AI Agents on Aneesh Sathe

Agent Harness Engineering vs. Loop Engineering vs. Graph Engineering

Sat, 01 Aug 2026 21:06:00 +0000

Bookmarked: Agent Harness Engineering vs. Loop Engineering vs. Graph Engineering

Jan 10, 2025 - AI Agents, Machiavelli's Study

Fri, 10 Jan 2025 08:06:00 +0000

Agents Are Not Enough #

Last year I was heavily experimenting with Knowledge Graphs because it’s been clear that LLMs by themselves fall short because of the lack of knowledge. This paper by Chirag Shah and Ryen White (you can click the heading above) from Dec 2024 expands on those shortcomings by exploring not just knowledge but also value generation, personalization, and trust.

They open the paper by casting a very wide definition of an “agent” everything from thermostats to LLM tools. While this seems facetious at first, their next point is interesting. Agents by definition “remove agency from a user in order to do things on the user’s behalf and save them time and effort.”. I think this is an interesting way to injext an LLM flavored principal agent problem into the Agentic AI conversation.

Jan. 8, 2025: Count your DIGITS! Drunk Bayesian

Wed, 08 Jan 2025 08:06:00 +0000

NVIDIA Project DIGITS #

Around 2015 I was putting together funds in academia. Convincing IT, senior professors, and finance that yes, it was worth giving me a LOT of cash to build a workstation with multiple GPUs.

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“No, it isn’t for gaming.”
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“Yes, it will change the world.”
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“No, there are no university rules that hardware bought multiple invoices across multiple departments can’t be used in the same box.”
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“Yes, I’m aware that all my individual quotes are just below the bureaucracy summoning purchase limits.”
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“Yes I tried random forest with the other stats and ML methods, this really is better. How do I know? Well…”

Jan. 5, 2025

Sun, 05 Jan 2025 14:00:00 +0000

Improving Research Through Safer Learning from Data #

Another one of Frank Harrell’s posts. Given my day job, and the R&D background this one is quite close to home. As a team leader on the industry side one hopes to build a culture with the team that aligns scientific rigor with company goals. Any method, statistical or cultural (in this case both), that solves for this tension will get you the most bang for your buck.

Dancing on the Shoulders of Giants

Fri, 10 May 2024 18:31:09 +0000

In Newton’s era it was rare to say things like “if I have seen further, it is by standing on the shoulders of giants” and actually mean it. Now it’s trivial. With education, training, and experience, professionals always stand “on shoulders of giants” (OSOG). Experts readily solve complex problems but the truly difficult ones aren’t solved through training. Instead, a combination of muddling through and the dancer style of curiosity is deployed, more on this later. We have industries like semiconductors, solar, and gene sequencing with such high learning rates that the whole field seems to ascend OSOG levels daily.