo 'BLOCKED: Hardcoded secret. Use env vars.' >&2 && exit 2 || exit 0\""
  }]
}

Fragile (regex-based) but catches obvious mistakes. For production, use semgrep or /security-review instead.

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Model Recommendations

Stage	Model	Why
Research, Planning	Opus	Cross-file reasoning
Implementation	Sonnet	Speed, cost-efficiency
Code Review, Security	Opus	Deep analysis
Anti-rationalization hook	Haiku	Fast, cheap gate

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Project Structure

project/
├── .claude/
│   ├── settings.json           # hooks config
│   ├── skills/
│   │   └── bulletproof/
│   │       ├── SKILL.md        # ← this file
│   │       ├── templates/
│   │       │   ├── research.md
│   │       │   ├── spec.md
│   │       │   ├── plan.md
│   │       │   └── handoff.md
│   │       └── agents/
│   │           └── code-reviewer.md
│   └── agents/                 # project-level agents
├── CLAUDE.md                   # project brain
├── specs/                      # WHAT and WHY
├── plans/                      # HOW
│   └── archive/                # completed plans
├── thoughts/research/          # research artifacts
└── progress/                   # handoff files