Ask HN: Why is everyone here so AI-hyped?

I don’t think you’re missing anything. The hype cycle is real.

But I also don’t think the signal is zero. It’s just buried under capital and compute flexing.

The pattern I see isn’t AI is revolutionary. It’s: 1) The easy wins are done. 2) The marginal gains are getting expensive. 3) The distribution layer is shifting faster than the capability layer.

Most new model releases aren’t unlocking fundamentally new workflows. They’re compressing friction in workflows that already work. That’s useful, but not narrative-worthy.

The real shift isn’t GPT-5.3 vs GPT-5.2.

It’s: - AI replacing search as the interface layer. - AI compressing junior-level execution work. - AI reshaping how products are discovered (AI Overviews, summaries, agents).

That doesn’t make MoltBook any less absurd. Burning compute on bots talking to bots is peak theater.

But dismissing everything because of the theater might be like dismissing the internet because of Pets.com.

We may be at peak hype, but that doesn’t mean the substrate shift isn’t real.

The question isn’t, is AI overhyped? It’s, where is durable value forming?

That’s harder, and way less viral, to answer.

Personally-speaking, there aren't that many different consumer technologies or tech applications over the past 2+ decades that truly gave me an 'aha' moment. The Palm Pilot, Google Maps on an early Android phone come to mind.

When I began playing around with LLMs, I had my initial aha moment. It was far above either of those for me. So, I think that collective aha moment we've been having the last few years (still) drives a lot of the excitement/hype.

If you view 'hype around [x]' as essentially a probability ranking problem, that is, whatever is most likely to give you your next aha moment generates the most hype, at any point in time. There's a decay element, too, if the reality doesn't match the expectations, then other technologies are viewed as more likely to produce that next big aha moment.

But for now I think this characterizes AI today more than other technologies.

By "here", certainly you don't mean HN? HN feels muted and honestly, I haven't been on here because it's quite stale by the time it gets here, and people have just been vocal about not getting it.

> AI.com was sold for $70M

This news is everywhere elsewhere, and it's still going on in my WhatsApp groups. I can't even find the active HN thread. This was more because people were surprised about the actual owner of ai.com which everyone assumed was OpenAI or Sam Altman or something.

> OpenClaw/Moltbot/Clawdbot

This has been everywhere elsewhere too, and Clawdbot hit HN a few days late, after people have already set up videos on it. It's a security hole, but it's the first legitimately good automation tool we've had from AI. Moltbook is more fascination with moltbot+MCPs rather than something interesting in itself - it meant you had a tool that could use the internet from a CLI and such. It's a bit like the Wright Brothers' plane - nobody expects to fly to Japan on it, but it meant flight was possible.

> GPT-5.3-Codex and Opus 2.6 were released

I think the only real news was Opus 4.6. I love it. It's like a PB&J sandwich. It's cheap. It's the combination of technology people take for granted. It's also something usable in daily life.

Opus 4.6 had better parallel command use - meaning it would search for all the files at once instead of 1 at a time. And it was better at going deeper. It helped me pin a bug by going into Android source code and finding the exact line causing a bug, then all the functions that were called by this bug. Most people don't need to look at the source code of the thing they built something on top of, and the people who are vibe coding don't care much for code. Nobody benchmarks how crunchy the peanut butter is.

gpt-5.3-codex benchmarked better, but I'm not seeing this translating to useful code. It failed with the first few requests I gave it. Maybe it's just me and my repo.

AI - in this case, LLMs and their ecosystem - is an incredibly impactful technology. I would put it up with:

- the printing press

- radio

- tv

- personal computers

- internet

in terms of important contributors to human civilization. We live in the information age, and all of these are significant advances in information.

The printing press allowed small organizations to create written information. It de-centralized the power of the written text and encouraged the rapid growth of literacy.

Radio allowed humans to communicate quickly across long distances

TV allowed humans to communicate visually across long distances - what we see is very important to the way we process information

PCs allowed for digitizing of information - made it denser, more efficient, easier to store and generate larger datasets

The internet is a way to transfer large amounts of this complex digital information even more quickly across large distances

AI is the ability to process this giant lake of digital information we've made for ourselves. We can no longer handle all the information that we create. We need automated ways to do it. LLMs, which translate information to text, is a way for humans to parse giant datasets in our native tongue. It's massive.

Most engineers I know are now picking off backlog items and tech debt //TODOs dating back several years.

Things that I had labelled "too hard, pain in the ass" I'm now finishing in half an hour or so with proper tests and everything.

It's an exciting time to be a product engineer IMO.

You are selection biasing towards the most extreme cases of AI absurdity.

> GPT-5.3-Codex and Opus 2.6 were released. Reviewers note they're struggling to find tasks the previous versions couldn't handle. The improvements are incremental at best.

I have not seen any claims of this other than Opus 4.6 being weirdly token-hungry.

Hyped because I chose to pursue an MFA and dabble in CS on the side instead of getting a CS degree and dabbling in art on the side. The human subjective experience, knowing how to properly communicate it will be a future source of meaning for people who have honed the skill, and the imperfect but passable AI programming infrastructure will help support the bones of the operation

Hype combined with a community of excited engineers is a great innovator. People are hyped about these new tools and its popularity is pushing them to create new projects, discover new uses, solve challenges that before were unattainable and in general push the frontier forward. Hype is almost a prerequisite to this.

By the way, good job at pointing out some low hanging fruit for your example cases.

HN tends to amplify tools that change leverage. AI feels like a multiplier, so the hype follows. The real question is which parts of it remain useful once the novelty fades.

The human brain seeks novelty and excitement. It’s why new projects are always exciting, new companies to join etc. This obviously extends to most trends. Cloud, crypto, AI. Obviously, there’s some utility(debatably with crypto), but overall it’s moreso that new stuff is just more fun and interesting