EVERYDAY WORK, WITH LESS BACK-AND-FORTH
Less managing.
More getting things done.
Follow a request from the first words to the next clear step. Explore the examples, try the controls, and see what we’ve actually tested.
Follow-through
A finished step should lead to a finished task.
Tamias keeps track of what remains, continues checks it can do, and explains a genuine dependency when it reaches one.
What you ask
“Remove the duplicate actions in this screen and check that each one still works.”
The friction to remove
A change is made, but the remaining checks get handed back to you.
A clear path forward
- Inspect the screen and its actions
- Make the smallest change
- Verify the affected behavior
- Report what passed and what remains
What we verified
Scripted workflow regression: independent checks continue and an unsupported blocker is reviewed once. The demo below is illustrative.
What this doesn’t prove
This example has not yet been evaluated with a real model. It does not demonstrate autonomous completion of an arbitrary coding task.
Interactive example · nothing here changes a real account.
Tamias
Uses Tamias’s actual web components with fictional content. These controls demonstrate the interface; they do not call AI or send messages.
SHOW THE WORK
Small tests.
Honest results.
On October 26, 2026, we ran the to-do correction and latest-video examples once each with openai/gpt-4.1-mini. Both finished without a follow-up from the user. The provider reported $0.009325 total, within a $0.20 cap.
The AI chose its own tools using Tamias’s real prompt, tool loop and permission checks. Account records and web responses were synthetic. This tests decision-making in a controlled setting, not production reliability.
Evaluation notes
Original video assertion falsely treated the question mark in the watch URL as a user question. Saved evidence revalidated offline after excluding URLs; no additional model calls, retries or user nudges.
Five model requests across two examples. No production data was changed. The other three examples have scripted checks only. One successful run is evidence of a path working, not a success-rate estimate.