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AI Engineer NYC 2026This is a full-day compilation from AI Engineer New York 2026, covering how financial and enterprise teams are putting agents into production. Speakers describe systems for policy-driven workflows, specialist models, agent swarms, verification, memory, MCP gateways, context optimization, and secure...
How to Actually Tokenmaxx and Save MillionsAlvin Pane presents token optimization as a measurement and release process. Teams should first trace model calls, retries, prompts, token counts, latency, and cost. They can then measure how often production disagrees with itself before judging a cheaper candidate. At...
I Spent Two Years Building the MedianHariprasad Sudharshan argues that AI changes how software is produced without changing what the world ultimately needs: reliable deterministic software. Models provide capability, while harnesses provide tools, context, orchestration, memory and workflows. Since these resources are increasingly rented by everyone,...
Coding agents look capable in a fresh repository and come unstuck in a ten-year-old one.
A production agent can give the right answer and still refund the same customer twice, act on a stale record or quietly finish half a job.
The chat box makes users package their work into prompts, wait, inspect the answer and try again.
More context can make an agent worse.
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