WTF Is the Context Layer? The Missing Infrastructure for Production Agents — Prukalpa Sankar
Source
AI Engineer
Author
AI Engineer
Date
Terms in this piece · Glossary
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
fine-tuning — Taking a trained model and training it a bit more on your own examples so it gets better at one specific job.
Why it matters
If your agents demo well but get abandoned in production, this breaks down the context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition →-layer architecture — versioned/testable context repos, simulation environments, and trace feedback loops — that gets agents past the demo stage where prompting and fine-tuningTaking a trained model and training it a bit more on your own examples so it gets better at one specific job.Full definition → fall short.
Key quotes
“the problem we solve is we say AI doesn't know your business, we fix that”
Prukalpa Sankar
“Intelligence has 1,000x'd in the last decade. Just in the last 6 months, we have 2x'd on that axis.”
Prukalpa Sankar
“building an agent was really easy. Took like 5 minutes. Uh but giving it the business context that it took to actually get it to be accurate took forever.”
Prukalpa Sankar
“We realized that context kind of needs to be managed like code.”
Prukalpa Sankar
“in a world where you and your competitor have access to the same models and the same intelligence, what differentiates a company?”
videoWhy AI Agents Need Million-Token Context — Thomas Wolf & Olive Song, MiniMax
videoYour company brain will leak secrets: how we stopped it for big banks — Tanmai Gopal, PromptQL
videoTethered: Our Agents Are Us — Shu Fang, Two Sigma
videoAgents' next frontier: agent-to-agent and network effects — Jean-Denis Greze, Town
