Omar Khattab#720
This is the DSPy way.
Prompts are imperfect instructions, always.
Write them yourself as little as possible, but hold them accountable with typing, tests, metrics, and optimizers.
Using agents effectively requires embracing their stochastic nature and setting up a framework for them to reason rather than giving them a pile of rules.
Harness engineering and knowledge base curation does not (and cannot!) rely on all information being pulled into context—and given things like autocompaction over long horizon work, context is constantly getting blitted so you can't really rely on things being in context either.
In general you want to tell agents your expectations on how/when/what type of context they should seek and how the tools in their environment can help them complete their work.
You need to tell the agents what they are working on, what parts of it matter, and how they should approach tasks. Tell them about common tasks for the things you’re working on and where they can learn more about them. Make your agents collapse a prompt they are given into a paved workflow.
