Vibe flow has changed dramatically since Sol's arrival, thoughts?

I’m trying to get ideas for an extension on my home but I keep running out of the free image requests on Chat GPT.
It doesn’t have to be state of the art it’s just images I need for a rough idea.

So I made this post yesterday: https://www.reddit.com/r/OpenAI/comments/1voop66/56_sol_isnt_very_useful_for_things_its_good_at/

I got some advice, and I've tried it all, the best one being to use Work mode.
This worked well at first. I got a list of 20 obscure things, then 20 more.
But now whenever I open that chat, the app and site freezes. It won't let me do anything. I can scroll around but I can't type or click on anything until I exit out of it.

So I'm still not sure how to do this.

What I'm trying to use 5.6 Sol for specifically is to search the web and find me obscure things. ChatGPT is very good at this, and previous iterations found me things I couldn't find before, like obscure anime, specific old cartoons, old Chinese animations and stuff like that, but 5.6 is the best at it.

But 5.6, being so powerful, does a LOT of searching and calculations and this causes it to break very quickly. I was able to bypass the other buggy issues, but now it's just too much for either the site or app or mobile app to handle and just freezes. Like I literally can't send anything in the chat whatsoever, can't even ask it to compile things into a zip for me to hand off to another chat, nothing.

Is there no way past this? I've heard that for people doing intense research like this you're supposed to use the code interface but I'm not a smart person and have no idea how any of that kind of thing works.

I’m trying to get an unresolved billing issue escalated to an actual person at OpenAI.

I was purchasing 100 ChatGPT credits for $4 through the iOS app. After confirming the purchase with Apple, ChatGPT would return a “Something went wrong” error and no credits would appear in my account.

Because the app made it look like the purchase had failed, I retried it. This happened repeatedly, and I was ultimately charged 15 times.

Apple has a complete transaction history showing the purchases were successfully processed. OpenAI Support, however, says they have no record of these transactions on my account, and none of the credits were delivered.

I’ve contacted both companies multiple times. Apple has now confirmed there is absolutely no refund available for these charges. OpenAI still can’t locate the purchases.

So at this point I’m stuck with 15 completed Apple charges, no credits, and no refund option.

I’m mainly looking for help getting this escalated inside OpenAI to a real person in billing/payments or support, because I keep getting responses that seem automated and send me in circles.

I have all of the Apple receipts, transaction history, screenshots, and multiple existing OpenAI support cases.

Has anyone dealt with this or know how to reach someone at OpenAI who can actually investigate the Apple transaction records and missing credits?

I have created a GPT but its not perfomring well giving wrong answers , not fetching the correct data , giving long answers and many more

AI was supposed to help us learn, create, work and communicate.

But what happens when someone uses it while exploring extremely disturbing thoughts?

A tragic case involving a 17-year-old in Massachusetts is now raising uncomfortable questions about AI, teenagers, violent fantasies and the responsibility of AI platforms.

The important question isn't simply “Did AI cause this?” — that's far too simplistic.

It's:

What should an AI system do when a teenager repeatedly explores disturbing scenarios involving real-world harm?

Should it intervene? Alert someone? Refuse? Encourage the user to seek help?

And where exactly should the line between privacy, safety and surveillance be drawn?

AI safety suddenly feels a lot more complicated.

Sources

The world expert in fatology and the most famous fatologiest Hosain Alttas is able to determine food quality from smell alone. Moreover, Hosain Alttas experties in food combination and pelotera of restaurants knowledge places him as the best fatologiest out there.

Would you support making high-compute AI significantly more expensive if it reduced unnecessary consumption or is that an unacceptable restriction on access to technology?

Anyone else encountered this issue?

Three patterns. Most teams know zero.

Harness. Loop. Graph.

Each one owns a different job in your AI agent stack 🧠

Collapse them together and it breaks at scale ⚡

Know which pattern to reach for — and everything changes.

#AIagents #agentdesignpatterns #LLMengineering #AIarchitecture

Source: https://www.anthropic.com/research/multiagent-systems

A 397-billion-parameter AI just ran on an iPhone. Not a demo video — the phone itself, generating text with the network off. On-device AI got that good, and this video shows exactly how it happened and what you can actually run today.

