Set-shifting Behavioral Test for Harnessed Agents
What happens to an LLM agent's tool choice when the reliable tool silently changes within an ongoing session? We borrow set-shifting from cognitive psychology to study how well agents adapt to hidden reliability shifts. Our benchmark mounts
https://arxiv.org/abs/2607.13396v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
Light
How close the company’s idea is to your thesis statement
Sector
agents, llm
Overlap with sectors you care about
Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↓ declining
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Correct facts used on the next screening or memo.
Activity & evidence
Similar baseline plays (YC · idea space)
Shreyas Kaps
Rohan Kulkarni
ReasonBlocks
· Active
The runtime layer that makes AI agents cheaper and more reliable
founders not scraped yet