Discussion on "Stop Writing Bigger Prompts. Start Designing Agent Skills."

Marek Skopowski · 2026-04-11T13:06:52.530Z

When an AI coding agent does something wrong, the natural reaction is to add more instructions. Another rule. Another example. Another edge case paragraph. The prompt grows from a few hundred tokens t

This really clicked for me. It kind of reminds me of how backend systems moved away from one big service into smaller pieces that each do one thing well. Also the idea that context is something you have to manage instead of just keep adding to it… that changes how you approach the whole thing. Feels like the hard part isn’t prompting anymore, but how you structure everything around it.

Yeah, the BE architecture parallel is intentional - single responsibility, bounded contexts, loose coupling. These are solved problems, they just apply to a new domain now.

Totally agree on structure vs prompting, a well-written prompt gets you pretty far, but the real difference comes from how you organize everything around it.

Cheers!

Yeah exactly, that’s the part that feels underexplored right now.

In backend systems we eventually learned that clean structure isn’t enough, you also need visibility into how things actually execute across boundaries.

I’m starting to see the same pattern here, where things look clean at the “design” level, but once execution spans multiple steps or tools, it becomes much harder to reason about what actually happened.

Feels like the next challenge is less about structuring components, and more about making the execution path observable.

This resonates deeply. We hit the same wall building automation workflows — a single monolithic prompt trying to handle every edge case becomes brittle fast. The shift to composable skills is essentially the same principle as microservices vs monoliths, but for LLM orchestration. One pattern that's worked well: treating each skill as a self-contained unit with its own context window budget, clear input/output contracts, and fallback behavior. Instead of one 8k-token mega-prompt, you get five 1k-token focused skills that the orchestrator chains based on intent classification. The debugging story also improves dramatically — when something breaks, you know exactly which skill misfired instead of hunting through a wall of instructions.

Spot on with the context window budget per skill - that's sth I should've called out explicitly. It forces you to be disciplined abt what goes into each skill. If it doesn't fit in ~1k tkns, it's probably trying to cover too mych. The I/O contracts points is interesting too. I've found that the clearer tjhe trigger conditions and expected outputs are, tjhe less the orchestrator has to think. I'm interested in your fallback behavior, it goes to a more general skill or retries with a different context?

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Stop Writing Bigger Prompts. Start Designing Agent Skills.

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