Notes on building
SaaS & AI products
Practical writing on RAG, natural-language data, choosing models and shipping AI to production — from the team that builds these systems for a living.
Loop engineering: stop prompting your AI, start designing the loop
In mid-2026 one idea reorganised how people work with AI: stop prompting your agent by hand, and design the loop that prompts it for you. Here is what loop engineering is — and how to build a loop that converges instead of spinning.
Read article →The agent harness: why the model is the smallest part of an AI agent
Swap the model in a working agent and little changes; swap the harness and everything does. Here is what an agent harness really is, the loop at its core, and why it decides whether an agent works.
Read article →From prototype to production: shipping a reliable AI feature
Every AI demo works on stage. The gap to production is evals, guardrails, observability and graceful failure — the unglamorous work that makes a feature trustworthy.
Read article →Choosing the right LLM for your product: a practical guide
The biggest model is rarely the right default. Picking by task, latency, cost and data-privacy usually lands you on a mix of models — each doing what it is best at.
Read article →Building an AI knowledge assistant your support team will actually use
Support teams answer the same questions endlessly. A knowledge assistant over your own docs can handle the repetition — but only if it cites sources and knows when to stay quiet.
Read article →Ask your database in plain English: how natural-language-to-SQL works
Most people who need answers from a database can’t write SQL. A natural-language layer turns "how many orders shipped late last month?" into a query, runs it safely, and hands back the answer.
Read article →What is RAG, and why your business data belongs in your AI
An LLM on its own only knows what it was trained on. RAG gives it your documents, your policies, your data — so the answers are grounded in what is actually true for your business.
Read article →Have an AI project in mind?
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