Practical perspectives from the work — on agents, evaluation, on-prem deployment, and turning models into products.
Why the leap from chatbots to tool-using agents changes everything about how you design, evaluate, and trust an AI system.
Lessons from building a coding agent with zero data egress — architecture, model choices, and the compliance conversation.
If you can't measure an agent's output, you can't ship it. A practical framework for scoring, guardrails, and observability.
How an end-to-end research platform turns scattered notebooks into reproducible, AI-assisted signal discovery.
Automating patent drafting and prior-art search without losing the traceability and control attorneys require.
Designing a playful, guardrailed learning platform that parents and educators actually trust.
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