The Highest-Signal
Technical AI Courses

We had argued for six months about why our RAG pipeline answered badly. After the eval module it turned out the problem was not chunking — it was that we had no reranking at all. Accuracy went up 31% in two weeks.

The "shrink the agent, grow the tool" framing saved our product. We cut 14 tools down to 4 and error rates dropped to a third.

Most courses stay at the surface. Here the very first lesson went straight into token budgets and latency math. That was exactly the level I was looking for.

I rolled the observability module out to my team as-is. We now see what a model swap breaks before it reaches production.

The fine-tuning workshop opened with a decision tree for "do you actually need this?". It saved us months of GPU spend.

I enrolled my whole team in the cohort. Two months later our first agent system is in production, approval flows included.

The streaming interface lesson paid for the course on its own. We halved perceived latency for our users.

After the MCP workshop we consolidated our internal tools behind a single server. Wiring up a new agent is a one-day job now.

Recordings stay available, so I came back three months later and rewatched the eval section from scratch. That access model is worth a lot.

The caching strategy from the cost-budget module cut our monthly bill by 44% without giving up any quality.

My favourite part is that every module ends with a working repo. You learn from code, not from slides.

A production problem I posted in the community channel turned into an extra lesson the same day. I have not seen that anywhere else.