Your agents lack context: Here's how to fix "You're absolutely right!"

Official Schedule Context

Official Description

Every AI coding tool can generate code. Very few can generate the right code for your organization,

because they're missing context. They don't know why your team chose Redis over DynamoDB, what the

team decided in a Slack thread earlier today about the auth migration, or which architectural

patterns your principal engineers actually enforce in review. This talk is a practitioner's guide

to building a context engine: the reasoning layer that continuously ingests & synthesizes

organizational knowledge across disparate sources into unified, queryable understanding. I'll walk

through the problems you actually have to solve — reasoning across systems that don't agree with

each other, searching globally before you can reason, maintaining identity-scoped permissions so

every user and agent only sees what they should, and personalizing results based on who's asking and

what they're working on. These are the engineering challenges that make naive RAG fall short, drawn

from real lessons building this at scale.

Related YouTube Video

Stop babysitting your agents... — Brandon Waselnuk, Unblocked (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

Transcript Status

Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.

People

Notes

Supporting Slides

Slide Evidence