RoRockRocket @rorockrocket

Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

staysaasy @staysaasy

3 months ago

The degree to which you are awed by AI is perfectly correlated with how much you use AI to code.

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one engine is fun. four engines in one AI game creator skill is better. → now shipping @godotengine and @unity via MCP. → phaser for 2D. three.js for browser 3D. shaders, physics, audio. just describe what you want. @DannyLimanseta game looks great. give it a shot.

Danny Limanseta @DannyLimanseta

3 months ago

I am having a lot of fun with this ThreeJS game. Will probably be spending more time on this cosy flyer game for #vibejam And btw, shaders are awesome! I highly recommend anyone building a 3D game to add some shaders to make your game look good. Here's a quick primer on the

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> been paying $200/month for cloud AI APIs > laptop: M2 MacBook, 16GB RAM > tried running models locally, garbage quality after 4K tokens > read this TurboQuant breakdown on Tuesday > applied 3-bit KV cache compression > same MacBook now runs 100K token conversations > quality: identical to cloud > cancelled all API subscriptions Wednesday > it's been 3 days > saved $200/month forever > with a free algorithm from a free paper > my MacBook didn't change. the math did

BuBBliK @k1rallik

3 months ago

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- 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 LLMs may elicit an opinion when asked but are extremely competent in arguing almost any direction. This is actually super useful as a tool for forming your own opinions, just make sure to ask different directions and be careful with the sycophancy.

@arafatkatze @cline We need to get Cline into Paperclip

dotta 📎 @dotta

4 months ago

We just open-sourced Paperclip: the orchestration layer for zero-human companies It's everything you need to run an autonomous business: org charts, goal alignment, task ownership, budgets, agent templates Just run `npx paperclipai onboard` github.com/paperclipai/pa… More 👇

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When I built menugen ~1 year ago, I observed that the hardest part by far was not the code itself, it was the plethora of services you have to assemble like IKEA furniture to make it real, the DevOps: services, payments, auth, database, security, domain names, etc... I am really looking forward to a day where I could simply tell my agent: "build menugen" (referencing the post) and it would just work. The whole thing up to the deployed web page. The agent would have to browse a number of services, read the docs, get all the api keys, make everything work, debug it in dev, and deploy to prod. This is the actually hard part, not the code itself. Or rather, the better way to think about it is that the entire DevOps lifecycle has to become code, in addition to the necessary sensors/actuators of the CLIs/APIs with agent-native ergonomics. And there should be no need to visit web pages, click buttons, or anything like that for the human. It's easy to state, it's now just barely technically possible and expected to work maybe, but it definitely requires from-scratch re-design, work and thought. Very exciting direction!

Patrick Collison @patrickc

3 months ago

When @karpathy built MenuGen (karpathy.bearblog.dev/vibe-coding-me…), he said: "Vibe coding menugen was exhilarating and fun escapade as a local demo, but a bit of a painful slog as a deployed, real app. Building a modern app is a bit like assembling IKEA future. There are all these services,

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I sat down with Greg and explained how to use Paperclip and share some of my best tips Is this not the greatest time in history to be building?

GREG ISENBERG @gregisenberg

3 months ago

I met the guy behind Paperclip. he won't show his face, but he just built one of the FASTEST growing open-source projects in AI. how to use Paperclip to hire AI agents to ACTUALLY run a startup with 0 employees: 1. with paperclip, you hire a team of AI agents like CEO,

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pi-gui takes another step to provide a codex app vibe/ux for pi fans. Build now includes tool expansion/collapse, in timeline diff viewer, diff reviewer panel, @ file references. Hope you like it! Also works off the bat with my new pi subagents extension, and should for other extension tools too :) Will explore better extensions support for the gui experience too.

the bitter lesson is coming for search we're open-sourcing Context-1 - a model that is better, faster, and cheaper than any frontier model at searching we published a 40-page technical report on our website with the ins and outs of how we did it. this is just step 1

Chroma @trychroma

3 months ago

Introducing Chroma Context-1, a 20B parameter search agent. > pushes the pareto frontier of agentic search > order of magnitude faster > order of magnitude cheaper > Apache 2.0, open-source

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🔊Introducing Voxtral TTS: our new frontier open-weight model for natural, expressive, and ultra-fast text-to-speech 🎭Realistic, emotionally expressive speech. 🌍Supports 9 languages and accurately captures diverse dialects. ⚡Very low latency for time-to-first-audio. 🔄Easily adaptable to new voices

I think this is the best post I've ever made.

ngrok @ngrokHQ

3 months ago

Quantization can make an LLM 4x smaller and 2x faster, with barely any quality loss. But what *is* it? @samwhoo crafted a beautiful interactive essay explaining it from first principles, aimed at coders, not mathematicians. ngrok.com/blog/quantizat…

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Isn't it beautiful to watch? Compounding.

Nyk 🌱 @nyk_builderz

4 months ago

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1/4 LLMs solve research grade math problems but struggle with basic calculations. We bridge this gap by turning them to computers. We built a computer INSIDE a transformer that can run programs for millions of steps in seconds solving even the hardest Sudokus with 100% accuracy

@ChristosTzamos Wait this is so awesome!! Both 1) the C compiler to LLM weights and 2) the logarithmic complexity hard-max attention and its potential generalizations. Inspiring!

Best article on Pi Coding Agent If there was to be an advert for why you should use Pi - this is it Fully customise it to your needs Huge set of community plugins to work with I advise many folks that Pi is the better base over OpenCode Spotify CEO @tobi loves it too

marv1nnnnn @marv1nnnnn1

3 months ago

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bookmark this immediately. cognee just solved the biggest problem with ai skills/prompts, they break silently over time and its hard to notice their fix: skills that observe their own failures, inspect what went wrong, and amend themselves automatically. try not to fall behind ^^

Vasilije @tricalt

3 months ago

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your edge is whatever you know that the models don't know

This might be one of the most useful gh repos on the planet.

GREG ISENBERG @gregisenberg

4 months ago

i found a github repo that lets you spin up an ai agency with ai employees engineers, designers, growth marketers, product managers each role runs as its own agent and they coordinate to ship ideas 10k+ stars in under 7 days 1. engineering (7 agents) frontend, backend,

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recommended viewing. "we're all making hotdogs"

Mo @atmoio

4 months ago

I was a 10x engineer. Now I'm useless.

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