laxmena

GitHub pages :(

Here’s the source repo link: https://github.com/laxmena/concepts

GitHub pages link(will redirect it to my domain though): https://laxmena.github.io/concepts

Citing the real source HN comments will be helpful.

One big concern for me in this article is, the MRI scans were not taken during the start of the study. But, I couldnt eliminate this because the pattern (of reduced white matter in brain) seem to hold true across the pool of 1700 people.

Most curious part of in this article is the active vs passive sitting distinction. Occupational sitting (or performing intellectual activity while sitting) correlated with better brain scans and white matter.

This makes sense, if I view it as consumption vs processing thing.

TV is pure consumption, Intellectual work requires output and creation.

If this thesis holds, the rise of AI tools is a bit concerning for knowledge workers. We are shifting from active creation (writing code, writing articles, designing, etc) to passive consumption and curation (reviewing AI generated content).

Will be interested to learn more on how this study unfolds further.

That's exactly my process I follow now.

I look at the traces of agent execution, and use that as a feedback to extract common patterns. The comment patterns are extracted out as Scripts, or Skills.

So Agent doesnt have to figure out how to do things from scratch, saving considerable amount of tokens and latency.

I also came across this paper recently: https://arxiv.org/abs/2603.25158

Which does exactly the same. Extracts traces and converts them into skills for agents to use.

> If all LLM tools disappeared tomorrow, all of my scripts and processes developed with an LLM will continue to work without hiccup.

This is a really pragmatic philosophy and I think it's underappreciated. Using the LLM as a development accelerator rather than a runtime dependency gives the best of both worlds.

More I use AI tools, stronger I'm convinced that it's a force multiplier. I'm one of the strong advocates for adoption of AI at work.

But I'm also very skeptical about the narrative- that AI will simply replace workers.

The main issue is accountability. If an autonomous agent takes an incorrect action, who takes responsibility?

I recently had a first hand experience at work where an agent, designed to act on customer tickets, was authorized to suspend accounts upon request.

It incorrectly suspended an active, critical account essential to our revenue metrics. Now, the support engineer who deployed that agent is writing the postmortem/CoE.

These are some incidents why I believe AI will not "completely" replace human roles. When systems fail at scale, we still require an accountable human to analyze the failure, accept responsibility.

I have a lot of questions after reading this article

1. How would Cocaine end up in wastewater treatment plant in the first place? 2. What is the volume of Cocaine needed, or used to observe this behavior from the fish? 3. If Cocaine pollution has already been happening in the wild, are there any recorded events that support the claim of effects on the habitat

I'm curious, why would cocaine end up in the wastewater systems in the first place?