Christian Nennemann 048eab3624 feat: initial 24 principles extracted from real multi-project AI dev work
Grouped into 7 themes: Architecture & Design, Cost & Efficiency,
Execution & Error Handling, Autonomy & Agents, Documentation,
Capture & Learning, Content Production.

Each principle grounded in observed patterns, not theory.
2026-03-31 15:29:46 +00:00

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

(inbox — unsorted ideas)

Drop new principles here. They get organized on next pass.

Description
Principles for building software with AI agents — extracted from real multi-project work
Readme 121 KiB
Languages
Markdown 100%