Workflows
How AI agents actually work
An AI agent is an LLM call, a list of tools, and a loop. A walkthrough of a working coding agent in a little over 200 lines of Python, no framework required.
Blog
Field notes
Guides and essays for people building AI systems, growing technical skills, and finding freelance work.
Engineering
How to set up LLM evals
A practical setup for LLM evals using raw events, unit tests, human review, LLM-as-a-judge, and A/B tests for production AI systems.
Workflows
How to build reliable AI agents
A field guide to reliable AI agents. Map the workflow first, use structured outputs for decisions, keep tool calling at the edges, and add recovery and human approval paths.
Data
How to prepare data for AI agents
Build an open-source pipeline that prepares documents, PDFs, and websites for AI agents, using Docling extraction, hybrid chunking, embeddings, and vector search in Python.
Data
How to implement hybrid search with PostgreSQL
A full walkthrough of hybrid search with PostgreSQL, combining semantic search through pgvectorscale, keyword search through full-text search and ts_rank_cd, and Cohere reranking on top, all in one database.
Data
How to build RAG with PostgreSQL
Build RAG with PostgreSQL using pgvector and pgvectorscale, keeping relational data and embeddings in one database, with similarity search, structured output, and advanced filtering.
Career
How to find freelance data and AI projects
A six-step roadmap for finding freelance data and AI projects, covering how to write a simple business plan, build your LinkedIn presence, sell solutions instead of skills, and land clients through the channels that actually work.
Data
PostgreSQL as a vector database: a beginner's guide to pgvector
PostgreSQL works as a vector database with the pgvector extension. A side-by-side speed test against Pinecone, the tables LangChain creates for you, and how to host it for free on Supabase.