@yibie: # No Coding Before 10am A startup I work with just threw out their entire playbook. They've been moving fast, but over the past month, their way of working completely collapsed because of Claude Code and Codex. So they held a war room meeting and rebuilt how to operate from scratch. He…
Summary
A startup rebuilds its engineering playbook around AI coding agents, adopting rules like no coding before 10am and treating agents as the primary user, signaling a fundamental shift in how engineering teams operate.
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Cached at: 06/17/26, 01:42 AM
No Coding Before 10am
A startup I work with just scrapped their entire playbook. They’ve been moving fast, but in the past month, their way of working completely broke due to Claude Code and Codex. So they called a war room meeting and rebuilt how they operate from scratch.
Their first new rule: No coding before 10am.
For the past twenty years, engineering culture has been about maximizing time spent writing code. Kill meetings. Block calendars. Stop anything that pulls an engineer away from the keyboard. This team is doing the exact opposite. Every morning, engineers now pair prompt: they sit together, draft prompts, define objectives, and set the agents up to succeed. Only after that do the agents start working.
Their playbook isn’t “use AI to write code faster.” It’s a full inversion. Agents, not engineers, are now the ones doing the work. Engineers ensure agents can do the work well. Over the past decade, I’ve seen dozens of teams operate—from DoorDash to my own startup. What they came up with is the clearest version I’ve seen of how engineering actually works now. I asked if I could share it. Here’s their playbook.
Agents Are the Primary User
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Design for agents, not for humans. Every system, data store, naming convention, and knowledge artifact should be designed with an AI agent as the primary consumer. Humans interact with systems through agents whenever possible.
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Code is context, not a library. Agents read code to understand what it does and then generate their own version. Don’t optimize for “code reuse across people.” Optimize for “code comprehensibility by agents.” Code itself is documentation.
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Data is the real interface. The right interface between two components is a well-structured data artifact, not a function call. Clean data lets agents compose systems on their own, without being told how.
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Maximize agent utilization. If the team is commuting and nothing is running, that’s waste. Agents should work overnight, during commutes, in meetings, asynchronously. The most expensive thing in the system is agent/compute sitting idle waiting for a human.
How We Spec and Build
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Objective and constraints come first. Before building anything: write the objective in one sentence, list the constraints, and define success criteria. If you can’t state the objective in one sentence, you don’t understand the problem well enough to build it.
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Spec the outcome, not the process. AI figures out the process. You judge the output against the objective function. This replaces traditional PRDs. Write objective functions, not implementation plans.
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Define rules, not structure. Don’t over-specify schemas and formats. Set naming conventions, metadata requirements, and versioning rules. Let agents figure out the rest.
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Review the output, not the code. Don’t read every line an agent writes. Test the code against the objective. If it passes, ship it. If it doesn’t, reset the objectives and constraints. Code review, as we once knew it, is overhead this system no longer needs.
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When you build a new way, kill the old way. No parallel implementations. Old code paths get removed immediately. The codebase is agent context. Every dead path is noise that degrades agent performance.
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Think in systems. If you do something manually more than twice, automate it. If a human is still repeating a task, the system isn’t set up right. Goal: set things up, let them run, check the output, move on.
Working Together
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No coding before 10am. Hands off keyboards. The first one or two hours every morning are for talking, aligning, and drafting prompts together. Once the team agrees on what to build and how to set agents up, then you can start coding and let agents work.
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Optimize for time, not tokens. If spending 10x the tokens saves a day, spend them. The bottleneck is human decision time, not compute cost.
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Individual autonomy, shared interfaces. Everyone uses their own IDE, prompting style, and workflow. What gets standardized: data schemas, objective specs, component responsibilities. Everything else is personal choice.
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Call out anti-patterns immediately. When you catch yourself or others falling back into old habits—designing for humans instead of agents, accumulating dead code, skipping specs—flag it right away. Old habits compound very quickly.
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Assume everything changes in three months. Technology is changing month by month. Every decision you make today will soon be wrong. Build modular. Minimize lock-in at every level.
Six months from now, there will be two kinds of engineering teams: those that rebuilt how they work from first principles, and those still trying to fit agents into their old playbook. The latter will be far outpaced by teams half their size.
If you run an engineering team and haven’t had your own version of this war room, go have it. Throw out the old playbook. Write a new one.
Original: Michael Bloch, No Coding Before 10am, Feb 2026 https://michaelxbloch.substack.com/p/no-coding-before-10am…
#AI工程 #Agent #软件工程 #工作方式
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