Everyone sells the medallion architecture on the same promise: your Silver layer is cleaner than your Bronze. Deduplicated, conformed, typed, joined. That's true, and it's also not the payoff that matters. After building a governed memory store on Databricks — Delta for the raw tier, Postgres for
A few weeks ago I stopped trusting my own traffic graphs. The edge dashboard told me one story — steady visitors, healthy numbers, nothing alarming. So I built a second view that reads the origin's own access logs instead of the edge's summary, and the story fell
I set out to build a memory layer for my agents — somewhere they could write what they learned and read it back later without me hand-feeding context into every prompt. A few weeks in, I looked at the schema I'd drawn and laughed, because I'd reinvented
Most agent-authorization schemes I've seen ask the wrong question. They gate on confidence: is the model sure enough to act? Set a threshold, and if the score clears it, the agent does the thing. It feels rigorous. It's backwards. The axis that should decide whether an
I ran git shortlog -sne on my orchestrator repo last week, the way you do before writing a release note and wanting to thank the right people. I scrolled to the top expecting my own name. It wasn't there. The top committer is forgeai-dev. Second place goes to
I keep two completely different reflexes in my head for the same task, and last week they finally collided. The task is ordinary: an app needs a real database — proper transactions, low-latency reads and writes, not an analytics table playing dress-up. For years my hand went to the same place
I wrote recently about Azure Agent Mesh and OpenSharing — two infrastructure layers that between them cover how enterprises register, discover, share, and execute agents. Between them, they address a lot of the plumbing that has been missing from the enterprise agent stack. But there's a gap neither of
Unity AI Gateway, announced at DAIS this week, is the feature I've been waiting for since Agent Bricks shipped last year. It's a centralized governance layer for model access in Databricks — you configure which models are approved for use in your environment, who can call them,
The performance gap between open-weight models and closed frontier models has spent the last year collapsing faster than anyone predicted. Epoch AI's tracking puts open weights at roughly a three-to-four-month lag behind state-of-the-art closed models on average. For coding tasks, the gap has effectively closed — DeepSeek V3.2
The central message from DAIS this week, delivered by Ali Ghodsi in the opening keynote, was direct: AI doesn't have an intelligence problem, it has a context problem. If your CFO can't get an AI system to explain why margins changed, that's not a
Two and a half years in, with a production knowledge system, a working orchestration layer, local inference running alongside cloud providers, and prompt hygiene enforced at the infrastructure level — I want to be direct about something the AI industry is not particularly incentivized to say clearly: building this has been
Anthropic announced Claude Fable 5 and Claude Mythos 5 yesterday — the first models in the new Mythos-class tier that sits above Opus in the model family hierarchy. Fable 5 is the accessible tier of the Mythos class; Mythos 5 is the top of the stack. If you've been