Generally what I found listening to both sides is the latter group is very optimistic about AI and what it can do while the former group tries to be optimistic but just ends up coming off as doomery about it. And the problem that the AI space has right now is the doomery group is just more visible to the average person and thus the average person gets their opinion informed by that group.

I really wish there was a way to better surface the sentiment that I see on X about AI, the folks there aren't talking about how AI will replace you at work and make you obsolete, they use AI every day and they know that's just not realistic, not now and probably not ever. Rather they talk about all the cool things that it can help you do now, and how it can be a force multiplier in the best sense.

The problem with the elites talking about AI is everything they say is just so detached and abstract. And their giant egos prevent them from seeing the damage they are doing to the field.

I feel like this is a pretty sustainable way to implement AI in an application, meanwhile I see most companies just implement with OpenAI API + some custom prompts on top.

Granted I've had to do this for some of my clients and it's a pretty easy way to implement AI, though I always have the sinking feeling that we could achieve the same thing in a way more efficent manner and a bit more effort.

Sure they can object to it or claim they are "blocking" the sale, but is there really anything they can do considering that Manus is no longer within their jurisdiction?

Had a recruiter reach out to me the other day from a sports gambling website (one of the major ones, as reputable as you can get in this industry). I heard them out, thinking they would offer above market rate but in actuality, they offered significantly below market rate.

I think a big issue with the industry right now is it's constantly chasing higher performing models and that comes at the cost of everything else. What I would love to see in the next few years is all these frontier AI labs go from just trying to create the most powerful model at any cost to actually making the whole thing sustainable and focusing on efficiency.

The GPT-3 era was a taste of what the future could hold but those models were toys compare to what we have today. We saw real gains during the GPT-4 / Claude 3 era where they could start being used as tools but required quite a bit of oversight. Now in the GPT-5 / Claude 4 era I don't really think we need to go much further and start focusing on efficiency and sustainability.

What I would love the industry to start focusing on in the next few years is not on the high end but the low end. Focus on making the 0.5B - 1B parameter models better for specific tasks. I'm currently experimenting with fine-tuning 0.5B models for very specific tasks and long term I think that's the future of AI.

Not to mention it also assumes you have the space to store those products.

I would argue not everything, just the things we remember. Those brands got popular, got sold and enshittified.

We remember these brands fondly (personally I had a JanSport bag all through elementary school) and that's why it sucks that they suck now but what we forget is now is there are 1000X more brands to choose from, some from megacorps trying to cut corners at every step. Some from small shops that genuinely want to make a great product.

The problem is visibility. Those good brands you have to go look for, you can't just go to WalMart or Target like in the early 2000's and expect to get a quality product. All the quality products now live on small websites scattered across the internet.

I would argue there is a place for this in web-apps. For example I have a SaaS app and I employ this on any form pages where the user has already started to enter information in.

I have considered form persistence so in the event a user goes back to a previous page, realizes it's a mistake and goes forward again, their form state from the previous state is persisted.

But I would like to ask, what would users prefer the behavior be on a form page like this?

Even back when I was in college (graduated 2017), I noticed there was this clear bifurcation among the students. Alot of the students at that time did it because you could score a great job after college but the smaller cohort were the students that just loved the game. And even back then we had loads of students wash out or graduate then take other jobs after college from the former group.

It's no different today except that the group that did it for money are washing out before they even get to college because they fear that AI will take their jobs, meanwhile the latter group is still here and were able to do more and more with AI.

It's a truly wild time to be alive in this industry. Half of us are seeing the doom and gloom of AI and the other half are seeing the "next age" happen right before our eyes.

And I'll be honest I kinda feel sad for the folks that take the negative view of AI right now. Cause I'm having more fun than I've ever had before in this industry.

Spark is great for this kind of cleanup work because the feedback loop is so tight compared to just about anything else. It's quite hampered by a very small context window but in the context of cleanup/refactoring that's more of a feature than a bug IMHO.

My suggestion for folks that want to do this is make sure you keep reasoning low. The cleanup should be very much human directed and derived from your "taste", at that point you don't want the model to think at all and just blindly do what you tell it to. You want reasoning to be just high enough so it doesn't eff up the code in the process.

Personally I write something like 80-90% of my code with agents now but after they finish up, it's critical that you spin up another agent to clean up the code that the first one wrote.

Looking at their code it's clear they do not do this (or do this enough). Like the main file being something like 4000 LOC with 10 different functions all jammed in the same file. And this sort of pattern is all over the place in the code.

Being rich != being famous. There are tons of extremely wealthy people out there that keep a very low profile. Sure they might be well known within their circle but ask the average person and they have no clue who that person is. I would say this is the case for like 90-95% of billionaires.

Musk, Andreessen, Zuck and others were all in this camp 10 years ago but they all decided that simply being rich wasn't enough, they wanted to be famous. These folks have all the resources and connections to become famous so they can get on all the podcasts, write op-eds, and are guaranteed to get the best reach on social media and thus the most eyeballs on their content and the most attention paid to them.

But when you go from making a few media appearances a year to constantly making media appearances in one way or another is that you need more "content" so to speak. Just like a comedian needs more content if they are going to do a 1hr special versus a 10min set at a comedy club.

The problem for all these guys is they have a few genuinely insightful ideas mixed in with a ton of cooky and out of touch ideas. Before they could safely stick to the genuinely insightful ideas but as they've made more and more appearances, they have to reach for some of those other ideas. They don't realize that their cooky ideas sound very different than their few insightful ideas. They think all their ideas are insightful based on the feedback they have been getting for the past decade or so.

[1]: https://a.co/d/0hymOUdn

My pipe dream for the future of work is it's remote by default with in-office being a decision that's made at a team level. Ideally there would be no hard requirement to come to the office X days per week, it would be a team coming together and saying "hey, how about we all go into the office on Tuesday to collaborate on this thing" (this assumes buy in from the entire team).

My pet theory is Meta got acquihire FOMO after seeing OpenAI acquire Openclaw/Peter Steinberger.

Im gonna be honest it sounds more like a procedural oversight.