Deep Dives into AI Engineering
In-depth explorations of AI techniques, LLM internals, agent architectures, and the engineering patterns shaping modern AI-assisted development.
Loop Engineering: Designing Systems That Prompt Your Agents For You
From prompt engineering to loop engineering — how developers are shifting from crafting individual prompts to designing autonomous systems that find work, run agents, verify results, and persist state without human input at each step.
Building an AlphaEvolve Skill for Claude Code
Turn Claude Code from a one-shot code generator into an iterative optimizer. This post introduces alphaevolve-skill — an open-source skill that brings evolutionary optimization to your coding workflow.
AlphaEvolve: Why One LLM Call Isn't Enough
A single LLM call generates plausible code — AlphaEvolve wraps LLMs in an evolutionary loop with automated evaluators to discover optimal code. Understanding this distinction unlocks a new mental model for AI-driven optimization.
Graphify: Turn Your Codebase into a Knowledge Graph
An introduction to Graphify — a tool that maps your entire project (code, docs, images, videos) into a persistent knowledge graph you can query instead of grepping through files.
Why Public LLM Benchmarks Are Misleading
Public benchmark scores are a poor proxy for real-world model quality. This post covers data contamination, benchmark overfitting, and how to actually evaluate models for production.
Claude Code: Architecture Deep Dive
A deep dive into the architecture of Claude Code — Anthropic's agentic coding tool that can read your files, run commands, and make edits across your entire project.
More notes on the way
New deep dives are in progress. Stay tuned.