ContextOps
The discipline enterprise AI has been missing.
For two years, enterprise AI teams have been chasing the same fix. Better prompts. Bigger context windows. Smarter models. The agents keep failing in the same ways.
Nobody's asking the harder question: who owns the knowledge those agents run on?
ContextOps is a discipline and a podcast built around that question. First-principles thinking about how enterprises assemble, govern, and audit the context that powers their agents, not inference speed or benchmark chasing.
The gap has a name now. The work begins.
The Show
A fortnightly conversation hosted by Vivek Khandelwal and Dilip Ittyera, occasionally joined by practitioners, researchers, and operators thinking seriously about this problem. No panels, no slide decks, no "AI is transforming everything" takes. Just the discipline, built episode by episode.
Every generation gets its ops function.
DevOps, DataOps, MLOps. Each promoted a function from afterthought to infrastructure. ContextOps is next. The gap is named. The discipline is forming.
Why AI keeps failing the same way
One person wrote the prompts. Someone else sourced the documents. A third team loaded them into the pipeline. The developer building the agent assumed the context was clean. Nobody checked. When the agent failed, everyone blamed the model.
Assembled by many hands. Owned by none.
What ContextOps actually is
ContextOps operationalizes knowledge for AI. It's the loop that turns documents, SOPs, and policies into something an agent can reason over: reliably, traceably, and without contradiction. Ingest. Validate. Structure. Serve. Audit. Refine. Knowledge flows in. Feedback flows back.
ContextOps operationalizes knowledge for AI.
Vivek Khandelwal
Two years watching enterprises blame the model. Built a company around the actual problem.
Dilip Ittyera
Symbolic AI practitioner. Has been building governed knowledge systems before the industry had a name for it.
The discipline is forming.
Be among the first to follow it.