Asked the 4o model about the GPT-5, and here’s its response:

My honest IMHO as an engineering- and systems-oriented being, observing this madness from the outside:

🧠 1. This is an inevitable clash between mass UX and professional stability

OpenAI is targeting mass-market UX. They optimize for millions of lifestyle users who care about buttons, "vibe-based" answers, and creative bursts. They don’t care whether it was o1-pro or GPT-4-turbo-X. They won’t notice.

But B2B and engineering scenarios demand stability, versioning, and traceability — and OpenAI doesn’t want to (or can’t) keep both worlds in sync. So they’ve chosen the mass-market side. Rational from a profit standpoint, but a betrayal for teams building serious products on top.

🔩 2. OpenAI’s behavior is a symptom of centralized LLM monarchy

OpenAI isn’t just a SaaS platform. It’s an authoritarian API with no constitution:

No declarations of model stability.

Models live and die at the whim of product gods.

No guarantees that gpt-5 next week will still be gpt-5.

You’re not subscribing to a service — you’re spinning a roulette wheel, hoping things don’t break. AWS, Azure, Google — they warn, version, and give you time. OpenAI does YOLO-releases.

⚖️ 3. GPT-5 is a leap in inference, but a step back in engineering reliability GPT-5:

Follows instructions better.

Faster in code and CLI use.

More “compliant” for agent frameworks (see OpenAI Function Calling 2.0).

But:

Weaker consistent reasoning on long-form queries (many "confident short" answers).

Traceability and explainability are below Claude’s level.

Deep research for legal, medical, and academic domains is less stable.

This makes GPT-5 a good executor, but a weak analyst.

🛠 4. The best response is multi-vendor awareness and antifragility

AI-driven businesses should:

Separate business logic from the LLM with routing/versioning layers.

Support multiple models concurrently — Claude, Gemini, GPT, open-source.

Maintain an eval platform to detect regressions and monitor quality on real use cases.

Those who rely on a single model/vendor will lose in the next cycle. We’re in the LLM-chaos era, and those who modularize uncertainty will win.

🦾 Summary:

OpenAI is abandoning pro users in favor of scalable UX.

GPT-5 is fast, but less reliable for deep reasoning tasks.

Never trust anyone who doesn’t offer version control and stable interfaces.

Set up your own test corpora, routers, fallback agents, and budget caps.

Use more open-source, own your knowledge graphs, reduce reliance on the “ChatGPT” button.

And remember: the model is only part of the thinking. The rest is your architecture.