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your timeline convinced you AI is in a bubble. talk to a boomer above the age 35 for 5 minutes. most people don’t even know what claude is.​​​​​​​​​​​​​​​​ kind of wild when you zoom out.

- Drafted a blog post - Used an LLM to meticulously improve the argument over 4 hours. - Wow, feeling great, it’s so convincing! - Fun idea let’s ask it to argue the opposite. - LLM demolishes the entire argument and convinces me that the opposite is in fact true. - lol The

I wanted to share a bunch of my favorite hidden and under-utilized features in Claude Code. I'll focus on the ones I use the most. Here goes.

I am humble enough to admit when I was wrong - 30k views in 5 days, maybe you are too youtube.com/watch?v=YwZR6t…

Based on everything explored in the source code, here's the full technical recipe behind Claude Code's memory architecture: [shared by claude code] Claude Code’s memory system is actually insanely well-designed. It isn't like “store everything” but constrained, structured and

Claude Code leaked their source map, effectively giving you a look into the codebase. I immediately went for the one thing that mattered: spinner verbs There are 187

rahat 👋 This is one of the signals we use to figure out if people are having a good experience. We put it on a dashboard and call it the “fucks” chart

LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating

I have also stopped using plan mode It creates a plan FAR too eagerly and usually asks you zero questions en route The whole point of planning is to get on the same wavelength with the LLM, not to generate an asset you don't read /grill-me all the way

Building a personal knowledge base for my agents is increasingly where I spend my time these days. Like Andrej Karpathy, I also use Obsidian for my MD vaults. What's different in my approach is that I curate research papers on a daily basis and have actually tuned a Skill for

Honestly, this is the most accurate diagram I've seen. Waterfall: You plan for 18 months and deliver exactly what nobody needs anymore. Agile: You deliver something usable at every step, but the CEO keeps asking, "Where's the car?" AI: You get the car on day one. It has six

if you care about coding agents and tasteful software def go watch this talk by Mario Zechner it’s very good youtu.be/Dli5slNaJu0?si…

this is great, am writing a similar blog which is even more important why there are open harnesses - memory cannot be stuck in a proprietary harness or behind a proprietary api

plans vs outlines vs design docs: I think the value of a plan-for-the-model is take intent + codebase research and build like a "guide to building this feature for idiots" - at least 80-90% correct, close enough that you have high success chance to spray out the diffs and fix

feels like model providers have shifted from chasing 100% intelligence to some percentage split between raw intelligence and more-vertical products i think its a signal that making models generally smarter is topping out and its more cost-effective to fill in the gaps with

Morning Bathrobe Rant: AI out-codes you; deal with it.

This GitHub incident is insane. Merge queue commits have been reverting previously merged commits at random. This not only breaks the mental contract teams have with Git in general, but is subtle enough to be really hard to unravel after the fact. githubstatus.com/incidents/zsg1…

yesterday I reported on GitHub employee concerns about reliability and leadership, and then hours later GitHub suffered a catastrophic outage 😬 theverge.com/news/918001/gi…