Notes from the build.
Build notes on agentic engineering, edge inference, hackathons, and what I'm learning while taking AI systems from prototype to production.
A practical look at what agentic workflows change: smaller briefs, clearer evals, parallel work streams, sharper review, and faster technical learning loops.
Eight AI builds in one quarter turned agentic engineering from a productivity idea into a problem-solving method: smaller briefs, stronger evals, faster prototypes, and sharper technical judgment.
Studio Copilot won the Raw to Curated track at NVIDIA GTC's Hack to Create. The product is simple: a local AI workspace for photographers that handles culling, contracts, and client review without ever uploading a file. Here's why edge AI for creative professionals is genuinely the right architecture.
At the Nebius hackathon the day before NVIDIA GTC, I worked on Sideline: one Cosmos Reason 2 loop controlling three simulated bodies. Same brain, three environments. Here's what worked, what didn't, and what simulation teaches about physical AI.
I put NVIDIA's Cosmos Reason 2 on a Jetson and pointed it at amateur tennis. The model does more than see frames. It reasons about ball trajectory, line calls, and the physics of a moment. Here's what that buys, and where it falls down.
Two MacBook Pros, two operating systems, three flash tools, an OTA upgrade that bricked the bootloader, raw PyUSB debugging, and one kernel parameter change to flash an NVIDIA Jetson AGX Orin 64GB. Over 20 attempts across two days. Everything that went wrong and the one-line fix that finally worked.
Most AI side-projects don't make it past stage two. Here's the funnel I now run every product through: what each stage is for, what kills you between them, and the gate that lets you move forward.
What changes when the same product runs on a $2,000 box under your desk instead of a per-token API. Latency, cost curves, what breaks, and the LiteLLM-as-router pattern that lets you flip between local and cloud without rewriting agent code.
One weekend, one Jetson, 2.3 million Austin construction permits, and a Nemotron Nano 8B running locally. The technical problem-solving behind the DGX AITX win.