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Lightweight AI forward engineering standards for software development
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Developer toolsPython · JavaScriptGitHub @rmorisonOnlineOwner unconfirmed
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Lightweight development practices and standards for software projects.
This repository defines engineering standards for building software. The standards are intentionally lightweight to support early-stage agile development while providing enough structure to maintain quality and enable effective collaboration—both human-to-human and human-to-AI.Read the full README ↗Lightweight development practices and standards for software projects.
To adopt them in a new or existing project, start with QUICKSTART.md: the steps in order, with snippets to copy and a prompt that has a Claude Code session carry them out.
This repository defines engineering standards for building software. The standards are intentionally lightweight to support early-stage agile development while providing enough structure to maintain quality and enable effective collaboration—both human-to-human and human-to-AI.
.claude/ directory template)agent-team starts an agent team in one stepDefines how and when to create documentation:
docs/ directory organization)Key principle: Documentation is the source of truth. Write specs before code, keep them current, focus on decisions and context rather than implementation details.
Defines the process for product/business-driven feature work from concept to production:
Key principle: Intent → Spec → Plan → Execute → Validate. Small scoped changes, continuous validation, spec-driven development.
Detailed guidance for Phase 3 of the feature development workflow:
Project management as a discipline deserves its own detailed standard while keeping the feature development workflow lightweight.
Engineering-driven work separate from product features:
Key distinction: Feature work is driven by product/business stakeholders; technical work is driven by engineering directives and engineers directly.
Branch management and version control workflow:
main + feature branchesKey principle: main is always deployable. All work happens in issue-based feature branches merged via pull requests.
How to organize issues, track epics, and manage multi-issue initiatives in GitHub:
Key principle: Use GitHub's native features (sub-issues, labels, milestones) for lightweight, scalable issue organization without external tools.
What every repository needs besides its code, public or private:
Key principle: Start from the smallest required set, and say plainly what each check cannot see.
Operational reference for adopting compound-engineering (CE) as the canonical realization of Layers 2–5 of the six-layer AI architecture. Covers artifact path mapping, ticket-tracking modes (team-scale and solo + AI), branch-naming reconciliation, AI-review discipline, and the CE skill ↔ standards doc cross-reference. Self-contained — usable by any adopter without rmorison context.
Key principle: The architecture is the abstraction; CE is one canonical realization. Vendor-neutral baselines remain in place for projects that don't adopt the plugin.
An opt-in operating model for one human directing several AI agent sessions: the operator signs off and merges, a lead coordinates, and one worker runs each ticket. Covers roles, the sprint loop, traffic between parallel tickets, a worker handoff template, the lead's Done-gate checklist, operator interaction (quiet mode), and how to adopt or decline it.
To start one, install the agent-team plugin and run its start-team skill, or start the lead by hand: see the Quickstart.
Conversation logs documenting the development and evolution of these standards through AI agent collaboration.
What's included:
These transcripts provide historical context and reasoning behind the standards, useful for understanding why certain approaches were chosen and how to adapt them appropriately.
Defines how AI tooling integrates with software engineering workflows. The architecture is the abstraction; specific toolkits — most concretely compound-engineering (CE) for Claude Code — fill the layers as canonical realizations. Vendor-neutral baselines live in this repository for projects that don't adopt a specific toolkit.
| # | Layer | Principle | Vendor-neutral baseline |
|---|---|---|---|
| 1 | Rules | Persistence — always-loaded session context | ai/claude-code/rules/ (this repo); templates/CLAUDE.md (an adopter's) |
| 2 | Workflow Skills | Composability — multi-step orchestrators | templates/.claude/skills/ |
| 3 | Persona Agents | Perspective — multiple expertises | templates/.claude/agents/ |
| 4 | References | Progressivity — context grows with workflow depth | (none yet) |
| 5 | Compound / Learnings | Compounding — institutional knowledge accumulates | (none yet) |
| 6 | Hooks | Determinism — non-AI enforcement at zero context cost | templates/.claude/hooks/ |
CE fills Layers 2–5. What it puts in each slot — skills, personas, reference subtrees, artifact paths — lives in process/compound-engineering-integration.md, which tracks it against a stated CE version. Layers 1 and 6 stay owned by your project: Layer 1 as its root CLAUDE.md, Layer 6 as its .claude/hooks/.
Key principle: Context is expensive — only load what's needed, when it's needed. The six layers each specialize this principle for a different context-cost slot.
For the architectural decision and full layer descriptions, see ADR-0001 and ai/claude-code/README.md. For CE adoption operational details, see process/compound-engineering-integration.md.
Starter kit for adopting these standards in new projects with Claude Code:
templates/.claude/ into your project root as .claude/ — provides Layers 2 (skills), 3 (agents), 6 (hooks) baselines plus configuration.templates/CLAUDE.md to your project root and fill in the placeholder sections — this is the project's Layer 1 (rules). The ai/claude-code/rules/ baseline in the table above is this repository's own Layer 1 and is not copied; draw on it when filling CLAUDE.md in.process/compound-engineering-integration.md for the operational details. CE specializes Layers 2, 3, 4, and 5 with deep implementations; Layers 1 and 6 stay owned by your project — Layer 1 as its root CLAUDE.md, Layer 6 as its .claude/hooks/.The vendor-neutral skills reference the canonical standards via URL, so they stay in sync without duplication.
These standards prioritize working software over process compliance. Use judgment:
Write specifications before code. Specs:
The spec is source of truth. Code implements the spec.
Ship small increments frequently. Validate early. Learn from users. Iterate based on feedback. Don't over-engineer for hypothetical future requirements.
Modern development increasingly involves AI coding assistants. These standards work well with AI:
These are standards, not laws. Deviate when:
When deviating intentionally, document why in the commit message or PR description.
These standards will evolve:
Draft - These standards are in active development and subject to revision based on practical experience.
Open an issue or submit a PR to discuss improvements to these standards.