The AI-Native Elixir Project: What Changes When the Agent is Your Pair
How project structure, tooling, and practices evolve when AI agents are central to development
Deep-dives on Elixir, Phoenix, OTP and distributed systems — code first, from two decades of shipping production software.
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Start with processes, then supervision and observing a running system.
Organize application boundaries, build interactive screens, and test them.
Project structure, code patterns, and the effect of ecosystem stability on AI tools.
Read the method, then follow the evidence through published product audits.
Project structure, code patterns, and the effect of ecosystem stability on AI tools. Articles are listed in suggested reading order.
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Clear filters and show all articlesHow project structure, tooling, and practices evolve when AI agents are central to development
Code patterns that maximize AI agent success—and the anti-patterns that confuse them
A decade of semantic versioning stability means AI agents trained on 2020 code still produce working 2026 code
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