The reading order
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1.
Elixir's Concurrency Model Is the One You Actually Want
The foundation: processes, supervision, and why the concurrency model other stacks fake with queues and retries is the default here.
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2.
Elixir's BEAM Is the Runtime AI Agents Want
Agents are long-running, stateful, failure-prone processes — exactly the workload the BEAM was designed for four decades ago.
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3.
Why Every AI Agent Framework Is Written in Go (And What That Costs You)
The steelman: why every agent framework picked Go, and the supervision, hot-code, and state-recovery costs hiding in that choice.
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4.
Elixir Is the Language AI Codes Best
Pattern matching, immutability, and a small surface area — why LLMs generate better Elixir than Python or TypeScript.
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5.
Ruby Isn't Dead, It Got Boring — And Boring Is Why It Ships
The counterweight: boring is a feature. If the team knows Rails, the right AI stack might be the one that ships this quarter.
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6.
Build an AI Agent Loop in 50 Lines of Elixir
The whole argument, executable: observe-decide-act in 50 lines with no framework — a GenServer doing what agent frameworks abstract.
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7.
15 Elixir Libraries I Reach For in 2026
The day-one Hex install list — what each library earns its place doing, and the ones that got dropped along the way.
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8.
RAG in Phoenix: Hand-Rolled pgvector or Arcana?
You don't need a vector database — the Postgres you already run does RAG fine. The hand-rolled path, and when Arcana earns its place.
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9.
The Ruby to Elixir Migration That Cut Our Service Footprint From Ten to Six
The production receipts: ten services to six at InsideTrack, the migration order that worked, and when not to migrate.
Other topic guides
- AI engineering What production AI engineering actually looks like in 2026 — the autonomy ladder for agents, the workflow shift, telemetry, and team sizing.
- Security for startups A guided reading order for startup security — what to read first on SOC 2 as a revenue tool, vCISO hiring, and securing AI-native products.
- Engineering leadership Engineering leadership at startup scale — hiring from one engineer to fifteen, rituals that work at small teams, the staff-engineer interview loop.