Tim Tremblay

I help teams and SMBs get unstuck with AI — from "where do we start?" to agent workflows and local models the team runs itself.

Most small teams are stuck at the same point: a few people pasting into ChatGPT, no shared practice, no idea if AI could do more — or do it cheaper and privately. I've spent 20 years leading enterprise engineering teams through exactly this curve, from first IDE tooling to custom, locally-hosted LLM systems. Before that enterprise chapter, I ran my own consulting practice for 16 years — one system I built for a client in 2008 is still in production today.

Four fixed-scope ways in, depending on where you're stuck:

- Getting started — your first AI workflow, working and measured, in two weeks

- Next level — from pasting into chat windows to agents doing the work (IDE + CLI tooling, shared agent workflows)

- BI & documentation — ask your data questions in plain language

- Open & local models — private AI on hardware you already own, benchmarked against your API spend

Every engagement is fixed-scope with a named deliverable, and ends with your team running the practice — not renting mine.

Deep domain: telecom infrastructure (voice, SMS, fax, carrier data) — 12 years on the same high-volume platform. Stack: Claude Code, Cursor, OpenCode, LangGraph, Ollama, vLLM, Apple MLX, Presidio.

More: tremcom.io