Topic
Notes from our projects
Write-ups of how we built specific systems: the order we built them in, the decisions that held, and what we would tell a team starting today. Each one links to its case study.
All case studiesOctober 8, 2026 · 4 min read
Keeping AI agents honest: the server-side grounding pattern
An agent that puts real items, prices or actions in front of a user cannot be allowed to invent any of them. The pattern we built for MayAI makes that impossible by construction rather than by prompt. Here is how it works and where it applies.
October 8, 2026 · 3 min read
RAG for code and other structured material: why token-count chunking fails
Most retrieval systems split documents by token count, embed everything and hope. On code, contracts and catalogues that returns plausible fragments and misses the answer. What we built for DevGuardian AI instead, and how the same design applies beyond code.
October 8, 2026 · 4 min read
Multi-agent systems in .NET: what we learned building two of them
DevGuardian AI runs three role-based review agents; MayAI runs one agent with six tools. Both are built on Microsoft Agent Framework in .NET. Seven lessons about when to add agents, how to design tools, and what has to be in place before the first demo.
October 8, 2026 · 3 min read
From public data to market intelligence: how Valco AI was built
Dubai publishes its property market as open data, updated daily. It is public, and it is not ready to use. The pipeline, the data model, the forecasting models and the conversational layer we built for Valco Properties, and the order we built them in.
Working on one of these problems?
The patterns in these notes are the ones we use on client work. Tell us what you are building.
Book an AI consultation