5 Comments
User's avatar
Jake Redmond's avatar

There’s an organizational layer to this that I find really interesting. Turning repeated work into a skill doesn’t just reduce context or improve reliability. It decides which parts of judgment should stop being rediscovered each time and become repeatable infrastructure.

That makes skill design partly a question of what we choose to stabilize. Which behaviors should become consistent enough to reproduce, and which should remain inside the reasoning loop because the context still matters?

nihal | deeptech decoded's avatar

One the leanest pieces out there explaining so nicely. Thankyou for putting it together!! 🙋🏻‍♀️

Logan Thorneloe's avatar

Glad it’s helpful!

James Wang's avatar

Great suggestions here! Agreed with all of these and have discovered (sometimes through painful trial and error) that these steps are the right ones for skills—or just agent instructions in general.

Gianfranco Mileo's avatar

Context rot in long-running agent workflows is rarely a pure context-window limitation; it is an architectural state-management failure. Treating skills as modular, isolated execution boundaries rather than persistent prompt state is essential for preventing reasoning decay in production-scale eval loops.