Athen

[Alps (e/acc) @alpaysh]

i still think about this ngl

[Dr Nimo Yadav 2.0 @DrNimoYadav]

Former BJP spokesperson Shehzad Poonawalla beaten black and blue in a reality show 😭😭

[Tony Dinh @tdinh_me]

You can do this on your own now. So cool.

[Movez @0xMovez]

Opus 5.5 is insane for motion design...

send this single prompt to Claude Opus 5.5 to turn it into a professional motion design studio.

then read the full guide to mastering motion design with Opus 5.5 in the article below.

[Ashish Kushwaha @ashishllm]

How to get 36 LPA job opportunities as an AI Engineer with 4 YOE. Just like me. Real Deal. No BS Guide... https://t.co/tbyQw1HXjm

[Chain @achxvi]

here is the prompt I used:

"make a dynamic 15-second motion graphics video about Pocketsflow that shows what an incredible motion designer you are, like it's your showreel for a résumé. go all out.

here is elevenlabs key:
xxxxxx_youthoughtiwouldleakit_xxxxxx

make a video where a character talks about pocketsflow and how people can use it and what can they do with it etc etc etc

LFG"

[Nate @natebjones]

This is my new favorite example of written clarity

The entire vision for Muse in 364 words

[Logan Gott @LoganTGott]

https://t.co/tzxwdtTnXg

[Paradis @ParadisLabs]

Recommended reading for the weekend:

1. @alexandr_wang — Why I'm Building Muse
2. @gregisenberg — AI-native services: a $100B opportunity
3. @FranklnTempletn — Macro Views: Growth Holds, Pressure Builds
4. @Google — Behind Project Suncatcher, our moonshot to put AI in space
5. @EpochAIResearch — The plunging price of thought
6. @AnthropicAI — Measurements for
understanding the pace of AI development inside frontier labs

Hope everyone has a great weekend!

[Jake Castillo @jakecastilloooo]

This is GOATED for AI UGC, get in here

[Mayukh @mayukh_panja]

Evil but competent people are much more tolerable than good people who are utterly incompetent.

Incompetent idiots who may have their hearts in the right place cause way more damage than say a selfish but actually competent person who can get things done.

Case in point: rent control.

Idiots without any understanding of 2nd order effects are capable of completely destroying the housing market through dumb policies like rent control.

A “greedy” landlord will actually solve problems by simply building more houses.

[Deedy @deedydas]

You can now generate an entire 3blue1brown style video from any research paper with Opus 5.5.

Here’s a 8min video summary of “Regularized Recursive Self Improvement of Agent Harnesses”.

The 90%ile educational YouTuber is fully automated.

[aditya @adxtyahq]

Preferably the best time to enter the AI space and get a job too.

Cant say much but make sure to study
langchain, langgraph, RAG, vector DBs, embeddings, reranking, LLM inference, quantization, evals, agents, MCP, vLLM, fine-tuning, distillation and GPU basics.

[Mubbu @wizofecom]

A masterclass on how to become the most TRUSTED name in your industry with just 45 minutes/week:

[akshaya @akshayadinesh19]

https://t.co/CrjQfgvov9

[Deedy @deedydas]

Opus 5.5 is incredible at instructional video generation.

I made this launch video for a inference startup in 1min for ~$2. Videos like these used to take weeks if not months and a lot of coordination with agencies and 1000x the costs.

Humans broadly prefer video to text. This changes the substrate of communication. These videos actually help communicate technical ideas in seconds (photorealistic video gen like Seedance is not very useful here).
- changes how often marketing should be talking about products and launches
- change how sales people can talk about technical products to their customers
- allow technical people to easily explain concepts internally without long docs
And thats just scratching the surface within startups.

Prompt: “make a modern slick and punchy video for a modern startup that works on inference”

[Paul Graham @paulg]

A CS undergrad asked me where he could have most effect in the AI age. I said probably at either extreme: either close to the technology, actually making LLMs, or close to the customer, using AI to give them exactly what they want. Or maybe both if you can stretch that far.

[Paul Klay @PaulKlayVC]

open-sourced the best skill for finding a job!

instead of showing you how it works, here’s what it did for a real person:

a software engineer with 6 years at Google was looking for his next opportunity

he’d rebuilt the Google Shopping checkout, cutting load time from 4.1s to 1.3s and increasing completed checkouts by 6%

we gave the skill his background

it went through ~40 real companies looking for places where that exact experience could be worth serious money

30 minutes later, it found a collectibles marketplace doing $2B in annualized volume

their checkout takes 1.8s to respond to a tap

one of their competitors does it in 0.24s

even a 1% improvement on $2B is $20M a year

so instead of sending:

“hey, saw you’re hiring”

he can message the CEO with:

“your checkout could be leaving ~$20M a year on the table. I’ve fixed this exact problem before”

the skill found the company, spotted the problem, estimated what it could be worth, and wrote the message for him

and here’s the best part:

half the companies it found weren’t even publicly hiring

you can run the exact same process on your own background

send this to Claude Code, Codex, or any other agent with terminal access:

run npx skills add paulklayvc/skills --skill high-leverage-job-hunt and set it up for this agent

[Shivansh Kumar @ShivanshKr0510]

Both photos show the same man — my father, Sanjay Kumar, 55. The second was taken this week in the ICU at KIMS Hyderabad, where machines are breathing for him. I'm his son, and this thread is my request to help save his life.

Fundraiser Link :
https://t.co/MIZTdxlGNl

[Chris @ChrisGPT]

A little industry secret, every frontier lab has a tiny, tiny number of people who understand the architecture + training stack at a level almost nobody else does quite literally it can be as few as 1-6 people. Not just transformers on paper, but which changes actually survive trillion token training runs, how scaling behavior interacts with data mixtures, and all the tacit tricks that separate a good architecture from a frontier model, they can save a bad training bad and save the company millions and millions of dollars every training run.

Every lab has its “Noam Shazeers.”

When one of those people leaves, you’re losing years of accumulated, (largely undocumented) knowledge about how to make these systems actually scale and replacing that knowledge can materially set a lab back.

That’s why they’re are paid 100M to 1B in stock options + salary.