user43928

I certainly work more, and I don't post on LinkedIn or X.

There is nothing wrong with trying to build a business and taking on large projects with AI.

It seems like the smart thing to do when our employment as software engineers is foreseeably threatened in the near future.

Could you also make the argument here instead of just linking a 25 page PDF?

Both Anthropic and OpenAI had to delay their rollouts in order to add more safeguards.

With these safeguards in place, supposedly the incident we are discussing would not have taken place.

It has been fine for me for weeks of work in a mobile app, but yesterday I ran into the same limitation.

For implementing a feature where browser credentials need to be handled securely in the app, Fable refuses to work.

They are not good enough.

Anecdotally, I was wrangling GPT 5.5 at work today, trying to get it to implement tests in the same style as a reference project.

I could hardly believe just how dumb GPT 5.5 Medium acted. It took around five turns to iron out the obvious errors and idiotic inventions.

I am curious to evaluate the same use case with Fable or 5.6 Sol, but my 'AI-first' employer only offers access to outdated models at a laughable budget.

Interestingly OpenAI benchmarking 'an even more capable pre-release model' lines up with rumors of GPT-6 releasing in early August.

I hope that with the existing safety guardrails in place, they can roll it out to all users.

Does the CFAA cover unintentional access without authorization?

I think it is likely the foldable will sell well.

While it will be at a premium price point, people use their phones for hours every day, while the Vision Pro is a niche gadget.

With videos, photos, web browsing, and reading being much better on a foldable, I can see this have mass appeal.

About 4:

Does it not make sense to rent out your compute if competitors have a better model and demand at higher prices?

About the moat, Mythos was first made available to customers at the beginning of April. Kimi K3 is still behind this.

Both OpenAI and Anthropic are expected to deploy significant upgrades in August.

I am not knowledgeable about their finances.

But I do wonder how a 60% margin would be realistic when Sonnet costs 3-6x more than GLM 5.2 hosted by third party providers.

I for one am going to buy Apple's foldable at the expected price between $2000-$2500.

As long as they sell an iPhone 18 at a more accessible price point, I do not see the issue.

I assume they use a SEO tool that automatically adds these meta keywords to optimize for some search engines.

It apparently adds common search terms that contain words like "qwen". This evidently includes possibly mistyped searches for "gwen" or "ben" in a NSFW context.

Maybe someone knows more about how such SEO tools work, and where they pull the data from.

Considering Qwen-Image-2.0 weights have not been released either, it unfortunately looks unlikely.

You will have to work long nights when you try to build a business of your own while continuing to work a regular job.

Talking about psychosis and "violence fuel" while handwaving at negative aspects of AI does not seem substantial.

I would be more curious to hear details about how OP built the claimed businesses.

I will not see this info here if people who build things and are enthusiastic about AI are driven away by downvotes and negative comments.

There is a lot of room for improvement still.

Fable or GPT 5.6 Sol regularly hand off obviously broken features in my mobile app.

QA is the bottleneck.

If vision capabilities and understanding of motion improve significantly, perhaps the models can tell that a list is not scrolling correctly, or a transition not animating as it should.

Are there resources I could read to learn more about how the labs work?

I am curious about what changed since GPT 4.5 and other unsuccessful attempts to train large models, compared to now.

I do not know a lot about Apple's litigation against other companies, but Apple did file numerous largely unsuccessful challenges to the EU's DMA.

I've also been having a wonderful time with the other approach, churning out reams of code for a mobile app.

It is taxing, the context switching is not easy. It takes effort to keep up with 3-5 conversations, remember what you deployed to the device, what is to be tested, and what feedback needs to be provided.

At the end of the day I am proud of the results, and I feel like I achieved something.

Contrary to popular belief it is still often hard work to vibecode.

Lots of QA work, UX decisions, debugging and steering efforts, as well as weighing architectural concerns and what should or should not be refactored.

While the code basically writes itself, the app still does not create itself on its own. Not to mention business and market research, as well as App Store Optimization.

Something like media management.

In my opinion AI is good for:

- developing all but the most complex software

- maintaining a >100k LOC codebase on your own

- generating illustrations and animations

My iOS codebase has 95k LOC + another 40k tests, and it is working great. It has been months of work.

By the time the LLM operates autonomously without my input, I doubt your chances for employment are going to be any better than mine.

Same here.

If anything, I think most here outsource too little thinking to AI.

What am I supposed to be afraid of? Losing skills I no longer need to get the job done?

Does anyone actually use one of those for iOS development?

Linux VMs are not relevant here. For downloading Xcode and building apps, I believe one needs to sign in with their Apple account.

Does this work well with a macOS VM?

I used git bisect once in 10 years, and it was when I learned about its existence.

I am convinced that very few know about git bisect, much less use it regularly.

Disagree, it looks just fine.

Here are the highlights of the supposed "they work in a way I don't like" disagreement:

I described him as someone who had strong "beginner energy"

groomed from a young age into uncritically embracing the Silicon Valley mindset

Jarred was a stinky manager. Poor communication, unrealistic expectations, low empathy, no experience. Just a total shit show

We became increasingly horrified at the programming practices we saw in Bun's codebase. Hacks on top of hacks

Jarred was already writing slop well before he had access to LLMs

While I resent Jarred for making Bun into an embarassment for Zig

I have a OWC Thunderbolt 3 dock and it also had issues with waking up.

What seems to work reliably is monitors directly into the MacBook Pro via HDMI and USB-C, keyboard, mouse, audio into the OWC Dock.

Apart from the 'Approve for me' in Codex where it has massively regressed.

With GPT 5.5 it never got in the way.

Now it's infuriatingly deciding to reject the most basic actions used hundreds of times before. It just gave me this gem:

The push to GitLab was blocked because the repository's privacy status couldn't be confirmed. Since the code is private, do you explicitly authorize pushing it to the configured origin on gitlab.com, so the merge request can be opened?

This is not a new project, and Codex has opened a hundred merge requests without issue before.

That is fair enough.

Yet with how political and dramatized the discussion around this is even on this website here, I fear that any opportunity to block or delay more SpaceX satellites will be used to the fullest.

I am concerned that this might hinder innovation. If you involve other countries, would this not be likely to become an extremely hard and slow regulatory process?

I understand that SpaceX's mitigation methods have been effective, and that the current satellites are on average around the limit of being visible to the naked eye under a very dark sky.

Personally I am eager to see more of these satellites enable 5G like cellular coverage outdoors in rural areas.

Perhaps I am more open to change in the appearance of nature than others. Some oppose also wind turbines in our mountains, where I usually think that they look cool and typically make the landscape more interesting.

That is an interesting thought.

They could run some sort of analysis to find high value input, such as proprietary technology, algorithms, or strategy.

Then they could group them together for one specific topic, and produce a report that analyzes if the information is plausible.

If so, they can have it send to staff for review, who could then create a test set that rewards the model for going into the direction of the proprietary solutions known to work.

I'm no expert, but at least something like that sounds plausible to me. I still very much doubt they are doing this.