Coding Agents Don't Scale Themselves. Neither Do Your Teams. — Patrick Debois, Tessl
Patrick Debois compares today's challenges with AI agents to the resistance against continuous delivery in 2009 — the technology works, but the organization isn't ready.
His point is that what makes the difference is not the agent itself or the prompts, but how the team, platform, and work processes change around it. Instead of fixing the agent's code, you should improve the system as a whole. It's about reducing the number of times a human needs to touch a task, and making improvements that benefit the entire team, not just one person.
Vibekollen prepared this summary with AI from the original publication. The content belongs to AI Engineer.
More from AI Engineer
Inside Arca's Long-Horizon Agents That Run the Business - Aman Singh, Arca
AI Engineer 23 Oct
Real AI Agent Attacks and What Would Have Stopped Them — Andrey Rybka, Bloomberg
AI Engineer 23 Oct
Outside of tech there has been no financial payoff to US companies for using AI, now viewed as a margin-hurting cost center, as VC-backed firms burn more tokens
Techmeme 4 h ago
Source: Replit recently moved most AI spend from Anthropic to OpenAI, which gave 30%+ off in a deal worth $100M+/year, after Anthropic discontinued its discount
Techmeme 6 h ago