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Notes from building agents in public.

Build logs and hot takes on agentic systems, retrieval, and the unglamorous infrastructure that makes AI reliable.

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9 posts
FeaturedAI Systems7 min read

The Model Doesn't Do Anything. Your While Loop Does.

Function calling means the model emits a request and your code runs it. The dispatch table, the loop, the state dict: that is the engineering. Build the loop well and a mediocre model behaves like an agent.

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AI SystemsMay 2026

Evaluating AI Agents Like You Ship Software

How I built evaluation pipelines for non-deterministic systems, and why vibes-based testing doesn't scale.

7 min read →
InfrastructureApr 2026

Designing Retry-Aware Infrastructure

Notes on queues, idempotency keys, and what it actually means to recover gracefully from failure.

6 min read →
Product EngineeringMar 2026

From Prototype to Production

What changes when a demo becomes load-bearing. The cuts, the rewrites, and the thing nobody tells you.

5 min read →
AI SystemsFeb 2026

Multi-Cloud Without the Chaos

Building a single pipeline abstraction across AWS, GCP, and Azure, and why the queue lives in Postgres.

8 min read →
InfrastructureJan 2026

What I Learned Shipping to Researchers

Clinical and academic users break your assumptions. Notes on the UCSF × Stanford deployment.

4 min read →
AI SystemsWeek 2

Your Agent Has Amnesia. Here's the Dict That Fakes Memory.

LLMs are stateless and frozen. Short-term memory is just context-window management: what you keep, what you summarize, what you drop.

Coming soon
InfrastructureWeek 3

The Gap Between a Notebook Agent and a Production One.

My notebooks ran on mock dictionaries. Here is what every mocked piece becomes in a real system: retries, timeouts, persisted state, observability.

Coming soon
RetrievalDrafting

Five Ways to Chunk a Document, and When Each One Bites You.

Fixed, semantic, recursive, structure-based, LLM-based. Recursive is the sane default, but the failure modes are where the real decisions live.

Coming soon