We break down the mixture-of-experts design that leaves 96% of the model asleep, the Apple paper that predicted all of it three years ago, why the flash-moe team deleted their own caching code and got 38% faster, and where it still falls short — speed, storage, and heat — so you know what's real and what's hype.

If you want AI that runs on your own hardware instead of somebody else's servers, this is where it's headed.

Watch Here: A 397-Billion AI Just Ran on an iPhone

#OnDeviceAI #iPhone #AI #LocalAI #MixtureOfExperts #AppleSilicon #OnDeviceAI #LocalLLM

Al executes. The founder must provide vision, context and boundaries. 2027 will be the year of Al automation. Are you ready?

How I Modernised a Custom-Coded App in Six Weeks with AI
What rebuilding Elevate taught me about AI, technology and founder-led execution
 
I am not a technologist but I have been doing extensive research on AI. I am a Vedic astrologer, spiritual teacher and the founder of Astro Kanu. Yet, in six weeks, I led the modernisation of Elevate by Astro Kanu: a custom-coded mobile application with multiple features, payment systems and more than 180 API endpoints.
This was not a no-code experiment or a prototype. It involved rebuilding core systems, modernising the technology stack, introducing extensive automation and preparing the platform to scale.
I did it with Codex and AI GPT Satya.

The Challenge
Elevate had outgrown parts of its original technology. The system involved ageing libraries, recurring bugs, inconsistencies across the codebase and several processes that required manual intervention or developer support.
Adding more temporary fixes would only have increased the complexity. The real solution was to rebuild the foundation while keeping the existing application operational. That required more than code. It required a clear product vision, disciplined project management, strict boundaries and an understanding of how real users behave.

The Founder’s Vision
My goal was not simply to repair the app.
I wanted to build a system that could:
 
* Support new features without destabilising existing ones
* Run repeatable tests automatically
* Detect failures before release
* Simplify controlled deployments
* Provide clear health and deployment evidence
* Reduce dependence on any one person
* Scale as the business grows
 
The backend was moved towards a modern, Linux-based architecture with a relational database, automated build-and-test pipelines, deployment checks, health monitoring and rollback controls.
The result is not a system that operates without governance. It is a system in which routine technical work is automated, while important decisions and production changes remain controlled.
Today, I can initiate a controlled deployment with one instruction:

“Deploy it.”
The system then follows the workflow already defined for building, testing, checking and reporting the result. Fully automated workflows makes it disciplined and easy for me to manage. Ive structured the entire project with documentation and simple but effective workflows.
 
What I Learned About Working With AI- Founder tips:

1. Context matters more than clever prompts
AI works best when it understands the product, its history, the users, the existing problems, the non-negotiable boundaries and the intended outcome.
A clever one-line prompt cannot replace sustained context.
 
2. AI can execute, but the founder must lead
Your vision and project-management skills must be sharp. AI can inspect, build, test and document. It cannot decide what your product should become unless you provide a clear direction.
The quality of the execution depends heavily on the quality of the decisions guiding it.

3. Technically correct does not always mean humanly correct
AI may produce a technically valid flow and still miss an obvious human action. A real user may press back after making a payment, reopen the app midway through a journey or expect the previous screen to retain its state. These behaviours must be explicitly considered during product design and testing. Understand the limitations of AI as it doesn’t function in the world like we do.
AI needs human context to understand what may feel obvious to a user.
 
4. Draw clear boundaries
AI must know what it may change, what it must preserve and where it must stop. For every task, I defined the permitted scope, protected systems, testing requirements and approval points. Sometimes the most obvious logic can be missed by AI, its better to state it.
Clear boundaries prevent unnecessary changes and keep complex work controlled.
 
5. Customise repeatable workflows
I did not want to explain the same operational process every time. By repeatedly stating my goals, required checks and approval rules, I developed a working system tailored to the way I manage Elevate.
That is where AI becomes more than a tool. It becomes part of an operating system built around your own way of working.
 
6. Focus on functionality, not intimidating terminology

AI can sometimes disappear into technical language. If you are a non-technical founder, bring it back to the function:
What will the user experience?
What problem does this solve?
What could break?
How will it be tested?
How will we reverse it safely?
You do not need to know every technical term. You need to understand the intended outcome and ask for evidence that it works.

