Fire Yourself First: The E-Myth Approach to Iteratively AI App Development (arcturus-labs.com)

A practical manifesto: the author adapts Michael Gerber’s E-Myth "fire yourself" philosophy to LLM app development, arguing teams should first do work manually, document the exact steps, then incrementally replace specific tasks with AI. This counters the common but risky impulse to build end-to-end agentic systems from day one. Because LLMs are powerful yet unreliable and prone to hallucination, the recommended path is safer and faster to production: observe, formalize, automate, validate, and repeat. The post gives concrete guidance and a real-world recruiting startup example: start with fully manual resume review, then automate structured data extraction, next introduce an LLM-as-judge for candidate scoring, and finally automate communication by producing email drafts. Technical prescriptions: pick targets with well-defined inputs/outputs or human+LLM workflows; map the human process so the agent can be onboarded like a new employee; modularize to swap in LLM-enhanced components while preserving interfaces; run incremental tests (spot-checks, corner cases) before full evaluation; and iterate until diminishing returns. Key implications: this modular, test-driven approach reduces risk, clarifies failure modes, and yields progressively more reliable agentic features compatible with current LLM limitations.