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Getting great results from a coding agent is a craft: feed it the right context at each step, keep its working set small, plan before you build, prove the work with tests. That craft has a name, context engineering, and it’s most of what separates an agent that one-shots a feature from one that flails. You don’t have to learn it. Smithers bakes context engineering into the agent that drives it: say what “done” looks like, and it assembles the context, the plan, the gates, and the loops for you.

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Ask your agent for the rundown

Ask the agent that runs Smithers for you to explain what’s happening under the hood. Try:
“Give me a rundown of how you do context engineering with Smithers, and what you do when you write a Smithers script.”
It walks you through its own playbook in plain language, tied to your project.

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What the agent does when it writes a script

Hand off a real piece of work, and the agent does this for you:
  • Plans, then validates. Writes a plan with teeth (named tests, a clear definition of done) and puts the gates in before the code: checked, not hoped for.
  • Stays in the smart zone. Keeps each step’s context small and focused, research and planning done up front, so the model spends its attention on the work.
  • Tests end to end. Doesn’t call a feature finished until a real test proves it. Work is broken into vertical slices: scaffold the layers (frontend, API, database) first, then build each feature all the way through before starting the next, so every step has something real to test and a feature’s context stays in one window.
  • Delegates the ends and the middle. Strong models plan and review at the two ends; cheaper models handle the routine middle, quality where it matters without paying top rates for everything.
  • Guards the point of no return. Runs the safe, reversible steps first and isolates anything irreversible, like sending money, deploying, or emailing customers, behind an approval gate: the agent decides, you approve what happens.