Kimi K2.5 is THE BEST model for OpenClaw. It's open-source, SOTA on every benchamark, and SO AFFORDABLE!!! What you get:
✓ Vision reasoning (SOTA model)
✓ 100 parallel agents + 1,500 tool calls
✓ Expert Office outputs (Excel/PPT/Word/PDF)
✓ Video-to-code deployment
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AGI
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Kimi K2.5: Open-source SOTA model with agents and tools
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Local open-source coding agent with AI workflow
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Open-source coding agent that runs 100% locally.
— God of Prompt (@godofprompt) 13 février 2026
Unlike Claude Code:
✓ Fully unrestricted
✓ Transparent (Python-based)
✓ Accepts video as input
✓ No cloud dependency
Watch it build an autonomous driving data visualization through MCP:
→ Reads local datasets
→ Generates… pic.twitter.com/hlGz7pLOaaOpen-source coding agent that runs 100% locally. Unlike Claude Code:
✓ Fully unrestricted
✓ Transparent (Python-based)
✓ Accepts video as input
✓ No cloud dependency Watch it build an autonomous driving data visualization through MCP:
→ Reads local datasets
→ Generates -
AI agents research YouTube creators across niches
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100 YouTube creators across 100 different niches.
— God of Prompt (@godofprompt) 13 février 2026
This would take you 8+ hours of manual research.
Kimi deployed 100 sub-agents simultaneously:
→ Each researched a specific niche
→ Found top creators
→ Scraped subscriber counts
→ Grabbed channel URLs
→ Compiled everything… pic.twitter.com/BmfkX1pQfi100 YouTube creators across 100 different niches. This would take you 8+ hours of manual research. Kimi deployed 100 sub-agents simultaneously:
→ Each researched a specific niche
→ Found top creators
→ Scraped subscriber counts
→ Grabbed channel URLs
→ Compiled everything -
Competitor 90-Day AI Activity Analysis Template
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Step 1 – Data Collection (Gemini) Prompt: Analyze [COMPETITOR]'s last 90 days of activity: 1. Product launches or updates
2. Pricing changes
3. New hires (executive level)
4. Customer complaints (Reddit, Twitter, G2)
5. Website changes (new pages, messaging shifts) Format as -
Brain accounts for 20% of body energy consumption
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And your brain accounts for 20% of yours, so long way to go.
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Google DeepMind paper critiques real-world AI agents
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I just read Google DeepMind’s new paper called "Intelligent AI Delegation." And it quietly exposes why 99% of AI agents will fail in the real world. Here’s the paper: Most “AI agents” today aren’t agents. They’re glorified task runners. You give them a goal.
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AI as Great Automator: Imitation Deceives Perception
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AI is the great automator, and to automate, it must first imitate. The imitation fools people into thinking it’s alive.
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ARC-AGI benchmark: Fact-checking claims about AI capabilities
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All 3 points here are wrong BTW: ARC-AGI came out 2 years ago It was declared "impossible for AI" beaten within the year, so they made ARC-AGI-2. Fact checking should occur *prior* to posting.
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Local AI hardware changes development approach
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Alex bought a $10,000 Mac to run @openclaw with powerful local models. He isn’t alone. Know a guy with several NVIDIA H200’s in his house. Now that I am building I get it. Having your own local AI changes your whole approach to building with AI. I can’t afford that and running