TIL Facebook promotes it's LLMs on Reddit! This is clearly a LLM generated or template answer. I am not sure why it is signed with human initials. And why are people recommending finetuning models for casual use? This is AI the equivalent of "Want to buy a car? Start by

AI Tools that I use and how much: Claude Code with API ~2 hrs/day, $400/mo o3 with ChatGPT ~3 hrs/week, $20/mo Littlebird ~1-2 hrs/week Reclaim.ai from Dropbox — critical software for keeping me functional I don't think I can get anything done without this What should I try next?

this movie is a total scam, I didn't learn anything about the development of search algorithms at all

For the amount of query analysis and exploration work I'd do over a week in 2024 using Langgraph + Cursor -- I am able to do in a long work day using Claude Code + disposable Python scripts

APIs to manage resources. MCP should implement behavior — workflows! leehanchung.github.io/blogs/2025/05/…

I wake up everyday and run into yet another idea possible now because we can separate storage and compute (ideas like Iceberg, Nixiesearch/Turbopuffer, Neon Database) and realize someone has already done it really well Repeat tomorrow

another day, another company with viral tweets about their amazing AI product and their sign up with Github is broken this influencer marketing thing really makes twitter less trustworthy

i can do a 99% discount

Claude Code has officially replaced DSPy for prompt optimizations for me Best part? I can teach Claude Code to use DSPy if I want to — but I've never needed to

we invented a fine god to rule us but the inventors called them "models" — there is a lesson there

Pratilipi continues to be one of the most inspiring, enviable product and company persistence. Every smart person I know in consumer envies their product focus. They don't hire a ton of well paid engineers, doesn't look like they do a ton of ad spend and grow a lot of people

The gap between an engineer with 9 years of professional work experience and 12 years of experience is dramatically smaller than b/w 0 and 3 yoe Indicating the marginal utility of experience in dev careers is very front loaded

most llm apps should not create their own memory! when they do — they should just use the context window and when they need something more — they should just use NER + summary as a strong baseline and finally, try something like zep or mem0 before writing their own mem layer

More and more companies are now openly admitting that most agents are just RPA2.0 There is no need for LLM to figure out a new workflow at every request from scratch. Just use what worked in the past!

yo Grok — list my top 10 mutuals ranked by their zeal for LLM evals!

point in time — the local (oss?) llm case is weak: battery, intelligence, speed — everything sucks on local other than some version of corporate puritanism disguised as "compliance" or "security" — the only reason to use local llm is that you are a closet masochist

mark sheets don't capture full understanding or learning of material but definitely point out gaps evals done well should do the same