How to stop babysitting your AI coding agents

If you are still saying yes to every prompt and steering every doom loop, your agents are missing context, not intelligence.

Brandon Waselnuk explains why teams end up babysitting their agents and how a context engine changes that, with a live terminal demo where an agent asks Unblocked instead of asking him, a walkthrough of free open source tools, and Q&A on architecture, permissions, memory, and measurement.

What you'll learn

• What the industry has actually measured. DX, METR, and Faros data on throughput, delivery speed, and review time in high AI adoption teams.
• Why you are still the babysitter. At every level but one on the maturity curve, you are still the context.
• What a context engine looks like in an agent session. Same prompt, same model, different context: citations, conflict detection, and the time and token savings that follow.
• Four free tools to build your own context layer. Social graph builder, repo rules agent, context engine simulator, and the beyond-RAG workshop.