Blog
Practical essays and guides for developers, on AI engineering, agentic coding, and freelance work.
A working framework for the five levels of AI agent complexity, from augmented LLM calls and DAG workflows to agent harnesses and multi-agent orchestration, and how to pick the simplest level that solves the problem.
Practical human-in-the-loop for AI agents, covering two ways to halt a process in your Python backend, plus the SSE streaming and async production patterns that save state and resume after approval.
Context engineering for AI agents in practice, covering why bad context, not the model, causes most production failures, and how to fix system prompts, tools, and message history.
How to build production AI systems with APIs, retrieval, agents, evals, deployment, monitoring, and human review around the model.
A three-phase roadmap to learn Python for AI in 2026, covering professional setup, the language core, and your first model API calls, plus how to use ChatGPT and Claude as a tutor instead of a copy machine.
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.
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.
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.
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.
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.
Build RAG with PostgreSQL using pgvector and pgvectorscale, keeping relational data and embeddings in one database, with similarity search, structured output, and advanced filtering.
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.
