mahesh (@_mnat_)

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When life gives you codex and free will

Of course you make yourself a massive LED Jumbotron in the office to monitor everyone who progresses through your puzzle

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Moritz Stephan Verified account @moritz_stephan Aug 12

🧩 -> hone.com

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mahesh @_mnat_ Oct 12

these guys totally aren't hiding anything..
🧩 hone.com

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mahesh @_mnat_ Oct 8

Frontier models can hill-climb almost any goal that is well specified and verifiable.

Most work inside a company is neither. The goals live in people's heads, and there is no way to check a change before it touches real work.

Hone's engines are built exactly for this. They learn implicit goals from users and their environment, then propose improvements to their own harness, promoting the ones that don't introduce regressions in simulation.

We wrote up how this these simulations works: hone.com/blog/closing-t…

If you want to work on the problems that get more valuable with each model release, we're always looking for the brightest talent: hone.com/careers/

hone.com Closing The Gap #1 - Simulations For Self-Improving Agents — Hone Engines replay each change to their own harness in simulation before promoting it, so regressions are caught before a user sees them.

Hone @hone Oct 8

Today Hone launches Engines: AI that owns business outcomes.

Chatbots give answers. Agents do tasks. Engines deliver outcomes, and we hold them responsible for creating real value, measured in actual dollars instead of tokens or vibes.

You point it at a business metric, and the Engine figures out the rest. It onboards itself, builds the necessary agents, skills, and memories, collaborates with the right people, and gets better with experience.

From AI leaders to global enterprises, our customers have already used Engines to:

• Uncover millions in procurement savings
• Optimize product funnels
• Manage credit risk
• Increase qualified pipeline in new territories
• Accelerate implementations and improve account management

To scale this impact across the economy, we’ve raised a $60M seed led by Benchmark and Index with participation from Elad Gil, Hanabi, Definition, Diffusion, Lux, SV Angel, and Align.

AI’s raw capabilities are far ahead of the value it creates in the real world, and Engines will help close the gap.

Here’s how they work…

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mahesh @_mnat_ Aug 21

overintellectualizing the hone.com landing page reveal animation to be maximally dopaminergic

smoothstep() strikes again (h/t @iquilezles)

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mahesh @_mnat_ Aug 20

the models of today still seem to have very poor theory of mind..

pic is an excerpt from the claude code system prompt regarding delegation semantics, where they explicitly urge the model to "never delegate understanding", "Brief the agent like a smart colleague who just walked into the room", etc.

models tend to either vastly over- or under- delegate context to their peers/"minions" without additional guidance. unclear if this improves with larger pretaining bases that would have the higher 'raw iq' to better think from another agent's perspective, or if post-training with the right collaboration incentives would inherently develop the capability.

people go through y e a r s of school to learn how to communicate their ideas effectively (write), why don't LLMs do the same? (if we imagine a future of multi-agent collaboration)

mahesh

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