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Blog
Field notes and method on AI transformation for SMEs, mid-caps and professional firms: AI agents, .NET integration, process automation.
28 July 2026
RAG on an existing .NET estate: three decisions that change everything
Wiring a RAG pipeline into an existing .NET application estate is not primarily a model choice. It is a question of vector storage, document chunking, and orchestration that respects what already exists.
27 July 2026
The 30-Day AI Diagnostic: why I packaged my offer into three fixed deliverables
A fixed-scope package with three written deliverables, not an audit that stops at a report: why a packaged AI consulting offer gets decided faster than an open-ended conversation.
22 July 2026
Hiring a .NET developer and a data scientist at the same time: one need, not two
A company that hires a .NET developer and a data scientist at the same time is sending a clear signal: it does not yet know it is looking for a single person.
15 July 2026
AI proposes, deterministic logic disposes: the pattern that keeps AI production-ready
AI in production is not AI that decides on its own. It is AI that proposes, to a system that has the right to say no. The three-layer architecture pattern behind it.
10 July 2026
Your problem is not (yet) an AI problem
"We want AI on our technical documentation. Where is your documentation? In binders." The data foundation comes before AI, and that is good news.
8 July 2026
Concierge first, code second: why I spent weeks automating nothing
Before writing the first line of my prospecting agent, I did the work by hand, for a long time. That step, not the code, is what actually makes the difference.
7 July 2026
"It's expensive": a category problem, not a pricing problem
An AI tool is an expense. An AI transformation is an investment. Confusing the two lenses explains most of the "it's too expensive" reactions heard at SMEs.
2 July 2026
The 2025 METR study: developers thought they were 20% faster, they were 19% slower
A controlled trial with experienced developers reveals a striking gap between perception and measurement. AI's gain is neither automatic nor free: it has to be measured.
1 July 2026
Garry Tan's AI software factory: the lesson is not in the tools
Y Combinator's president published his method to "ship like a team of twenty." The real lesson is not in the 30 tools he shares, but in the process they run on top of.
24 June 2026
"We already have Copilot, why would we need you?": the question worth answering
The number-one objection from leaders running on Microsoft. Three things a Copilot license does not buy you, and the real question to ask before answering it.
19 June 2026
I built an AI agent for my own prospecting: here is where it gets it wrong
An n8n agent sourced, enriched and scored my prospects every morning. What it taught me best was one concrete case where a confident AI can be completely wrong.
17 June 2026
Zero human validation, and that is the right call: the Convention Online AI chain
One pipeline requires human validation at every step. Another one runs all night with nobody watching. How to decide where to set the dial, based on the real business stakes.
11 June 2026
A document AI pipeline in production: what actually keeps it running
Hundreds of scanned timesheets, keyed in by hand, with no systematic check. Here is the AI pipeline I designed for an industrial group, and what actually matters in production.
8 June 2026
Why I chose Semantic Kernel over Python for AI in .NET
Certified on Microsoft AZ-2005, I chose to integrate AI into existing .NET systems rather than rewrite everything in Python. The reasoning, and the Semantic Kernel pattern.