And it isn't really fair criticism. I've been on many spaces defending you all against criticism.
AGENTS
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Opus 4.7 tight plans enable GPT-5.5 confident execution
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Why this works. Opus 4.7 writes tight, contract-style plans. Exact file counts. Line limits. First-principles architecture. It thinks like a senior engineer scoping a project. GPT-5.5 reads that plan and executes with confidence. It deletes files, rewrites from scratch,
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Opus 4.7 plus GPT-5.5 nearly doubles benchmark scores
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Dan Shipper at Every tested this on their Senior Engineer Benchmark. The scores:
Opus 4.7 alone: low 30s GPT-5.5 alone: low-to-mid 40s Opus 4.7 planning + GPT-5.5 executing: 62.5 For reference, human senior engineers score 80-90. The combo nearly doubled either model's -
DeepAgents CLI Coding Harness Shines With Open Weight Models
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open weight models are having a moment @masondrxy is making deepagents cli a coding harness that works amazing with open weight models what is missing? what should he add? try it out!
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Single-model workflows: planning vs executing is flawed
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Here's the problem with single-model workflows. Planning and executing are two completely different cognitive tasks. Asking one model to do both is like hiring the same person as your strategist and your builder. Some models think beautifully but execute loosely. Others
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AI coding workflow pits Opus 4.7 planner against GPT-5.5 executor
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I tested the highest-performing AI coding workflow of 2026. It doesn't use one model. It uses two competing models against each other. Opus 4.7 plans. GPT-5.5 executes. The results aren't close. (Prompts included)
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Runway Characters Enables Real-Time Conversational Video Agents at 24fps
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Real-time video agents are here.
— Runway (@runwayml) 4 mai 2026
Today, we’re sharing how we built Runway Characters, allowing you to turn one image into a fully expressive, conversational video agent streaming at 24 frames per second in HD. With just 1.75 seconds of end-to-end latency.
Learn more below. pic.twitter.com/CJqv3Kdl0vReal-time video agents are here. Today, we’re sharing how we built Runway Characters, allowing you to turn one image into a fully expressive, conversational video agent streaming at 24 frames per second in HD. With just 1.75 seconds of end-to-end latency. Learn more below.
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AI Agents Are Multi-Layered Systems Powered by Orchestration
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AI Agents ≠ one LLM They’re multi-layered systems: • General LLMs → reasoning
• Domain LLMs → expertise
• RAG → real-time data
• Tools → execution Real power = orchestration From answers → to actions. Via Giuliano Liguori (
@ingliguori
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AI Self-Review: How ListenLabs Built Autonomous Quality Checks
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What if your AI could review its own work before you even see it?@ListenLabs Co-Founder & CTO @florian_jue explained how this works on the Max Agency podcast hosted by @hwchase17 pic.twitter.com/YHXwL39q2v
— LangChain (@LangChain) 4 mai 2026What if your AI could review its own work before you even see it? @ListenLabs Co-Founder & CTO @florian_jue explained how this works on the Max Agency podcast hosted by @hwchase17
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AI Agents and LLM Workflows: Highlighting Innovative Startups
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I hope this thread was useful.
— Charly Wargnier (@DataChaz) 4 mai 2026
Small teams like @Tiny_Fish are the ones truly pushing the boundaries of AI right now.
If you enjoyed this, feel free to repost to support their work ♻️
For more on AI agents and LLM workflows, follow me → @datachaz https://t.co/YFX8DND7oiI hope this thread was useful. Small teams like @Tiny_Fish are the ones truly pushing the boundaries of AI right now. If you enjoyed this, feel free to repost to support their work For more on AI agents and LLM workflows, follow me → @datachaz