01
Start with a workflow, not a model
A useful AI project begins with a decision, an owner and a repeatable piece of work.
By Alex Vale↗
TOKENMONSTER INSIGHTS
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Gathering useful ideas for your next workflow.
TOKENMONSTER INSIGHTS
Big ideas.
Working AI.
We turn complicated data and everyday workflows into useful AI systems. Explore field notes on strategy, analytics, agents and the work of getting them into production.
From a promising experimentto a system people can use.
STRATEGY · DATA · APPLIED AI · DELIVERY01 / FIELD NOTES
A practical point of view
Intelligence matters when people can use it. We connect data foundations, analytics and application engineering—with permissions, evaluation and a clear handoff built in.
How we thinkNOTES FROM THE WORK
Useful thinking,
made readable.
Practical ideas for choosing the right problem, making data useful and getting AI into the hands of a team.
02
What to measure before you launch an agent
Separate task success, mistakes, time and cost before you build a leaderboard.
By Alex Vale↗
03
Give agents a clear stopping point
Completion should be observable, and retries should have limits.
By Noor Stone↗
04
Design the review step
Human review needs an interface and a decision, not just a checkbox.
By Alex Vale↗
FROM IDEA TO IN PRACTICE
Useful AI is a team sport.
01
Find the right problem
Choose a workflow with an owner and a measurable first release.
02
Make data usable
Connect information, definitions and permissions behind useful answers.
03
Build useful intelligence
Put assistants and bounded agents against representative work.
04
Put it into practice
Test, deploy and hand off a service the team can own.