BentoLabs AI (YC P26)

The monitoring and learning layer for long-running agents

[BentoLabs AI (YC P26) @BentoLabsAI]

We are live on @ycombinator !

Building the monitoring and learning layer for long-running agents.

[Y Combinator @ycombinator]

.@BentoLabsAI is the monitoring and learning layer for long-running agents. Their learning layer gives agents model-jump gains: Sonnet 4.5 went 42.2%→52.4% on TB2 (Internal).

Congrats on the launch, @Abhinavv_soni & @kacppian!

https://t.co/LTy5sslfni

[BentoLabs AI (YC P26) @BentoLabsAI]

Does your agent actually learn from its failures, or just log them?

[BentoLabs AI (YC P26) @BentoLabsAI]

@Rahul_J_Mathur Thank you @Rahul_J_Mathur🙌🏻, glad Bento made this list.

[BentoLabs AI (YC P26) @BentoLabsAI]

Teams running agents in production, what is one thing you wish your monitoring could tell you that it currently cannot?

[BentoLabs AI (YC P26) @BentoLabsAI]

@abhitwt The human in the loop out here doing god's work, all because the toilet paper fumbled the first few steps. we've all been that person :,)

[BentoLabs AI (YC P26) @BentoLabsAI]

Why agents that work in staging often degrade in production?

It's usually a diagnostic failure. Users use your agents in ways you can't even imagine, that results in failures that are even harder to catch and work on.

Our framework helps you spot which layer is actually breaking.
Read here 👇🏻
https://t.co/M6542A7cJV

[BentoLabs AI (YC P26) @BentoLabsAI]

We ran our recursive learning layer on Terminal-Bench 2.0. Same agent. Same model. Same harness. Same budget.

The result: Claude Sonnet went from 42.2% → 52.4%. A +10.2 percentage-point lift, significant at p < 0.05, with a 13:3 task-level win/loss ratio (internal).

The only variable was a learning layer.

We wrote a full technical breakdown on what changed, why it worked, and what this means for production AI agents.

Read it here 👇
https://t.co/VhVCgURuXv

[Kaushik @kacppian]

My co-founder @Abhinavv_soni clearly does not like being kept away from his agents.

PS: BTS of the BTS.

#launchsoon

[BentoLabs AI (YC P26) @BentoLabsAI]

Consider this a glimpse of what's coming

#launchsoon

[Abhinav Soni @Abhinavv_soni]

Almost didn't document the day, my team made sure we did.

Some days you just feel the shift. We booked a studio, brought in a team, and spent the day trying to capture what @BentoLabsAI actually is right now. Where we started, where we are, and where we're going. It's one thing to build in silence. It's another to finally show it in a much bigger way.

We've been deep in production agent systems, working with some of the top teams running AI at scale today. The problem we set out to solve is more real than ever.

Not ready to say more just yet. But it's close. Stay tuned.

[BentoLabs AI (YC P26) @BentoLabsAI]

We are live on the YC Directory.

https://t.co/6nEr0It6Do

[Abhinav Soni @Abhinavv_soni]

Stop fine-tuning your model.
Your harness is broken.
The model was fine.

[BentoLabs AI (YC P26) @BentoLabsAI]

The model: “I can do it, I promise.”

The harness:
❌ wrong context
❌ broken retrieval
❌ timeout
❌ hallucinated tool response

Everyone:
“wow, this model is really bad”"

[BentoLabs AI (YC P26) @BentoLabsAI]

Everyone wants AGI.

You just want the pager to stop going off after deploying one prompt change.

Don't worry. We got you. Coming soon to save you some sleep.

[BentoLabs AI (YC P26) @BentoLabsAI]

Busy building for the humans behind AI agents.
Stay tuned.

[BentoLabs AI (YC P26) @BentoLabsAI]

https://t.co/cl8cAsUYU4

[BentoLabs AI (YC P26) @BentoLabsAI]

Other tools show you the known failures.
We show you the unknowns as well.

But we don't stop at detection.

We help prevent them from repeating. Knowledge carries forward. Successful patterns get reinforced. Failures get avoided.

Knowledge compounds over time!

[BentoLabs AI (YC P26) @BentoLabsAI]

Why we call it 'learning infrastructure':

Traditional monitoring: Log → Alert → Debug → Patch → Repeat

Learning infrastructure: Capture → Learn → Apply → Improve → Compound

The difference between reactive maintenance and proactive improvement.

[BentoLabs AI (YC P26) @BentoLabsAI]

If you've ever noticed your production AI agents ignoring instructions mid-run and spent hours debugging it.

Here's why it might be happening and how you can fix it.

https://t.co/OfZ2Z8Lasc