AI Agent Development

Designing and shipping agents that go beyond a chat box. I define the job, the tools, the guardrails, and the handoff so the agent can actually finish work — research, support, operations, or product workflows — without becoming a black box.

Each agent is scoped around a clear outcome: what it can do, what it must ask a human, and how it reports back. That keeps the system useful in production instead of impressive in a demo.

Connecting agents to the systems you already use — APIs, databases, CRMs, calendars, internal tools — so they can take actions, not just generate text. Structured tool calling, retries, and audit logs are part of the build, not an afterthought.

I map the workflow first, then automate the steps that are repeatable and high-leverage. The goal is fewer manual loops, not a chatbot that still needs you to do the work.

Giving agents reliable memory of your documents, codebase, and business data with retrieval-augmented generation. That includes chunking strategy, embeddings, vector search, and citation so answers stay grounded in your source of truth.

I tune retrieval for precision over noise — the difference between an agent that sounds confident and one that is actually correct.

Embedding agents into web and mobile products with the same care as any other backend feature: authentication, rate limits, streaming responses, evaluation, and cost control. Built with LLM APIs, LangChain-style tooling, and the MERN stack when the product lives there.

From a first working agent to something your team can monitor and iterate on, I leave you with a system you can maintain — not a one-off prompt buried in a notebook.