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# AI Dev Principles
> Living document. Principles discovered while building with AI agents.
> Extracted from CLAUDE.md files, memory, project configs, and observed patterns.
> Drop ideas in chat — they land here.
---
## Architecture & Design
### 1. Single Source of Truth
One file, one config, one definition. Never maintain the same information in two places.
- Dockerfile: one shared by all agents
- Queue: `queue.json` is canonical, markdown table is a view
- Voice profiles: YAML is source, generated text is output
**Test:** If you change something, how many files do you need to touch? If >1, you have a SSOT violation.
### 2. Vertical Spike Before Framework
Validate architecture through working code, not docs. Don't write 1000 lines of specs for zero lines of working code. Frameworks are extracted from spikes, not theorized upfront.
**Origin:** afet validation strategy — spike first, then extract. Dogfood with a real project.
### 3. Convention Over Configuration
Reduce decisions by establishing patterns that just work.
- Conventional commits everywhere (`feat:`, `fix:`, `docs:`)
- `docs/status.md` in every project (same format)
- Queue priority: P0 > P1 > P2 > P3
- Agent picks up work without being told which item is next
### 4. Agent-First Design
Build frameworks and tools that agents can use, not just humans. Measure agent ergonomics.
- Schema-free entities (type + status + JSON meta) — agents don't need to learn fixed schemas
- Config-driven: new types/statuses/fields = TOML, never code changes
- Standard tool interfaces (MCP) so any agent can plug in
**Origin:** tool.affordance — 380 tests, agent ergonomics testing built in.
### 5. Don't Make Me Think (About Infrastructure)
Dev environment changes propagate automatically. No manual rebuild, no "remember to also update X".
- One Dockerfile, auto-detected by all consumers
- devcontainer features for language runtimes
- post-create scripts for project-specific setup
- If a human has to remember a step, it will be forgotten
---
## Cost & Efficiency
### 6. Cheapest Model per Task
Don't use Opus for what Haiku can do.
| Task | Model | Cost |
|------|-------|------|
| Validation, guardrails, diff | Haiku | $0.80/MTok |
| Creative writing, rewrites | Sonnet | $3/MTok |
| Architecture, complex reasoning | Opus | When needed |
Two-pass approach: Haiku draft + Sonnet polish = 80% savings vs Sonnet throughout.
### 7. Budget-aware by Default
Track every token. No surprise bills.
- `--dry-run` before expensive operations
- Cost estimation before fan-out
- CostGuard with hard limits per session
- Batch API for bulk (50% discount)
- Prompt caching for repeated system prompts (90% on reads)
- Report estimated vs actual after runs
- Budget decisions >$10 require user consent
### 8. Batch, Cache, Deduplicate
Before implementing any API operation, proactively optimize:
- **Batch**: group N items per call (100 rows/insert, not 1)
- **Cache**: static reference data between runs
- **Dedup**: hash-based skip of already-processed items
- **Incremental**: upserts and delta syncs, not full re-processing
- **Parallelize**: async/concurrent where rate limits allow
- **Respect limits**: throttle proactively, don't react to 429s
State the optimization strategy when proposing a workflow.
---
## Execution & Error Handling
### 9. Checkpoint / Resume
Every long-running operation must be interruptible and resumable.
- Save progress incrementally, not all at the end
- Hash-based dedup so restarting skips completed work
- JSONL for append-only progress logs
- Killing a stuck task must not lose completed work
### 10. Diagnose Before Retrying
When something fails, understand why before trying again.
- Read the error message. Check logs. Understand the cause.
- Never retry the same command hoping for a different result
- Never add broad `try/except` or `|| true` to suppress errors
- Never sleep-loop waiting for things to work
- Fix the root cause, then try once more
### 11. Fail Forward
Don't block on one broken thing. Document it, next item.
- Error → log it → move to next queue item
- Missing dependency → note it → work on something else
- Rate limit → save progress → switch tasks
- Unsolvable error → document in status, move on
### 12. Read Before Write
Understand existing code before changing it. Match the project's patterns, don't invent new ones.
- No `todo!()`, `unimplemented!()`, `pass` in production code
- Fix lint/test failures before committing
- If a pre-commit hook fails, make a NEW commit (never `--amend` after failure)
- Never silence warnings to make code compile — fix the root cause
---
## Autonomy & Agents
### 13. Autonomous but Auditable
Agents work independently. Humans can always follow what happened.
- Status logs updated after every sprint
- Control center as handoff document between sessions
- Conventional commits with meaningful messages
- No silent failures — document and move on
### 14. Parallel by Default
Never sit idle when there's work that can run concurrently.
