Coding Agents Don't Scale Themselves. Neither Do Your Teams.The Rise of Agent Enablement.

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Every company wants to know how others are actually scaling AI coding. But it's hard to get past the

generic transformation stories. What are the new practices showing up in real engineering orgs? What

does maturity actually look like, and what separates teams that are moving from teams that are

stuck? What are the patterns for enabling humans and agents, together? Patrick Debois has been

collecting the practices and patterns, talking to the early Agent Enablement teams already on the

job, team leads, and VPs of Engineering. What's showing up is a new function: a team that enables

other teams to get real leverage out of their agents. This talk takes the [Context Development

Lifecycle](https://tessl.io/blog/context-development-lifecycle-better-context-for-ai-coding-agents/)

off the individual laptop and onto the org chart, grouped across three pillars: - Enablement.

From individual experimentation to team and org-level fluency with agents. - Platform. Agent

tooling that runs like a real delivery pipeline: fast, observable, cost-aware. - Governance. Ad-

hoc guardrails growing into real evaluation, telemetry, and accountable agent work. For Agent

Enablement leaders scaling it out across the org. For team leads looking to help their teams get

better at this. For VPs ready to unblock the friction and unlock what agents can actually do.

Coding agents don't scale themselves. This is the talk about who does

Related YouTube Video

Context Is the New Code — Patrick Debois, Tessl (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

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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.

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