Skip to content

Writing

We Gave the AI Better Documentation. It Got Slower.

We had 15 skill files documenting every Synthesis CLI command — syntax, options, example invocations, expected output. We wrote them carefully. We loaded them into the agent's context. We assumed the agent would use them.

Then we ran a benchmark.

The CLI condition was the worst-performing integration in the entire test. Worse than no integration at all.

AI Agents Without Knowledge Infrastructure Are Interns With Amnesia

I have been watching the AI agent space closely for the past year. The frameworks are impressive. The orchestration tools are clever. The models are increasingly capable. And yet, most agent deployments I see make the same quiet mistake: they treat the knowledge problem as solved.

It is not solved. It is barely addressed. And until it is, all the reasoning capability in the world will not make your agents reliably useful.

The Synthesis Excavation: Recovering 3.5 Years of Lost History

Title slide: The Synthesis Excavation — Recovering 3.5 Years of Lost History, achieving 99.96% knowledge coverage across 4,852 binary files

We build Synthesis — a knowledge indexing tool whose purpose is to make everything in a workspace searchable. We had been running it on our own workspace for months and the coverage number looked excellent: 99.6%. Nearly perfect.

That number was a vanity metric. It told us exactly what we wanted to hear while hiding what we needed to know. The real asset coverage was 15.2%.

Who Describes You to AI?

I spent part of today rebuilding this wiki. Not because it was broken. Because when I read it carefully, it was wrong.

Not dramatically wrong. Wrong in the way things get wrong when you stop paying attention. I was listed as Chairman of IASA Norway. I stepped down from that role in 2011 -- fifteen years ago. One of my companies had the wrong founding year. The framing throughout was from a different era: SOA, distributed systems, the vocabulary of a decade ago. The site looked like me. It described someone who used to be me.

I Wrote About Cloud Computing in 2009. Seventeen Years Later, I Have the Same Feeling.

In February 2009, I wrote a blog post called "Clouded Vision." The central argument was straightforward: "developers have fundamentally misunderstood how cloud computing delivers its benefits." They saw cheaper prices but never stopped to consider where the savings came from. They expected to move existing applications, full of what I called "enterprise DNA" -- static configuration, vertical clusters, high administration costs -- onto cloud platforms with minimal change. Then they complained when it proved difficult. I wrote nineteen posts about cloud computing that year. Most of them circled the same frustration: the industry was adopting a new technology while completely misunderstanding the structural shift it required.