LLMs aren’t perfect, but calling them a “cult” misses the point. They’re not just fancy heuristics, they’re general-purpose function approximators that can reason, plan, and adapt across a huge range of tasks with zero task-specific code.
Sure, it’s not AGI. But dismissing the progress as just marketing ignores the fact that we’re already seeing them handle complex workflows, multi-step reasoning, and real-time interaction better than any previous system.
This is more than just Lisp nostalgia. Something real is happening.
Sure, I have seen the detrimental impact on some teams, and it does not play out as Marketers suggest.
The trick is in people seeing meaning in well structured nonsense, and not understanding high dimension vector spaces simply abstracting associative false equivalency with an inescapable base error rate.
I wager Neuromorphic computing is likely more viable than LLM cults. The LLM subject is incredibly boring once your tear it apart, and less interesting than watching Opuntia cactus grow. Have a wonderful day =3
For the most part, O-1 filings for the founders or employees of startups are no more difficult than the O-1 filings for employees of established/large companies; the main issue is "distinguished reputation" (a component of one of the O-1 criteria), which can be harder for startups to show.
Built Taskade by solving my own workflow pain points, need for structured note taking, and our team being remote, fully distributed. Launched on Product Hunt, joined niche subreddits/communities, responded to feedback fast, and kept shipping + relaunching.
First 100 users came from showing up where early adopters hang out essentially.
Working on Taskade (https://www.taskade.com), building the execution layer for AI collaboration.
Taskade started as a real-time workspace for teams to organize projects and ideas. It's evolved into something bigger — a platform where humans and AI work side by side.
We’re moving past simple chatbots into real agentic workflows, where teams can generate structured task lists, mind maps, and tables, train custom AI agents with dynamic knowledge, and automate work from start to finish.
Today, Taskade is built around three core pillars: Projects, Agents, and Automation. It’s like giving your team a second brain that can think, plan, and get work done across projects, automations, and real-time collaboration. If you’re interested in the future of human-AI collaboration, take a look!
Merry Christmas and happy holidays everyone! My dad’s birthday is on Christmas, so it was always a double celebration. Growing up in Queens, we’d sometimes go to Atlantic City, taking a Greyhound or driving once we had a car. We’d head to Bally’s, enjoy the Christmas vibes, and spend hours at the buffet.
Those trips were always fun. This year, he’s in a rehab hospital on another continent after a stroke, but we’re all staying hopeful to celebrate together next year.
I’m working on https://taskade.com, which started as a unified workspace for distributed teams to collaborate. Now, it’s become a playground for AI agents that work alongside you.
These AI agents think, learn, and act—handling tasks, research, and more—right in your workspace where you can chat, manage tasks, create mind maps, tables, and more.
Funnily enough, 'obstinate' was one of the first words I picked up in ESL, fresh off the boat. I loved throwing it into conversations just to practice and feel smart... And here I am, years later, reflecting on that word.
This is still being actively updated, just wow. Growing up on alt rock, it's so good to see most of these bands still kicking it. (RIP Chris and Chester)
On the topic of AI, you've brought up some valid points, and I understand the skepticism, especially given the AI hype cycle. However, there's also plenty to get excited about beyond the marketing gimmicks.
Consider the recent Google demo. It was recreated and, while still fun and impressive, it's definitely not ready for commercial use. You can see it at https://sagittarius.greg.technology. This demo is a preview of what's to come, and I think it's important for us to stay open-minded.
I believe that in 2024, we're going to witness a significant expansion in what's possible with AI, while costs decrease. Increased contributions in the open-source community will likely fuel another wave of startups and new applications.
My current reference class with AI today is 3D games in the 90s.
Doom has just turned 30; when it was introduced, it blew people's minds with the quality, and fuelled a moral panic about it being a "murder simulator". Every year or so after that, a new game would come out, be hailed by the press as "photorealistic", and then forgotten as the next in the cycle replaced it… but even then, they're called "Doom clones", and the original doesn't disappear.
I even remember one of the magazines bemoaning that Riven was pre-rendered rather than real-time "given Quake proves the PowerPC chip can handle polygon-based gaming" (or something close to that quote).
I think we're in a similar phase with AI: ChatGPT-3.5 blew people's minds with the quality, and fuelled a moral panic about it being a fully automated plagiarism/cheating engine, we keep getting news stories about new models or ways to get much more out of any model, which are then forgotten as the next hot thing repeats the cycle… but even then, they're called "ChatGPT clones", and the original doesn't disappear.
It's only an analogy; I don't know how long we have to wait before AI becomes an almost unnoticeable enhancement of everything in the kind of way CGI did.
That Corey Quinn article is great, thanks for sharing. It's a more thorough mirror of my own experience with Q. After seeing the obnoxious popups all over the AWS docs I tested it out with a few simple questions about AWS services.
My main takeaways were
1. It refuses to answer a lot of simple questions.
2. It provides a lot of factually incorrect answers.
I didn't even try any complicated or subtle questions; it failed at simple factual asks.
So many companies are rolling out obviously half-baked and useles Gen AI features that I would be embarrassed to release. All of these terrible user experiences must be damaging some company reputations. The only justification I can see is that many large corporations care more about being able to tell investors and journalists that they have checked the box on having the latest shiny trend than they do about building actually useful tools and user experiences.
Sure, it’s not AGI. But dismissing the progress as just marketing ignores the fact that we’re already seeing them handle complex workflows, multi-step reasoning, and real-time interaction better than any previous system.
This is more than just Lisp nostalgia. Something real is happening.