Coding Agents Dont Scale Themselves. Neither Do Your Teams. — Patrick Debois, Tessl @aiDotEngineer
Coding Agents Dont Scale Themselves. Neither Do Your Teams. — Patrick Debois, Tessl  @aiDotEngineer
Uploaded August 2026 | Updated September 2026, 3 weeks ago
In 2009 people told Patrick Debois that continuous delivery was crazy. He hears the same thing now about the dark factory, and reads it the same way: not that the technology cannot work, but that the organization is not set up for it yet. His starting assumption is that harnesses and loops will commoditize, possibly into a service a frontier lab just sells you, so none of that will be anyone's differentiator. What actually changes is the team, the platform and the organization around them.

Developers pushed back on the conductor framing, telling him they did not sign up to write better prompts. What brought them back was tooling. Once the team started building harnesses for the agent, a genuinely technical path reopened, and the loudest skeptics turned out to be the right people to hand context authoring to, precisely because they were angry about the output. The shift he pushes is to stop fixing the code the agent produced and improve the system instead. Retros stop being about the code and become about where the agent hit the same wall repeatedly. Planning splits into work scoped tightly enough to hand off and work that still needs a conversation. He tracks two numbers: how many human touches it takes to get the right result, which should fall, and how much of each fix is shared, because one improvement to a common harness lands for everybody rather than making a single person 10x. Above the team it is paved roads and a named owner, not a thousand flowers blooming.

Speaker info:
- https://x.com/patrickdebois
- linkedin.com/in/patrickdebois
- jedi.be

Timestamps:
0:00 - It will not work here, and what that signals
2:46 - Developers who did not sign up for prompting
5:20 - Stop fixing the code, improve the system
7:04 - Retros, planning, and the downstream squeeze
9:38 - Two metrics: human touches and reuse
10:29 - The platform team's new problems
12:12 - Sprawl, paved roads, and making spend visible
14:43 - Enabling the organization without a champions program
15:36 - Hiring when the job titles mean nothing
18:07 - Optimize the spend instead of capping it
20:38 - A dim factory, and knowledge as the moat
Coding Agents Dont Scale Themselves. Neither Do Your Teams. — Patrick Debois, TesslScaling up Continual Learning — Ronak Malde, TrajectoryAgents Need Feature Flags - Sachin GuptaUnlock Agent Autonomy: The Runtime for AI-Native Systems — Tushar Jain, DockerEmulated: The Data for Fully Autonomous Software Engineers and Companies — Joseph WangProductionizing LLM Gateways: Architecture, Tradeoffs and Hard Lessons — Kanish Manuja, Twilio
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Coding Agents Don't Scale Themselves. Neither Do Your Teams. — Patrick Debois, Tessl

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