Yup, the bridge is what I was actually testing to see if it could reproduce. In some rolls it gets close but given a bit of spatial RAG (say of local aerial and street view imagery) the result could be far more geographically accurate.
PROMPT ENGINEERING
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ChatGPT Image Recreation Prompt Engineering Experiment
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ChatGPT pidió 74 veces que “recreara perfectamente esta imagen, sin cambios” pic.twitter.com/Vf44smKm8y
— SONIA (@S0N_IA_) 27 mai 2026ChatGPT asked 74 times to “perfectly recreate this image, without changes”
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Companies wrestling with token usage and model choices
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Most companies only have very crude understanding of token usage right now, so they veer from focusing on adoption (“everyone should use as many tokens as possible”) to cost control (“can we just use local models?”) depending on the moment and manager. This is all very new.
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Debate over Token Allocation as AI Becomes Essential for Coding
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The fact that tokens went from something no one even put in a budget line a year ago to an absolute requirement for coding now is the cause of handwringing, not that AI is not turning out to be useful No one knows who should get tokens, how much they should get & how to control
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Introduction to Runway MCP: Connect to Claude, ChatGPT, and More
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Introducing Runway MCP. Now you can connect Runway directly into Claude, ChatGPT, Cursor, Replit and more.
— Runway (@runwayml) 27 mai 2026
Generate polished images and videos with state-of-the-art models, like Gen-4.5, Seedance 2.0, GPT Images 2.0, Kling and more. Right from where you're already working.… pic.twitter.com/J3wBb4kZDyIntroducing Runway MCP. Now you can connect Runway directly into Claude, ChatGPT, Cursor, Replit and more. Generate polished images and videos with state-of-the-art models, like Gen-4.5, Seedance 2.0, GPT Images 2.0, Kling and more. Right from where you're already working.
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AI Agents Automate Task Distribution and Team Coordination
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Works with Claude Code, Codex, and OpenCode out of the box. Define the org chart once, assign work from the top down, and have agents handle the rest, including handoffs among themselves. Every completed task feeds back into a shared memory layer, building SOPs the whole team
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Optimizing Codex Prompts for AI Agent Automation
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UPDATE: Came up with an even better version of this prompt after the feedback Ask Codex to look across your sessions, Memories, and Chronicle, identify patterns, reuse what already exists, and only create the smallest useful skill, subagent, or automation. "Look back over my x.com/reach_vb/statu…
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Agent Token Efficiency: Context Re-reading Loop Performance
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input tokens are the real driver here. agent re-reads the entire context on every single loop
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Building SaaS Apps with Multiple LLMs in One Prompt
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🚨 One Prompt To A Fully Functional SaaS App And Complete Software
— Abacus.AI (@abacusai) 27 mai 2026
Opus 4.7 -> front-end
GPT 5.5 -> long running complex backend
Gemini 3.5 – > AI chatbot embedded in the app
Sonnet 4.6 -> scheduled task mask management
Kimi 2.6 -> simple cron jobs
One prompt will build AND… pic.twitter.com/nzMkP7ripuOne Prompt To A Fully Functional SaaS App And Complete Software Opus 4.7 -> front-end
GPT 5.5 -> long running complex backend
Gemini 3.5 – > AI chatbot embedded in the app Sonnet 4.6 -> scheduled task mask management
Kimi 2.6 -> simple cron jobs One prompt will build AND -
Storyboard-first AI video workflow with Topview Canvas and Seedance 2.0
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The prompt box was never enough.
— God of Prompt (@godofprompt) 26 mai 2026
AI video needs a creative workflow, not another “type and pray” casino.
Topview Canvas lets you build the storyboard first, arrange scenes on an infinite Figma-like canvas, work with an agent, then generate with Seedance 2.0.
Control before… https://t.co/nDA3Zhiv8F pic.twitter.com/Q2Qu1D4ZzbThe prompt box was never enough. AI video needs a creative workflow, not another “type and pray” casino. Topview Canvas lets you build the storyboard first, arrange scenes on an infinite Figma-like canvas, work with an agent, then generate with Seedance 2.0. Control before