Technically, "unreleased" model is already available on LM Arena in Preview. And it was the only one that followed "minimalistic" instruction properly. – Image 1 – MAI Image 2.5 – Image 2 – GPT Image 2
– Image 3 – Nano Banana 2
– Image 4 – MAI Image 2
PROMPT ENGINEERING
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Only unreleased model on LM Arena Preview follows minimalistic instruction
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Godofprompt gets OpenAI X analytics with one prompt, no code, using ego lite browser
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I pulled a full week of @OpenAI
's X analytics without an API key, a scraper, or a single line of code One prompt. 30 seconds. The tool that made this possible isn't Claude, Cursor, or ChatGPT. It's a browser called ego lite: -
Two-step prompting: camera move first, then add character
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It’s still pretty good! Maybe the simple solution is to first prompt it to get the camera move right, without the character – just the drone point of view. Then take that video and prompt it to add the character with text or img ref.
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Microsoft transforms SKILL.md into trainable object with SkillOpt
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Microsoft just turned SKILL .md into a trainable object! SkillOpt is a text-space optimizer for agent skills. Instead of hand-writing or one-shot generating your SKILL .md, SkillOpt treats the skill document as the trainable external state of a frozen agent and optimizes it
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Use Codex instead of ChatGPT for better responses
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You need to ask codex, not chatgpt if you want good responses.
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Explain vs. Describe: Understanding the Nuance in AI Concepts
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"Explain" vs. "Describe" These feel identical. They're not. "Explain RAG to me" gets you retrieval mechanics, why chunks are embedded, how context windows are populated, and where the architecture breaks. "Describe RAG to me" gets you a surface-level overview. What it looks
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GPT 5.5 boosts prompt duration and confidence with new features
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With GPT 5.5, /goal, autoreview and crabbox my prompts moved from ~30-60min to often 4-10h tasks and my confidence that it’s ready is much much higher. Yielding agents is a skill.
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Old model vs new: from syntax to plain language
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The old model was simple:
you had an idea,
then translated it into syntax,
then fought the tooling until it worked. The new model looks very different: → describe the app in plain language
→ generate the interface, logic, and structure
→ test it
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Build Complex SaaS Apps End-to-End with AI, No Coding Required
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🚨 Build Complex SaaS Apps End To End – No Coding Experience Needed
— Abacus.AI (@abacusai) 30 mai 2026
Use Opus 4.8, GPT 5.5 xHigh and Gemini 3.5 Pro to make magic
No need to set up databases, user auth or backend
Do it all in one prompt pic.twitter.com/wmbWmF7MzCBuild Complex SaaS Apps End To End – No Coding Experience Needed Use Opus 4.8, GPT 5.5 xHigh and Gemini 3.5 Pro to make magic No need to set up databases, user auth or backend Do it all in one prompt
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AI Vision Model Limitations in Object Detection Tasks
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This kind of prompt only works up to a point. If I ask it to put bounding boxes around all cars or all vehicles, it will mislabel lots of things while also hallucinating new things to label. pic.twitter.com/8B1CNnlbh5
— fofr (@fofrAI) 29 mai 2026This kind of prompt only works up to a point. If I ask it to put bounding boxes around all cars or all vehicles, it will mislabel lots of things while also hallucinating new things to label.