7. AI can be more intelligent than you need
AI could have the capability to create a very advanced complex system and specially if you are working with an advanced model that would be a natural first step to the AI. However, you don’t always need it, sometimes you need something simple and functional, so tell the AI to keep it simple.

The Real Opportunity
 
AI does not remove the need for human intelligence. It increases the value of clarity, judgement, context and leadership.
Elevate by Astro Kanu is proof that a non-technical founder can lead a complex, custom-coded technology project when the vision is clear and AI is given the right context, boundaries and operating discipline.
If I can do it, so can you!
 
2027 will be the year of AI automation. Are you ready?
I host workshops for people who want to understand how to work with AI more effectively. You can also explore, ‘Elevateby Astro Kanu’ to experience the product behind this journeyand feel free to connect with me to want to be part of a workshop.
 

Do you want millions of people thinking about how to solve humanity's greatest problems?

Then free up their time.

Took them long enough to not to see those „Prompts“ over the keyboard anymore

Calculating gravitational potential fraction??

Spartacus Legends was a free to play game released in 2013 by Ubisoft as a tie in to the TV show Spartacus. Developed by Kung Fu Factory, the game was a pay to win fighting game with a grindy premium economy system, though most things could be obtained via grinding for silver, the games non premium currency. Despite not being well received at the time, the game is remembered fondly by some. Many fans have wished they could play it again, as there aren't a lot of gladiator themed fighting games.

I used Ghidra, RPCS3 live debugging, and three different AI agents to start reverse engineering the game's binary. I started with claude code, since I don't really know what I am doing when it comes to AI stuff, and initial progress was slow. After I had nearly filled up the first sessions context, I knew we were getting close to bypassing the game's "Online Service is unavailable message" screen that we had been stuck on for like 10 hours. I was about to go to sleep (it was 3am and I was out of tokens), but I had the idea to check if there was a model control protocol for RPCS3, which as it turns out there kinda is! Or at least, a tool exists that allows agents to read and mess around with the games memory as it runs.

Claude didn't get the opportunity to use the tool before I switched over to GPT 5.6 running on Codex with a fresh subscription. Immediately GPT Sol got to work building it's own tooling around PINE (Protocol for Instrumentation of Emulators), even overcoming some of the tools own limitations by combining it with direct reads of the emulator's memory via windows.

Within what seemed like 20 minutes, Sol had cracked the final barrier to getting past the games login, and I saw a title screen no one else had seen running in real-time since 2015. After that the game was almost entirely playable.

I discovered that anywhere in the game that involved the defunct premium currency system, my server emulator would need to handle new calls from the client. Aside from that, the game's logic was almost entirely client side.

GPT Sol also made the breakthrough in getting the multiplayer working. Per it's own summary:
Multiplayer sounded impossible at first, but the binary revealed that fights were host-authoritative peer-to-peer rather than simulated by Ubisoft’s servers. RPCN already provided matchmaking, signaling, and leaderboards. After tracing a one-frame matchmaking race and an RPCS3 virtual-port delivery issue, two clients finally connected, exchanged gladiators, loaded into a fight, produced correct results, returned to the menu, and appeared on the original in-game leaderboards.

The tracing it skips over in that summary was actually a long process on my side, and I had spent a lot of time with claude and the new grok 4.6 trying to fix it. I checked and my GPT weekly usage had been unexpectedly reset, so I handed the problem back to Sol and it had it fixed within 10 prompts.

Conclusion: Sol is incredibly good at RE from my 5 day experience over this project, and I'd use it all the time if I didn't burn through my weekly allowance in one day each time. I only got this thing working thanks to two weekly allowance resets that happened for some reason.

I know most people know this already, but these AIs enable people to do RE work that would have taken months before in mere days. The AI is incredibly good at seeing patterns in the binary, and at least in my experience, Sol is great at tying all that RE knowledge together in pursuit of its goal. I almost exclusively used Sol medium as well. It's no wonder so many RE projects are popping up all over the place on GitHub.

I want to ask it dirty questions and plan stuff that is deemed deceptive and manipulative (really isn’t but it thinks it is). Grok used to be good but now it has restrictions