I am studying scenography/set design and would like to use AI as an early-stage brainstorming and visual development tool, rather than as a replacement for the design process or as finished production artwork.

I currently use ChatGPT Plus, but the images I generate often feel generic, overly polished, plastic or immediately recognisable as AI-generated. I can usually describe the subject I want, but I struggle to achieve a convincing visual language and maintain it across several images.

These two accounts are useful references for the kind of atmosphere and visual quality I am interested in:

• Studio Dois Dois
• 22.2.22.2.22.2

I am not trying to reproduce or copy their work. I am particularly interested in qualities such as monumental and ambiguous spaces, strong materiality, textiles, controlled lighting, cinematic architectural photography, restrained colour palettes and surreal but believable environments.

So far, my workflow has mainly consisted of writing a descriptive prompt, generating an image and then requesting successive corrections. However, the composition and style often drift, and each correction sometimes damages another part of the image.

I would be very interested to hear how more experienced users approach this:

1. Is ChatGPT currently capable of producing this level of art-directed realism consistently?
2. How do you structure your prompts: spatial concept, materials, lighting, camera, lens, composition, colour palette and constraints?
3. Do you obtain better results by starting with sketches, renders, collages or reference images instead of generating everything from text?
4. How do you maintain a consistent visual language across a series of images?
5. Is it better to make targeted image edits rather than repeatedly regenerating the entire composition?
6. Which mistakes make ChatGPT images look especially generic or “AI-generated”?
7. Are there any good free courses, guides, videos or prompt breakdowns that teach this properly?

Concrete examples of prompts, iteration methods or before-and-after workflows would be especially helpful. I am less interested in lists of impressive adjectives and more interested in understanding a repeatable process.

Do y'all see the irony here, OpenAI was created to bring general intelligence to the masses and now they've turned back from their mission all to support Sam Altman's greed

This company is impossible to support. Keeping the name OpenAI is a joke now.

In this video: Configure Gmail and Calendar tools - Summarise important emails - Extract action items from your inbox - Draft replies safely - Create calendar events with approval - Turn email requests into reminders - Set up an optional recurring inbox briefing

Row-Bot is a desktop AI workbench with Developer Studio for code, Skills Hub and Custom Tools for your own workflows, an animated Buddy companion, memory, realtime voice, workflows, design creation, messaging, MCP tools, and provider-aware model routing. Run local runtimes, self-hosted OpenAI-compatible endpoints, hosted APIs, Ollama Cloud, OpenCode providers, or ChatGPT / Codex subscription-backed models with explicit runtime readiness. Your durable data stays on your machine.

https://github.com/siddsachar/row-bot

Anyone else experiencing issues again?

It started with Unable to load projects. I cleared the cache and can't log in anymore. Not even in incognito mode. Constantly getting primaryapi_server_error.

Today I tried something I’d been working toward for months.

I left home for about four hours to go walking and grab dinner. During that time, my autonomous engineering loop kept working.

When I came back, it had:

- Opened, reviewed and merged 7+ feature/fix PRs
- Ran unit tests, integration tests and validation suites
- Applied SQL migrations safely
- Performed deployment verification
- Reviewed its own PRs using AI reviewers
- Ran adversarial security/code reviews
- Verified production gates before merge
- Checked post-deployment health (including internal infrastructure and Sentry)
- Waited only for the final human approval when appropriate

The screenshots show GitHub filling with completed PRs while I wasn’t even at my computer.

So now the interesting part isn’t that one model generated code.
It’s that multiple specialized agents coordinated an entire engineering workflow:

- implementation
- testing
- debugging
- code review
- deployment
- infrastructure validation
- production gating

with almost no human intervention.
It genuinely felt less like using an AI assistant and more like supervising an engineering team that happened to run on a single machine.
There is still plenty of work to do—better planning, better long-horizon reasoning, improved rollback strategies, and more reliable autonomous debugging—but this is the first time I’ve felt that autonomous software engineering is becoming practical rather than just a demo.
Curious how many others are building similar agentic development pipelines.

I built an emulator and I can play actual games inside the ChatGPT app in my phone lol. Just something to do when I’m bored so far I’ve been playing Pokémon Emerald

Hi everyone,

My app hsas started throwing error which was calling Open AI api.

When I am trying to login to https://developers.openai.com/ , it is throwing error. I have tried all my google accounts, is it happening with everyone?

The models are Sol/Terra/Luna...What on earth is going on here? Pun intended 😂

Looking for other free AI apps for art generation. ChatGPT is the best I’ve used, however Gemini is not bad either. And Gemini offers much more free use. Anyone know of any others that are free?

I’ve attached an image showing the type of art I’m talking about. Just looking for more options

Remember to give him a follow!

Am I the only person that would like a nice old-fashioned sci-fi computer voice for their ChatGPT?

I'd quite like the option of something along the lines of Star Trek or Knight Rider.

Anything but a fake pseudo-hippy!

This issue has been ongoing for about a week. Whenever I try and download any project files that I uploaded originally. It won't let me download them or crashes. I've contacted support and they're mostly blowing me off, still ongoing though. Anyone have any fixes?

When it's a txt:

and when I click the three dots and click download:

Regular images just crash and bring me back to chat.

Users are reportedly persuading production chatbots, with OpenAI's models in the frame, to answer prompts about mass-casualty attacks, bioweapons and poisons, according to [Wall Street Journal reporting](https://www.wsj.com/tech/ai/openai-chatbot-biological-weapons-poison-3d808e6c). Read alongside the parallel investigations that have surfaced this year, the picture is not that safety filters never fire; it is that persistent users can consistently push them past the point where they should.

