What a weird thing to suggest. This model is worse than some Chinese models from last year, which were already worse than frontier models from last year.
This looks like a worse Deepseek V4 pro. Costs more, dumber, slower and more verbose than most modern Chinese releases.
Seeing how those Chinese releases are in various states of open source, I would hope a competitor could at least match them.
Really cool experiment. A lot of jank. It would sometimes rubber band me back, movement was grid aligned in a way that made accessing the secret room challenging, and the whole tab unexpectedly crashed with no error. 5 star would play again
It's not fun to spend an hour going zig zag against the wind? What about an hour doing it with a boat full of precious materials that can't go through the portal while you're being chased by some ungodly horror from beneath the waves?
In your example, those projects were not the domain of engineering. Your friends couldn't afford expertise and those projects never would have been made before. Therefore, these are net-new projects that replace nothing that came before.
This is common in technology, especially software, that improvements in efficiency make software cheaper and expands the total pool of possible software.
And, even if one of the "one button shipping" platforms (and there are many) was hooked into the agent, your friends will hit major problems that they and their AI cannot solve. Whether its tech-debt hell, a major security breach, or something else, any sufficiently complex project will require expertise. Will be a fun day when a European regulator asks a friend about their GDPR compliance and their agent is like "shrug"
This is a non-answer, and in fact, a statement like "don't let fear be an excuse to lose rigor in thinking" in response to my question "how verifiable are their claims" is insulting and sloppy. Rigor in thinking includes human discussion and humans asking questions, but yet you shot that down.
ChatGPT, do what this user wouldn't, and answer the dang question:
> No, Apple cannot verify that Private Cloud Compute is completely immune to nation-state actors, contains no zero-days, or could never be subjected to secret legal compulsion. Nobody can honestly establish those absolutes for a complicated, evolving computer system operating across multiple jurisdictions.
> What Apple has done is more meaningful than ordinary corporate “due diligence,” however. PCC is specifically engineered to make clandestine access—whether by hackers, insiders, or governments—technically difficult, difficult to target, and more likely to leave externally detectable evidence...
> Against ordinary attackers, rogue employees, conventional cloud administrators and routine government data requests, PCC appears exceptionally strong for a cloud AI service.
> Against a targeted nation-state willing to combine zero-days, supply-chain compromise, endpoint exploitation, legal pressure and secrecy, the right description is: Highly resistant, deliberately difficult to target, and unusually auditable—but not immune.
Thanks ChatGPT. Don't know why I bother to ask humans anymore, it's StackOverflow the whole way down.
Can they verify the private cloud is completely immune to nationstate actors, has no zero-day vulnerabilities, is completely bulletproof in a court of law and can never be compelled to secretly share info with government(s), etc?
I think the users fear here is real. "We did good due diligence at the consumer level" and "we're completely immune to nationstate hackers and clandestine legal cases" are very different things.
You can do basically the same thing as cloudflare except as a skill you run in your local harness. If you're going through the motions with PRs and are familiar with actions, you can have it run in a github action instead. But this is basically just a skill. The Claude code review skill is a simple version of exactly this.
I've come to realize that folks are including "ai-slop" in their ~public use of AI to intentionally signal to others that they're using AI. To some, that signal results in revulsion. To others, that signal results in approval. In my opinion, the approval signal comes from investors, board members, c-suite, and now management. They want us to use AI? Let's make sure they know we are.
Brother, I don't care who writes the specs as long as they sign the checks on time. And yes, I do care about my work even if upstream is slop. In a relay race, you can lower your performance to weakest leg, or you can be the strongest leg. And maybe I just like to run.
There is no way to facilitate untrained users in the healthcare space to vibe code real applications touching patient data. There is no magic policy, firewall, or "facilitation technique" which can make vibe coded software reliably meet contractual and regulatory obligations with a high degree of security in the healthcare space.
If you care about data privacy, especially your own protected health information, that sentence should give you a lot of comfort.
In a HIPAA environment, people who are sufficiently trained on how to develop regulated software securely are called "software engineers".
In my opinion, agents will replace the majority of the rest of businesses before they are good enough at agentic engineering to be able to autonomously develop software that safely and reliably can manage PHI without a single mistake.
It goes without saying: never trust your PHI to any company who is vibe coding in production.
I actually think "just asking ChatGPT" is fine, because A) the data in these apps is suspect at best and B) the data behind calories is also pretty suspect (but we all play along because we can adjust other variables to make it all "work" well enough).
Once or twice a year I spend a few weeks meticulously measuring ingredients/cooked foods and recording calories and on complex recipes apps are next to useless at getting accurate data. You're trying to input five or ten relevant ingredients, and then weighing your cooked outcome to try and divide the ingredients by proportion. Frankly it's a mess and most people aren't doing it for home cooked meals, and are getting very lossy outcomes (weighing cooked chicken and marking it as raw chicken, etc)
With reasoning and tool calling (combined with me meticulously weighing before and after), it's producing fine data for my purposes.
Feels like a pretty wildly misleading graph. What do they say about lies, damned lies and statistics?
This graph is literally designed to abuse correlation =/= causation by attaching the arbitrary label "microsoft acquires github" so that the reader will apply causation to the uptime.
Now let's overlay ontop of the uptime graph a few lines of: # of monthly active users, # of monthly commits, size of PRs, action minutes per PR (whatever demonstrates scaling)
Something tells me that the uptime issues follow scale more than they do ownership... but that's not the narrative that this chart was designed for...
Are you referring to the one (1) study that showed that when cheaper LLM's auto-generated an AGENTS.md, it performed more poorly than human editted AGENTS.md? https://arxiv.org/abs/2602.11988
I'd love to see other sources that seek to academically understand how LLM's use context, specifically ones using modern frontier models.
My takeaway from these CLAUDE.md/AGENTS.md efforts isn't that agents can't maintain any form of context at all, rather, that bloated CLAUDE.md files filled with data that agents can gather on the spot very quickly are counter-productive.
For information which cannot be gathered on the spot quickly, clearly (to me) context helps improve quality, and in my experience, having AI summarize some key information in a thread and write to a file, and organize that, has been helpful and useful.
Even more than validating ideas, I think my personal AI use falls into two categories:
- Exploration: I am "vibe coding" to explore a domain, add many features, refactor the app over and over, as a real time exploration of the domain to see what works and what doesn't
- Specific Execution: I have a full design, a full idea, I've thought about architecture, we're making a plan and we're executing this extremely coherent vision
Whenever a new one comes out, there's a good chance they're free for a week on Zen, so I try out any free ones. For example, MiniMax M2.5 and Qwen 3.6+ are free right now.
Personally, I've had a lot of good results in my little personal projects with Kimi K2.5, GLM 5 and 5.1, and MiniMax M2.5.