SamX

I build and work with AI Agents because I have ADHD.

[SamX @HyperfocuSam]

People just don't get it - use AI to automate the dirtyworks for you, not the meaningful ones.

It doesn't matter if your are business owners, executives, teams or individuals.

Say, if content writing is where your passion and strength lies, just do it on your own, do not just "DRAFT A POST FOR ME ABOUT XXXX". Instead let LLM to assist you in research and dedicate an AI Agent to take care of platform posting for you. Let AI be your source of inspirations, not an uncontrolled proxy.

I saw enough talented individuals and enterprises spending hours and hours just trying to make LLM replicates 100% of what they are current good at doing. They are in FOMO status just thinking if they are not doing do they are behind.

NO, the true reason why your competitor are getting ahead is they are focusing on their shorthands with AI, meanwhile maximizing their strength by their own identity. It is a matter of focus, not technical.

In 2025 we will see an explosive development in AI Agent. This mindset is ever more essential to have since Agent is the magnifier of standalone LLM, the gap between those who strategically adopt agents and those who apply agents out of FOMO will be bigger than ever.

AI will replace mediocre, but magnify talents - wrapping up 2024 with this my biggest takeaway and I hope share with you if your are in the bottleneck of AI adoptions.

[Firecrawl @firecrawl]

Today we're launching anydoc, our new Rust-based doc parsing engine 🔥

sub ~5ms markdown parsing for PDFs, Word docs, slide decks, and 10 other formats with best in class quality.

100% open source and powering our /parse endpoint!

[DAN KOE @thedankoe]

The average person does not try to solve their problems or struggles. They get stuck in a routine and live the same day over and over. It does not cross their minds to snap out of it, engage in strategic thinking, and change direction so they can eventually reach a more advantageous position in life.

If you want to get ahead of 90% of people, all you have to do is pause, think, and actually attempt to overcome the struggle you're faced with.

[LN @ln_dev7]

Open-source template for your management projects

GitHub : https://t.co/BQNravXTmG

[Firecrawl @firecrawl]

we open sourced the fastest pdf parser engine

pdf-inspector powers /parse together with our custom OCR models

0.002s per page

[Guillermo Rauch @rauchg]

Open source agentic CRM built on https://t.co/99eEa13mZ3 and @nextjs.

Model-agnostic, self-hostable or serverlessly-deployed, multi-channel, and headless.

This is the way.

[Min Choi @minchoi]

This Claude Code prompt is literally $300/hr senior engineer🤯

[Andrej Karpathy @karpathy]

We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all.

I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand.

Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.

[ChatGPT @ChatGPT]

Work with just your voice, hands free.

See—and hear— ChatGPT Voice in action, now on macOS and Windows.

[GREG ISENBERG @gregisenberg]

The biggest opportunities right now:

1. build for solving loneliness (the more AI floods everything, the more people crave real human connection, IRL and small social)

2. build for agents that need to spend money (they're getting virtual cards and budgets, someone builds the spend controls, fraud protection, receipts)

3. build for people drowning in AI output (everyone generates infinite drafts now, the bottleneck moved to reviewing and choosing, build the judgment layer)

4. build for the burnout economy (everyone is expected to always be on and always optimizing, and the backlash toward rest, slowness, and enough is building)

5. build for verifying humans (deepfakes broke trust, every dating app, marketplace, and video call needs proof-of-human within 2 years)

6. build for the physical world (the trades, hardware, robots that AI is finally reaching)

7. build for the agent that answers the phone (every local business misses calls after 5pm, a voice agent that books the job is worth thousands a month)

8. build for the aging (70M+ boomers who want to stay healthy, sharp, and connected)

9. build for the LLM-search land grab (being the cited answer is the new SEO)

10. build for the newly automated (the paralegal, the analyst, the marketer whose job just changed and needs to reskill fast)

11. build for the seat-pricing collapse (software repricing from $50/seat to per-outcome, whoever nails outcome billing wins a category)

12. build for AI enablement (95% of businesses use nothing beyond ChatGPT, someone has to onboard the other 95%)

13. build for the agency everyone resents (businesses pay $1k/mo to agencies they hate, an agent that does 80% of it undercuts the model)

14. build for verticals on 2011 software (dentists, HOAs, contractors, all overdue for an AI-native rebuild)

15. build for reviving dead software (thousands of abandoned apps with real users, agents can maintain what a team couldn't, buy and revive)

16. build for markets too small to matter before (500 lobster fishermen was never worth a team, now it's a weekend and a real business)

17. build for agents hiring agents (a shadow economy is forming, it needs escrow, reputation, and dispute resolution for machines)

18. build for the anti-AI premium (as everything gets generated, human-made and analog become status symbols people pay up for)

19. build for distribution-first (anyone can build the product now, so the audience is the moat, media company first, product second)

20. build for the reinvention of college (what does an MBA even mean anymore)

21. build for a world with more free time than it knows what to do with (if AI takes the busywork, the question becomes what people do with the hours, and that's a civilization sized market)

note: more trends/ideas @ideabrowser (free to sign up)

22. build for the return to the physical (screens fill with slop, people crave the real world, the hands-on, the local, the analog)

23. build for the caregiving wave. The population is aging fast, tens of millions are caring for parents, and the whole burden is landing on families with no support.

24. build for the longevity shift (people want to live to 100 healthy, and a whole industry is forming around actively managing your own biology)

25. build for the housing and rootlessness problem (people can't afford to settle down, and the whole idea of a stable home base is up for grabs)

26. build for spiritual hunger (as institutions hollow out, the need for meaning, ritual, and belonging is exploding into new forms)

KEEP BUILDING

[Y Combinator @ycombinator]

We’ve decided to open-source a multi-agent harness we use internally at YC.

