Browse Comments — Raw (as collected)

Im happy to hear about Synth ID. A cross platform standard for marking AI content feels huge for allowing AI to be a force for good! Something like to mark agentic actions would also be great.

Claude intelligence (cowork) is far better anti gravity.... Anthropic is already won...

Is there a cost benefit analysis? Gullible people are exploited. Another big ponzi scheme!!

The data loop one is the most underrated — most teams ship a thin wrapper around an LLM and call it a moat. Compounding usage > clever prompts, every time 👌

No it didn’t

Bring back the viva.

I think Anthropic and OpenAI in trouble... 😄

That headline is doing work the study never asked for. The MIT “Your Brain on ChatGPT” study put 54 people into three groups: writing with ChatGPT, a search engine, or nothing but their own head. EEG showed the ChatGPT group had the weakest brain connectivity and remembered less. That is not brain damage. That is reduced engagement, the same thing that happens any time you hand the thinking to something else. A calculator never hurt anyone’s arithmetic. Never doing arithmetic does. The tool is not the problem. Outsourcing your judgment to it is, and that has been true since the first kid copied homework on the bus. The real takeaway holds: use AI instead of thinking and you learn less. But “hurts your brain in 10 minutes” was built for a thumbs up, not the truth. Read the study, not the caption.

Google antigravity it was a garbage for real life coding and now is a fast garbage. They passed all trust me bro benchmarks but for real life coding any open source Chinese model is way better.

I appreciate your perspective. To clarify, AI what I meant by navigating the real world is survival of AI does not rely on the ecosystem, events, actions, or laws that define the human experience. AI can compile data to guide real world experiences of machines (surgery, vehicles, weapons, etc.) and humans (voice assistants, GPS, algorithms, etc.); however the AI is built by, trained on, and continually relies on humans in a variety of ways. Humans are not dependent on AI. AI would be nothing without humans. This dynamic could also be described as a matter of originality vs. simulation.

Another reminder that innovation without human dignity eventually becomes extraction. Pope Leo XIV’s insistence on ethics, labor, and moral responsibility puts the conversation exactly where it belongs: not “Can we build it?” but “Who does it serve, and at what human cost?” In an era racing toward automation, that is a necessary voice.

Since this showed up in my feed, I’ll call out its b.s. … “Turns your laptop into a full AI software company.” — This is what’s wrong with LinkedIn posts! Why do people feel it necessary to put exaggerated nonsense in their posts? In our new world of AI, LinkedIn should do a better job of preventing posts that spread non-factual misinformation like this garbage. You should be ashamed of yourself for posting misinformation for the sake of hype. Truly a disgusting tactic, and says a lot about the type of person you are.

Let's take a look at an interesting real example: https://www.linkedin.com/posts/panagiotis-gioannis-3b8605186_i-knew-my-writing-students-were-using-ai-share-7459634731127558144-6WwY & https://www.linkedin.com/posts/panagiotis-gioannis-3b8605186_dont-let-your-students-use-ai-as-a-ghostwriter-share-7455500974082818048-XL7W [Don’t let your students use AI as a ghostwriter]

Pascaline Amuzu

hilarious!

Sheshadri Bhattacharyya I’m rooting for Google too. The vision is right, AI orchestration is clearly the future. But execution still matters. Right now, a lot of developers care less about “93 agents in parallel” and more about reliability, output quality, and cost efficiency. That’s where Claude and ChatGPT still feel ahead for serious coding workflows and deeper reasoning tasks. That said, Google has something almost nobody else has: world-class talent, infrastructure, distribution, and control across the entire AI stack. If they can align product quality with that advantage, they could become extremely hard to beat. Competition here is good for everyone building with AI.

Milind Gune That’s the bigger shift here. The real breakthrough isn’t just coding faster, it’s compressing enterprise-grade capability into consumer hardware. Once powerful local AI models can run efficiently on standard laptops, the barrier to innovation drops dramatically. A single person with a laptop could soon access capabilities that previously required an entire engineering department and massive cloud infrastructure. That changes who gets to build.

Shiza Akif That’s the real paradigm shift. We’re moving from “writing every line yourself” to architecting systems where multiple agents collaborate effectively. In many ways, prompt design, context management, task decomposition, and workflow orchestration are becoming the new software engineering fundamentals. The developers who thrive won’t necessarily be the fastest coders, but the best coordinators of intelligence.

Oomkar S. This has been a common sentiment from many early users. The vision was exciting, but the developer experience felt fragmented. In AI tooling, raw model capability alone isn’t enough anymore. Developers care deeply about onboarding, reliability, observability, pricing transparency, documentation, and workflow integration. If those pieces break, even strong models become frustrating to use. Google absolutely has the infrastructure and talent to fix this though. If they can combine their model scale with a truly polished developer experience, they’ll become a very serious force in AI engineering workflows.

Keanu Dedenbach The abstraction layer keeps moving higher. First we managed hardware, then software frameworks, then cloud infrastructure. Now we’re managing intelligence itself, deciding goals, context, constraints, and coordination between agents. The speed of the shift is what surprised everyone. What felt experimental 12 months ago is rapidly becoming a new operating model for building products.