Architecture and boundaries
Assess data, integrations, model behavior, security constraints, and the parts of the system that deserve deterministic engineering.
Product and delivery choices
Turn an AI opportunity into a sequence of decisions a small team can validate, build, operate, and own.
Engineering leadership
Bring practical product-engineering judgment to an existing team, a constrained project, or a high-leverage technical decision.
Advice tied to implementation
Our consulting is grounded in the reality that an AI feature still has users, software dependencies, costs, failure modes, and a team responsible for it after launch. We help make tradeoffs explicit, then can work with the team to carry them into delivery. That includes reviewing a team's coding-agent setup, tool choices such as MCP servers, and evaluation approach.