Who this is for: founders, product owners, and engineers building AI features/agents in real products.
What I help with: I pressure-test your agent approach (RAG, tools, routing, memory, integrations, model choice) and help you pick a direction that works under latency, cost, reliability, and observability constraints, not just in demos.
You’ll leave with: a clear decision and either a next-step plan (what to build first) or a rubric (how to evaluate options), depending on your situation.
Common traps I help you avoid:
- chasing the newest frameworks/tools that may not survive 3–6 months
- building “agent complexity” before you have evals/metrics
- shipping without guardrails/monitoring and then bleeding cost or reliability
- over-engineering early when simpler patterns would scale
Example questions:
“Which model should we use for this task, and how do we choose systematically?”
“What should be tool calls vs retrieval vs structured data lookup?”
“How should we design routing (single agent vs multi-agent vs workflow)?”
“What memory strategy makes sense here, and what’s a trap?”
“What evals/metrics should we set up so we know it’s improving?”
“Which parts should be built in-house vs using an existing framework/vendor?”
“What’s the simplest architecture that will still scale and stay reliable?”