- Multiple agents on independent projects simultaneously (up to 4-5)
- Background scouts while foreground work continues
- If blocked on one thing, pick up the next queue item
- Use idle time productively — check the task list
### 15. Dual-Agent Routing
Different agents for different task shapes. Route to strengths.
- **Claude Code**: long-running, autonomous, shell-native, writing, research, tests
- **Cursor**: interactive, codebase-aware, multi-file edits, UI/web, PR-scoped
- Each queue item has an `agent` field. Agents only pick their own items.
- Handoff protocol between agents to avoid collisions
### 16. Session Handoff Protocol
Every session writes a handoff so the next session can resume without re-discovery.
- Fill "Letzte Session" in control-center before ending
- Update project's `docs/status.md` with what was done
- Fields: date, channel, projects touched, completed, blocked, next step
- Read handoff at session start — this IS the context
### 17. Worktree Safety
When agents work in isolated worktrees, protect uncommitted work.
- Agents must commit before finishing
- Check for uncommitted changes before deleting worktrees
- Save work as named branches before cleanup
- Never use TeamDelete as a shortcut — it destroys worktrees
---
## Documentation & Knowledge
### 18. Documentation as First-Class Deliverable
Not an afterthought — parallel to code.
- Every architectural decision gets an ADR
- Master Prompts and Book docs updated alongside code
- Security by design, not bolted on
- New concepts captured immediately, not retroactively
### 19. Script Everything
Multi-step workflows, automations, reusable commands → save as scripts in `scripts/`. Never just execute ephemeral commands.
- Include a brief comment header explaining what the script does
- Reproducibility, auditability, handoff clarity
- If you did it twice, it's a script
### 20. Memory as Institutional Knowledge
Persistent memory bridges sessions. Only save what a future session would need.
- API quirks, DB schemas, key architectural decisions
- Not routine operations or task progress
- Check at session start to avoid re-discovery
- Update or remove stale memories
---
## Capture & Learning
### 21. Zero-Friction Capture
Ideas, principles, and decisions are capturable in the moment without switching tools.
- The conversation is the inbox
- Agent triages and routes automatically
- Principles are extracted proactively from observed patterns
- User validates by not objecting
### 22. Proactive Principle Detection
When a decision is made, a pattern repeats, or an approach is confirmed — check if there's an underlying principle worth capturing. Don't ask. Just add it and mention briefly.
---
## Content Production
### 23. Voice Profile Consistency
Writing follows defined voice profiles with guardrail enforcement.
- Kombi B: essayistic + provocative-analytical
- No fictional characters, no coaching language, no listicles
- "Follow the money" in every chapter
- Structure: Strukturanalyse → Philosophie → Daten → Praktische Übung
- Automated guardrail checks before publishing
### 24. Persona / Series / Volume Hierarchy
Content scales through structured inheritance.
- Persona (author identity) → Series (universe rules) → Volume (individual book) → Fan-Out (publisher × language variants)
- Volume override > series default > persona default > global default
- One persona can write multiple series; each series has shared terminology and rules
---
## Infrastructure
### 25. Tool Auto-Provision
When an agent needs a tool that isn't installed, it should install it automatically — not block and ask.
- Container should support on-demand tool installation (apt, npm, go install, curl binary)
- Dockerfile covers the 80% case; auto-install covers the long tail
- Log what was installed so it can be baked into the Dockerfile later
- Never let a missing `jq` or `go` derail a 30-minute sprint
**Origin:** "Wenn irgendwas fehlt wie go — wir brauchen die Möglichkeit ein Tool passthru oder auto-install zu ermöglichen"
---
## Quality & Process
### 26. PDCA Every Sprint
Plan-Do-Check-Act after every sprint, not just at the end. Check catches bugs before they compound.
- Plan: define features + acceptance criteria
- Do: implement with team, commit after each feature
- Check: test in production, read debug logs, try bad inputs, verify on mobile
- Act: fix everything found before starting next sprint
- Never skip Check. A shipped bug costs 10x more than a caught bug.
**Origin:** Sprint 1-3 each had a PDCA cycle that caught rate limiting issues, SSE race conditions, and Caddy routing gaps.
### 27. Test in Production (for fast prototyping)
For single-user tools in rapid prototyping: test against the real deployment. Mocks hide integration bugs. **Grain of salt:** This applies to MVPs and personal tools. For multi-user, shared, or safety-critical systems, use proper staging environments and test suites.
- Fast prototyping: `curl` against live API, try PWA on real phone, submit real jobs
- Production-grade: staging environment, automated test suite, canary deploys
- The principle is about speed of feedback, not skipping quality gates
- Know when you've graduated from prototype to product — then add proper testing
**Origin:** "Committe regelmäßig und test in production — keine mocks!" (during rapid MVP sprint)
### 28. Changelog as First-Class Artifact
Every project gets a CHANGELOG.md. Updated with every sprint. The user should never have to ask "what changed?"
