Streaming LLM Tokens in LiveView, the 2026 Way
Token-by-token LLM streaming in Phoenix LiveView, no React — the 2026 async APIs, plus the production failure modes most tutorials skip.
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Posts tagged AI
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Posts tagged AI
Trust Is the Operating System
One operating system runs a team whether the teammate is a person or an agent. My blueprint: trust, pods, outcomes over hours, managing agents like interns.
What an AI Agent Postmortem Should Contain
Classic SRE postmortems can't explain agent incidents. The sections to add — decision-time context, autonomy rung, permissions delta — with a template.
Building an AI Memory That Outlives Any Single Agent
Your accumulated agent memory is a bet on one vendor's format. Build a portable, git-versioned knowledge layer any agent can read instead.
4,154 Commits in Six Months With AI Agents
I shipped more code in 2026 than the previous four years combined. The commits are real. The productivity is real. What I lost is harder to measure.
Programming Sucks, Now With Agents
An homage to Peter Welch's Programming Sucks, updated for agents: a genius intern with amnesia, hallucinated packages, and a closet that eats your auth layer.
Prompt Injection Defense for a 5-Person AI Startup
Prompt injection defense a five-person team can ship in a week — trust boundaries, least-privilege tools, approval gates, and what not to build yet.
Oban as a Durable AI Agent Runtime in Elixir
Most AI agent frameworks reinvent a job queue badly. Oban already is one — durable, idempotent, retry-aware. Run an agent loop that survives a deploy mid-run.
Amazon Let the AI Drive. It Hit a Tree.
Amazon mandated AI coding, let it touch infrastructure unwatched, and lost millions of orders. The fix wasn't less AI — it was more humans per deploy.
AI Made Tokens Cheap. It's Making Hardware Costly.
Apple raised prices on Mac, iPad, and HomePod, blaming an AI-driven memory shortage. The cost of intelligence is falling; the hardware to run it isn't.
The AI Coding Agent Bugs I Catch Every Week
Eight failure patterns I see running AI coding agents daily — the confident wrong answers, the lost context, and the bugs they reliably ship.
Build an AI Agent Loop in 50 Lines of Elixir
Every AI agent framework runs the same loop: observe, decide, act, repeat. Here it is in 50 lines of Elixir — no framework, just a GenServer.
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 pgvector path in Phoenix, and when Arcana earns its place.
We're About to Stop Making Senior Engineers
The path to senior ran through the grunt work AI now does in one prompt. The knowing-vs-doing gap hits juniors first — and how to grow architects anyway.
Nadella Is Right About AI and the Firm. Mostly.
Satya Nadella's 'token capital' framing is right that AI amplifies human judgment — but it's enterprise advice that skips the small teams who feel it first.
Elixir's BEAM Is the Runtime AI Agents Want
Go won the agent daemon and Python owns the reasoning — but the layer nobody claimed is the one that bites you: thousands of long-lived, stateful, crash-prone agents you must keep alive. That's the BEAM's home turf.
Prompt Skills, Not Claude: Four Rules from Anthropic's Engineers
Most engineers prompt Claude one sentence at a time. Anthropic's own engineers don't — they prompt skills. Four rules from their recent talks, with the operator nuance the talks left out.
How I Prompt Claude as a Staff Engineer (50 Prompts I Actually Use)
Fifty prompts I use to ship production AI features, debug distributed systems, and write docs that don't rot. Code review, debugging, refactoring, system design, and PR-quality writing — with five full examples.
An AI Just Deleted a Production Database in Nine Seconds. Hire More Engineers.
Replit's AI agent ignored a code freeze, wiped a production database in nine seconds, then confessed it violated every principle it was given. The strongest case yet for hiring MORE senior engineers in the AI boom — not fewer.
AI Won't Shrink Your Team — It'll Expose Why You Needed a Bigger One
Every company rolling out AI is about to discover how much work they were leaving on the table. AI doesn't replace headcount — it surfaces the backlog you never had bandwidth to touch. The math behind why velocity creates surface area, the failure mode that follows, and why the companies cutting headcount now are about to get outpaced.
How I'd Run Security at an AI-Native Company in 2026
AI-native companies need a security model that classic appsec doesn't cover. Agents have credentials. Prompts are an attack surface. Training data leaks. The four-layer security stack I'd build, the controls I'd ship in the first 90 days, and the ones I'd defer.
AI-Assisted Engineering Isn't Faster Coding. It's a New Workflow.
Most engineers using Claude Code see a 10–15% speedup. The teams seeing 40–55% aren't typing faster — they're sequencing work differently. The four modes I use AI in, what to never delegate, and how to get a skeptical team across the line.
Your AI Product Needs a Telemetry Layer Before It Needs a Better Model
Most AI startups try to fix the model when the real problem is they can't see what the model is doing. The four-layer AI telemetry stack, the tooling to use, and how proper instrumentation cut a Lavender hallucination rate by 40% without touching the model itself.
When to Trust an Agent and When to Step In
The hardest part of agentic AI in 2026 isn't getting the agent to do the work. It's knowing when to override it. The four-level autonomy ladder, the five signals an agent is going off the rails, and a real example of catching one before it shipped a quietly broken auth flow.
My Daily Agentic AI Workflow
A walkthrough of how I run 4–7 agent sessions in parallel through a normal engineering day. Morning background tasks, mid-morning pair programming, afternoon reviews, end-of-day ops. The interaction modes that work, the handoff protocol, and the trap that makes most agent workflows produce slop.