We call it “QM” and it’s meant to be easy to customize, like Hermes or OpenClaw, but useful for a whole company. We use it across accounting, legal, events, and engineering (including building QM itself!).

The whole project is under an MIT license. It is cloud-first and has Slack and web UI natively.

[Marina Budarina @marina_uiux]

Interactive chimes quick tutorial

Links and resoirces 👇🏻

[Jackson Greathouse Fall @jacksonfall]

https://t.co/D5aNSrUEgl

made a free + open source riso inspired analoguish print shop for web

excited to see what you make with it!

[SpaceXAI @SpaceXAI]

Use the TinyFish plugin in Grok Build to give your agent powerful search and retrieval capabilities on the web

[AmirMušić @AmirMushich]

How to design a premium pitch deck with AI (tutorial)

I built 10 free pitch deck templates for you - and you can remix them in minutes respecting your brand, changing copy, graphs, backgrounds etc.

By just telling AI what to do
Full tutorial:
https://t.co/LHSv5KHX9a

[Gizem Akdag @gizakdag]

My type of restaurant

[Gizem Akdag @gizakdag]

Menu design

[Codez @0xCodez]

https://t.co/OKJyooXqTc

[Berryxia.AI @berryxia]

兄弟们，微软居然还搞了这个好东西，值得看看啊！
做零售店、巡检的行业人简直是大喜~

Microsoft扔出一个仅仅4B的流式视觉模型，能实时盯着视频说“什么时候发生了什么”。

Mage-VL是Codec-Native的Streaming VLM，专门做直播式理解。

它一边看视频一边描述正在发生的事，你还能用自然语言指定关心的时刻，比如“火车到站的时候”“进球的瞬间”。4B体量却能持续处理流式输入，效率很高。

以前实时视频理解要么靠大模型烧算力，要么只能事后分析。

[Max For AI @MaxForAI]

如果不是看了法院判决的原文，我绝对不知道Anthropic有这么畜生。。。。

一边天天教育全世界要重视AI安全，一边为了训练Claude，干了一套相当畜生的事情。

首先是它花了数百万美元，买下数百万本实体书。

然后雇人把书脊拆掉，把每一页裁开，逐页扫描成可以检索的PDF，最后把纸质原书全部丢弃。

法院的表述是：
「The print original was destroyed. One replaced the other.」

纸质原件被销毁，数字副本取而代之。

数百万本书，就这样被买回来，拆掉，裁开，扫描，销毁。

但这甚至还不是Anthropic干得最离谱的事。

判决显示，从一开始，Anthropic明明有很多渠道可以买书，但法官直接写道，它更愿意「preferred to steal them」，因为这样可以避开Dario Amodei所说的法律、实务和商业麻烦。

并且Anthropic联合创始人Ben Mann还亲自下场了。

2021年初，他下载了Books3，里面有196640本未经授权的版权书籍。

几个月后，他又从LibGen下载了至少500万本盗版书。

2022年，Anthropic继续从PiLiMi下载了至少200万本。

判决明确指出，Ben Mann和Anthropic知道这些累计超过700万本的书是盗版的。

更恶心的是，Anthropic后来已经意识到法律风险了。

��部开始对继续使用盗版书训练模型有所顾忌，原因就是「法律问题」。

但法院紧接着写了一句：「It kept them anyway.」

虽然知道有问题，Anthropic它还是把书留下来了。

当然Anthropic也尝试过找出版社授权。

2024年，它专门挖来Google图书扫描项目的前合作负责人，任务是弄到「世界上的所有书」。

他给几家大型出版社发了一两封邮件，询问AI训练授权。

法院认为，如果继续谈下去，原本可能达成许可协议。

但Anthropic高层让这些谈判直接中止了。

因为高层认为谈版权太麻烦，还是批量买书、拆书、扫描比较省事。

而那些被Anthropic弄来被并被销毁的书，也不是训练完就删掉。

Anthropic准备把它们放进一个永久的通用中央图书馆。即使已经确定某些书永远不会再用于训练，也要继续保存。

法院还提到，数百名工程师可以访问这些文件，并为其他用途制作副本。

法官甚至批评Anthropic在相关证据披露上进行了回避。

但最讽刺的是，法院最后认定：用这些书训练大模型，本身可以属于合理使用。

原因是任何人合法购买实体书后，将它一对一转换成数字副本，并销毁原书，也可以属于合理使用。

Anthropic真正栽掉的，是它明知书籍来自盗版网站，仍然下载超过700万本，并试图建立一个永久保存的通用图书馆。

法院最后还特意表示：

Anthropic后来买下一本它此前从网上偷来的书，也不能免除之前盗版的责任。

所以这件事里Anthropic最畜生的地方是：

Anthropic并不是因为不知道版权规则才盗版。

它知道正规授权渠道在哪里，也知道这些书是盗版，更知道继续使用存在法律风险。

它只是觉得走正规流程太麻烦。

这家公司对AI安全的道德要求似乎主要适用于未来的机器。

至于自己，先把700万本书偷回来再说。

[Orange AI @oran_ge]

Finally, everyone has realized how serious the problem is.

Over the past six months, model training has made tremendous progress in agentic coding through RLVR. But in other areas, progress has stalled.

English writing has even started to regress.

What models say is becoming increasingly difficult to understand.

Opus 4.7 to Opus 5 was a completely failed experiment.

Mythos and Fable were also at their best when they had just been released, before they had gone through much RL.

After RLVR, we may need a new kind of RL.