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AI Training and Enablement
We hand over systems. We also hand over the judgement to run them.
Our principle
Courses transfer knowledge. Judgement is built on real systems, with real data, next to people who have done it before.
Anyone can run a two-day course on prompting. What organizations lack is people who can look at an AI system in production and decide: is this output trustworthy, is this cost justified, is this failure the model or the data, should this decision class be automated at all. That is judgement, not knowledge, and it is built by working on real systems with people who have done it. Our enablement programs are run by the same engineers who build our clients' systems, on the clients' own systems, with the clients' own data.
Tracks
Engineering track.
For developers and architects. Building, evaluating, deploying, and operating LLM and agent systems. Retrieval design. Cost engineering. Observability for AI components. Four to eight weeks, embedded.
Operations track.
For the people who will run the system daily. Reading decision logs, handling escalations, recognizing drift, when to pull the brake. One to two weeks.
Leadership track.
For executives and boards. What AI can and cannot decide, how governance works, what the real costs are, how to read a vendor's claims. Two sessions.
Rust track.
For teams inheriting a Rust codebase from us or planning their own migration. Ownership, borrowing, async, and the idioms that make Rust maintainable rather than merely compiling. Four weeks.
Format
Embedded, on your systems, with deliverables rather than certificates. By the end of an engineering track, your team has shipped a component to production under our review. By the end of the leadership track, your board has a one-page governance policy it wrote itself.