- Reverse-chronological, grouped by version/sprint
- Include Added/Changed/Security/Fixed sections
- Link to relevant commits if helpful
- Update it DURING the sprint, not after
**Origin:** "Ich brauch gute changelogs um bei allem laufenden zu bleiben."
### 29. Emergency Stop (Not-Aus)
Every autonomous system needs a kill switch. One button, kills everything, no confirmation cascade.
- Cancel all running jobs immediately
- Pause the system (workers stop polling)
- Log the event as critical
- Resume button to unpause
- Visible at all times, not buried in a menu
**Origin:** "Und wir brauchen einen Not-Aus-Knopf ;)"
### 30. Self-Monitoring (Guardian Pattern)
The system monitors itself. A background watchdog checks health every N minutes and logs findings.
- Check: stuck jobs, dead workers, error spikes, DB connectivity
- Log structured findings to a queryable debug_log
- Agent can read the logs to self-diagnose
- Future: alert the user via push/webhook when degraded
- Clean up old logs automatically
**Origin:** "We should have a guardian who checks every other minute what's going on."
### 31. Debug Logs as Agent Interface
Structured debug logs aren't just for humans — they're an API for the agent to understand system health.
- Queryable by level, component, time range
- Secret-safe (auto-redact tokens, keys, passwords)
- Agent reads them between sprints to catch issues
- Self-healing: agent detects error patterns and applies fixes
**Origin:** Built during dispatch development — agent reads `/debug/logs` to diagnose production issues.
### 32. Multi-Layer Auth for Admin Endpoints
Regular API operations and admin/debug operations need different auth levels.
- Regular token: job CRUD, worker operations
- Admin token: debug logs, stats, worker management, emergency stop
- Rate limiting: stricter on admin endpoints
- Never share the same token for both levels
**Origin:** "Ich hoffe wir haben da ne mehrstufige Authentifizierung dahinter..."
---
### 33. Container-First Development
Use containers wherever possible — for isolation, reproducibility, and security.
- Dev environments: devcontainer (one Dockerfile for all agents)
- Agent execution: run Claude Code in sandboxed containers (claudine)
- Worker jobs: execute in ephemeral containers, not on the host directly
- Dispatch workers: should spin up containers per job (isolation, cleanup, no state leakage)
- Testing: container-based test environments matching production
- Production: containerized services (not bare-metal pip installs)
The goal is not containers for containers' sake — it's **isolation + reproducibility + disposability**. A crashed job shouldn't affect the host. A rogue agent shouldn't access other projects.
**Origin:** "Wir sollten noch darauf achten so viel wie geht Container sinnvoll zu nutzen"
**How to apply:**
- Dispatch Sprint 4+: Workers should optionally run jobs inside containers
- `claudine` already does this for Claude Code sessions
- Dev environment already uses `.devcontainer/Dockerfile`
- Next step: containerized worker execution (docker/podman per job)
### 34. Git Worktrees for Agent Isolation
When multiple agents work on the same repo, use git worktrees instead of branches. Each agent gets a full working copy without cloning.
- Agent writes to its own worktree — no merge conflicts during work
- Main branch stays clean until merge
- Agents can work in parallel on the same files
- Worktree = disposable sandbox. Commit → merge → delete.
- Cheaper than containers for code-only isolation (no image build, instant)
**Combination with containers:** Container for runtime isolation (process, network, filesystem). Worktree for code isolation (git history, no conflicts). Best of both:
- Agent runs in container (sandboxed execution)
- Container mounts a worktree (isolated code copy)
- Agent commits to worktree branch
- Team lead merges worktree branches → main
**Origin:** "Genauso wie git worktree, was wohl auch sehr clever ist"
**Caveat:** Worktree safety is critical — agents MUST commit before worktree deletion. See Principle #17 (Worktree Safety).
---
## (inbox — unsorted ideas)
- **Least-privilege agent access**: Agents should SSH as a dedicated non-root user (e.g. `deploy@`) with scoped sudo for only what they need (systemctl, caddy reload). No root SSH long-term.
- **Immutable deploy artifacts**: Agent builds a tarball/image, uploads it, runs a deploy script. Never edits files in-place on production.
- **Multi-node same-repo**: Multiple workers (laptop + vserver) working on same git repo but different features. Merge conflicts → Gitea Actions hook or team-lead merge strategy. Start small: one worker per repo. Scale: worktrees per feature.
- **Prioritize small+working over ambitious+broken**: "Lieber erstmal klein und funktionierend und dann mehr." Collect ideas, implement incrementally, never ship broken.
_Drop new principles here. They get organized on next pass._