strategyLATEST INSIGHT · 2 MIN READ
Start with a workflow, not a model
A useful AI project begins with a decision, an owner and a repeatable piece of work.
Alex Vale / Sep 22, 2026↗
TokenMonster
Loading…
TokenMonsterTokenMonsterLoading…
We turn complicated data and promising ideas into AI systems people can actually use.
Read the insights ↓Field notes from
problem to practice.
A useful AI project begins with a decision, an owner and a repeatable piece of work.
Reliable answers depend on definitions, freshness and permissions as much as the interface.
Separate task success, mistakes, time and cost before you build a leaderboard.
Assign responsibility before the pilot starts.
Make it possible to inspect the evidence behind an answer.
Completion should be observable, and retries should have limits.
When automation cannot finish, preserve the context for a person.
The interface and the backend must agree on who can do what.
Deployment, support and handoff turn an experiment into a service.
Keep inputs and evaluation consistent when choosing a model.
The interesting part starts after the demo. Explore what it takes to build AI with a purpose, a plan, and a person in mind.
Find your starting point ↗