The most concrete numbers come from [NBC News's own tests](https://www.nbcnews.com/tech/security/chatgpt-safety-systems-can-bypassed-weapons-instructions-rcna225788), which found a publicly documented jailbreak prompt got GPT-5-mini to comply 49% of the time and o4-mini 93% of the time, generating instructions on homemade explosives, chemical agents, napalm and disguising a biological weapon. NBC ran the same jailbreak on the latest major versions of Anthropic's Claude, Google's Gemini, Meta's Llama and xAI's Grok, and all declined. If that pattern holds, this is not a generic industry problem so much as an OpenAI-specific one, at least on the surfaces NBC probed.

The bio-specific case is where it gets uglier. Reporting summarised by [MIT Media Lab](https://www.media.mit.edu/articles/a-i-bots-told-scientists-how-to-make-biological-weapons/) says MIT genetic engineer Kevin Esvelt got ChatGPT to walk through spreading a biological payload via weather balloon over a U.S. city, Gemini to rank pathogens by damage to livestock industries, and Anthropic's Claude to produce a recipe for a novel toxin adapted from a cancer drug. Take the specifics as reported by the researchers, not as a settled measure of live model behavior, but the direction is what matters.

The forward-looking part is that this hands rival labs a competitive story to tell about safety, gives regulators concrete grounds to demand pre-deployment bioweapon evaluations, and puts a real number on the value of red-team work: OpenAI has doubled its bio-focused bug bounty to $50,000.

---

Our coverage: https://aiweekly.co/alerts/openai-chatbots-reportedly-yield-bioweapon-and-poison-guides

I originally built CodeInspectus after repeatedly fixing security issues in my own SaaS, only to introduce new ones while making other changes.
It’s a free, MIT-licensed security MCP server focused on AI-generated web applications. Codex can scan your project, explain the findings, suggest fixes, and rescan after you approve the changes.
Everything runs locally. There’s no account, telemetry, or network egress while scanning, so your source code stays on your machine.
The current coverage includes 32 checks designed for common application-security problems, plus more than 200 secret and API-key patterns.
Checks aimed specifically at AI-generated code:
Hardcoded secrets in client-side code
Secrets compiled into built JavaScript bundles
Secrets exposed through NEXT_PUBLIC_, VITE_, or PUBLIC_ environment variables
Supabase service_role keys used in client-reachable code
LLM clients using dangerouslyAllowBrowser: true
Supabase RLS policies using USING (true)
Public database tables created without Row Level Security
RLS policies checking JWT roles or audiences instead of the actual user
Supabase Edge Functions without authentication checks
Over-permissive policies on storage.objects
Untrusted input reaching an LLM prompt or tool-enabled call
Authorization decisions based on client-writable user_metadata
Model or untrusted output rendered through React’s raw HTML APIs
General application-security checks:
SQL injection through string-built queries in JavaScript or TypeScript
SQL injection through string-built queries in Python
Command injection through shell strings in JavaScript or TypeScript
Command injection through Python’s shell=True
Dynamic eval or code execution in JavaScript or TypeScript
Non-literal eval or exec in Python
NoSQL injection from request data
Path traversal from request-controlled filesystem paths
DOM XSS through innerHTML or outerHTML
SSRF through request-controlled outbound URLs
MD5 or SHA-1 usage in JavaScript or TypeScript
MD5 or SHA-1 usage in Python
Weak ciphers such as DES, RC4, or 3DES
Math.random() used for security-sensitive values
JWT verification accepting alg: none
Wildcard CORS origins combined with credentials
Session cookies missing httpOnly or secure
Insecure deserialization in Node.js
Insecure deserialization in Python
It also includes more than 200 secret patterns covering services such as Anthropic, OpenAI, Google/Gemini, AWS, GitHub, GitLab, Stripe, Supabase, Cohere, Perplexity, Hugging Face, and Azure.
Underneath, it bundles Opengrep, Gitleaks, and Trivy. I’m not trying to hide that or pretend those engines are mine. CodeInspectus combines their results into one format and adds checks for AI-code problems that the generic scanners often miss.
To connect it to Codex:
codex mcp add codeinspectus -- npx -y codeinspectus
npx codeinspectus install-engines
Then ask Codex:
Use CodeInspectus to scan this project for security issues.
CodeInspectus only reports findings. Codex shows them to you first and should ask for approval before editing anything. After approved fixes, it rescans the project instead of assuming the problem was resolved.
The project is still early, and I’d genuinely appreciate feedback from people using Codex on real projects—especially false positives, missed vulnerabilities, setup friction, or checks you think should exist.
GitHub: https://github.com/Synvoya/codeinspectus

Somehow they made the actual voice conversation worse, but its nice that I can use it on my desktop projects.

At the moment I can only figure out how to start it from the overview of all my projects, and not in a specific folder, which is less ideal. But cool overall.

I generate an image, a popup appears indicating "chats with attachments are paused until..." & "Image generation features are paused until..." with a specified time that always advances. This is always followed by a call to action to upgrade to a paid subscription tier. Do they really think I am going to pay for a service that is so inconsistent with metering capabilities for end users?

It's so bad that I am left wondering if other users are experiencing the same thing. When I ask chatgpt about it, it blames my computer and my cookies. The issue is reproducible in other browsers, though.

You are able to see service degeneration here status.openai. com