Big ideas. Working AI.
AI that works in the real world, not just the demo.
We turn complicated data and everyday workflows into useful AI systems. Explore practical field notes on strategy, analytics, agents and the work of getting them into production.
How we work
One accountable delivery team, from the first workflow map to the service your team operates.
- Strategy & scopeChoose a meaningful workflow and a measurable first release.
- Data & analyticsConnect the information, definitions and permissions behind a useful answer.
- Agents & applicationsBuild software that assists, explains and acts within clear boundaries.
- Delivery & adoptionTest the complete experience, deploy it and help the team own what comes next.
TokenMonster Insights
Practical writing on choosing, building and running useful AI.
4 articles matching your filters
Start with a workflow, not a model
A useful AI project begins with a decision, an owner and a repeatable piece of work.
What to measure before you launch an agent
Separate task success, mistakes, time and cost before you build a leaderboard.
Give agents a clear stopping point
Completion should be observable, and retries should have limits.
Design the review step
Human review needs an interface and a decision, not just a checkbox.