AI Solopreneur Engineer

7 modules, 65 lessons. Build AI products solo — principles, frameworks, tools, and real projects.

Powered by solo-factory — a Claude Code plugin that implements this methodology as executable skills.

Module 1: Mindset & Philosophy

Why build. What to believe. How to think about risk, creativity, and freedom.

Result: Clear personal manifesto. Decision framework installed.

1.1 posts Solo Founder Manifesto 1.2 wiki Origin story — Life2Film to SuperDuperAI, second mountain 1.3 wiki Antifragile life design: barbell across domains 1.4 wiki Ikigai as 8-9 daily micro-joys, not a mission 1.5 wiki Optimizer syndrome: best choice ≠ more happiness 1.6 wiki Portfolio approach — multiple small bets, not one big bet 1.7 wiki Privacy is architecture, not a feature

Module 2: Decision Making

Frameworks for decisions at every level — from epistemics to daily ops.

Result: STREAM framework applied to one real decision. Kill/iterate/scale thresholds set.

2.1 posts STREAM Framework: 6 Layers Decision System 2.2 wiki STREAM: principles as hierarchy, not a flat list 2.3 wiki 5-step decision framework: from epistemics to action 2.4 wiki Decision Making 2.5 wiki Kill / Iterate / Scale — weekly decision rules 2.6 wiki One pain → one feature → launch

Module 3: Validation & Launch

From niche selection to live product with traffic in 5-9 days.

Result: One niche scored via S.E.E.D. Fake-door test run. Go/kill decision made.

3.1 posts Launch Playbook: From Niche to Revenue 3.2 wiki S.E.E.D. — niche scoring in 10 minutes 3.3 wiki Startup Validation 3.4 wiki Solopreneur success patterns — benchmarks, pricing, distribution 3.5 wiki 2026 validated app ideas — homeschool, family productivity, privacy-first 3.6 wiki Inspiration sources — curated channels, communities, newsletters

Module 4: Engineering Foundations

Schemas first, CLI-first, clean architecture, privacy by design.

Result: Project scaffolded from stack template. CLAUDE.md configured. Pre-commit hooks running.

4.1 wiki Universal Development Principles — every project, any stack 4.2 wiki SGR — schemas first, logic second, UI last 4.3 wiki SGR complete guide — code examples, patterns, structured output 4.4 wiki CLI-first testing — every project gets a CLI mirror 4.5 wiki Privacy-First Architecture 4.6 wiki Infrastructure: two tools, serverless by default 4.7 wiki Background jobs — cron → CF Workers → Prefect → Temporal → Trigger.dev 4.8 wiki KMP sync — Supabase + PowerSync for offline-first cross-platform 4.9 wiki PostHog analytics: one product = one project, cross-platform identity

Module 5: AI Agent Engineering

Harness, memory, context, testing, code review with agents. The core of the course.

Result: Harness file tuned. Memory system configured. Agent does reliable work on your real tasks.

5.1 posts Harness Engineering — Development in the Age of Agents 5.2 wiki Context engineering — context as code 5.3 wiki Agent mistake → fix the harness, not the prompt 5.4 wiki Agent self-discipline — drift detector and complexity thresholds 5.5 wiki Agent sandboxing — safe LLM agent execution on Mac 5.6 posts Agent Memory Architecture: From Working Memory to Compound Learning 5.7 wiki MemPalace — spatial memory architecture for AI agents 5.8 posts Context Graphs — Agent Trajectories and Organizational Memory 5.9 wiki Decision traces compound — each agent action improves future ones 5.10 wiki RAG patterns — 7 approaches from vector to agentic 5.11 wiki Enterprise RAG Challenge — what actually wins in production RAG 5.12 wiki Token-efficient web requests — HTTP Accept header trick for agents 5.13 wiki Tool calling internals — four layers from HTTP to parser 5.14 wiki Agent benchmarks — how to measure if your coding agent actually works 5.15 wiki ERC3 — Enterprise RAG Challenge 3: AI Agents in Action 5.16 wiki Apple Foundation Models — zero-cost on-device AI for iOS portfolio 5.17 wiki Agent patterns from practice — skills vs MCPs, dream mode, self-evolution, teaching→skill 5.18 posts Agent-Bit: building a PAC1 competition agent in Rust

Module 6: Solo Factory: The Toolkit

Claude Code plugin as the practical framework. 30 skills grouped by pipeline phase.

Result: Solo-factory installed. 3-5 skills used on a real project. Custom skill created.

6.1 projects solo-factory — Claude Code plugin for solopreneurs 6.2 wiki Agent toolkit landscape — from prompt libraries to autonomous project managers 6.3 wiki CodeGraph — code intelligence across all projects via FalkorDB + tree-sitter 6.4 projects solograph — code intelligence MCP server 6.5 wiki LLM providers & startup credits — where to get models, free tiers, and funding 6.6 wiki Television (tv) — fuzzy terminal search for wiki and code

Module 7: Case Studies

Real projects demonstrating the principles. Each one: problem, approach, result, lessons.

Result: Your own project shipped end-to-end using the methodology.

7.1 projects openai-oxide — idiomatic Rust client for OpenAI API 7.2 projects rust-code — AI terminal coding agent in Rust 7.3 projects airq — CLI air quality checker 7.4 projects Invoice CRM — free file-based invoice generator for freelancers 7.5 projects You2Idea — AI startup idea search from YouTube 7.6 projects SuperDuperAI — the company behind the products 7.7 projects SuperStoryboard — AI storyboard generation with Figma sync 7.8 projects Life2Film — turn everyday moments into meaningful montages 7.9 projects FaceAlarm — face yoga tracker with daily selfie alarm 7.10 projects KubizBeat — Bashkir kubyz instrument app 7.11 projects SEO CLI — all search engine data in one terminal 7.12 projects SuperVox — voice pipeline toolkit for Rust 7.13 projects OpenWok — transparent food delivery platform

New lessons auto-added when wiki pages get course_module in frontmatter.

Manifesto · Solo Factory · GitHub · Book a call