AI Orchestration
We train your team to run agentic AI development loops: planning work so it can be delegated, running delegated builds, automated browser QA, and validation gates that catch what the model got wrong before anyone else sees it.
- How to decompose work so an agent can be handed a real task rather than a prompt, and how to tell when it cannot
- Delegated build loops: fanning work out, keeping the pieces coherent, and merging them back without losing the thread
- Automated browser QA, so the thing that was built is checked by something other than the thing that built it
- Validation gates: the checks a change has to clear before it counts as done
- The judgment layer, which is knowing which of the above to skip
- Work arrives decomposed into tasks an agent can actually be handed, with the ones that cannot be delegated named as such
- Orchestrated agent loops with browser QA in them, so a build is checked by something other than the thing that built it
- Validation gates a change clears before it counts as done, written down rather than held in one person's head
- A team that can tell when the loop is the wrong tool and says so
We run our own company this way, including the site you are reading. The practice is what we teach, not a tool we resell.
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