Shipping AI agents that actually work in production
Most agentic demos fall apart the moment a real user touches them. Here's the eval-driven loop we run at Ulties to keep ours honest.
Agent demos look magical because the demo path is hand-tuned. Production is the opposite — users do strange things, latency spikes, models drift, and tools fail. Without a brutal evaluation loop, you ship a parlor trick.
At Ulties, we treat agents like distributed systems. Every agent step is observable, replayable, and graded by a deterministic + LLM-judge hybrid. We run regression suites every commit and refuse to ship if the suite drops more than 1.5%.
The shortest version: define what good looks like before you write a single prompt. Build a golden set of 200–1,000 historical cases. Score every change against it. Stop tuning prompts in the dark.
If you do this for two weeks, your agent will go from 'cool demo' to something users actually rely on. If you don't, you'll be patching prompts at 3am for the next year.