Waitlist open
Write a better harness by practicing.
AI engineering moved to the systems around the model. Same model for everyone. A real environment. A hidden eval. Improve the loop until the number goes up.
Leave your email. We will send a seat when the playground is up.
How it works
Read the trace. Change the loop.
- 01
Start from a weak loop
The starter is already in the editor, with traces that fail. You do not burn a run just to watch it lose. Read those, then change the loop.
- 02
Read a failing trace
System prompt, every tool call, every result, the grader verdict. This is how you debug a harness.
- 03
Edit and submit
Thirty hidden tasks. Same model. Pass is 85 percent. A careful loop lands higher, with tokens still in budget.
Get a seat when it opens.
One email. We send the link when the playground is up.
FAQ
Questions
What is a harness?
The software around the model: the loop, the tools, the context, retries, when to stop. Not the model.
Why pin the model?
If everyone picks a different model, you cannot tell who built the better loop. Same model, same environment, same hidden eval. The only variable is the harness.
What is a trace?
The full transcript of one task: system prompt, every message, every tool call and result, the final answer, the grader verdict. You debug from this, not from the score.
When do I get in?
When the eval environment is hosted. We will email you a seat.
Is it free?
Yes for the waitlist and the first problems. A cheap pinned model. Run is three tasks. Submit is capped so nobody burns the bill.