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quinnovator/README.md

Hi, I'm Jack 👋

I'm the engineer customers talk to: I learn what they need, build it, and stay until it runs in production. Mostly that means AI agents, evals that judge them, and the infrastructure underneath.

Now

  • Founding Engineer at D2 Labs. Sole engineer on two ed-tech platforms that deploy LLM agents in the public sector. MyVoice is used by ~20,000 educators across six states. Students First took North Dakota's statewide school system from kickoff to go-live in about a month.

Before

  • Co-founder & CTO, New Memories. Built a multi-agent platform on GCP, plus a system that monitors ~100k physical locations across New York using small tuned models on self-hosted GPUs.
  • Capital One, Associate → Lead. Worked on the control plane of the enterprise ML platform (scheduling, distributed training, serving) for a few thousand data scientists.

Things I reach for: Python · Go · TypeScript · Rust · Swift · Kubernetes · Terraform · AWS · GCP · PyTorch · MCP

Things I think about: agent evals and guardrails · context engineering · inference cost and latency · making AI systems a customer can actually trust

→ jq.codes · LinkedIn

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  1. inhouse inhouse Public

    Your own app platform on one box, with your tailnet as the front door

    Go 40

  2. contactd contactd Public

    One Go binary that lets a client talk to an AI contact the way it would talk to a person: JIT threads, JIT prompt cache, JIT REPL environments over one append-only log.

    Go 27