Solo Methodology
AI-driven solo development — how one person ships products using LLM agents, harness engineering, and automation.
Open Source Tools
| Project | What | Stars |
|---|---|---|
| solo-factory | Claude Code plugin — 27 startup skills, 3 agents, privacy-first pipeline | 14 |
| solograph | Code intelligence MCP server — multi-project code graph, semantic search, session history | 3 |
| openai-oxide | Idiomatic Rust client for OpenAI API — 1:1 parity with openai-python | 20 |
| rust-code | AI-powered terminal coding agent in Rust — TUI, structured agent loop, MCP | 7 |
| supervox | Voice pipeline toolkit — STT, VAD, TTS for Rust voice apps | 0 |
| airq | CLI air quality checker — any city, Open-Meteo + Sensor.Community | 0 |
| rustman-blog | This blog — Astro static, wiki content, CF Pages | 0 |
Pages
Harness Engineering
- harness-engineering-summary — Harness engineering: agent mistake → fix harness, 3 components, 6 adoption steps
- agent-mistake-fix-harness — Core loop: CLAUDE.md → linters → structural tests. Ratchet effect
- context-engineering — Context as code: CLAUDE.md as TOC, progressive disclosure, dynamic context
- agent-self-discipline — Drift detector, complexity thresholds, evolution = commit
Principles & Frameworks
- stream-six-layers — STREAM: principles as dependency graph, not flat list
- antifragile-life-design — Barbell for solo: 90% consulting + 10% products
- one-pain-one-feature-launch — Ship one thing in days, not platforms in months
- portfolio-approach — Multiple small bets, not one big bet
Knowledge Graphs & Memory
- context-graphs-summary — Context graphs: agent decision trajectories as compounding asset
- decision-traces-compound — Each agent action improves future ones via precedent retrieval
- codegraph-guide — CodeGraph: code intelligence across projects via FalkorDB + tree-sitter
Development Patterns
- dev-principles-summary — 993-line reference: SOLID, TDD, DDD, Clean Arch, i18n, infra, code quality
- cli-first-testing — Every project gets CLI mirror,
make integrationmandatory - schema-guided-reasoning — SGR: schemas → logic → UI. Agent reads schemas first
- enterprise-rag-challenge — ERC: structured outputs beat vector search in production RAG
- tool-calling-four-layers — Tool calling internals: HTTP → chat template → constrained decoding → parser
Infrastructure
- infra-two-tools — SST + Pulumi, serverless by default, 4 tiers
- background-jobs-ladder — Cron → CF Workers → Prefect → Temporal
- rag-patterns — 7 RAG approaches from vector to agentic
Open Questions
- Optimal agent team size for solo dev?
- When to use subagents vs sequential work?
- How to prevent context window waste?