robots should learn some manners! pic.twitter.com/i2NKZBz8tL
— clem 🤗 (@ClementDelangue) 13 février 2026
robots should learn some manners!
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robots should learn some manners! pic.twitter.com/i2NKZBz8tL
— clem 🤗 (@ClementDelangue) 13 février 2026
robots should learn some manners!

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BREAKING: MANUS AI IS ROLLING OUT A NEW ALWAYS-ON AGENT FUNCTIONALITY! SKILLS, SUBAGENTS, MEMORY, DEDICATED COMPUTER INSTANCE, IDENTITY AND MESSENGERS SUPPORT! Meta is coming for @openclaw

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Can we trust AI agents to interact with the world safely without a clear way to diagnose their mistakes? Shanghai Artificial Intelligence Laboratory presents AgentDoG! It is a new diagnostic guardrail framework that monitors AI agents in real-time. Instead of just blocking

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@togethercompute and @DecagonAI are redefining customer experiences from the ground up. “Every customer everywhere deserves a concierge experience – and voice is a cornerstone of delivering on this vision,” says Decagon Head of Research Max Lu. With Together’s optimized
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Coding agent users: do you run with –yolo (Codex) or –dangerously-skip-permissions (Claude Code) or equivalent?

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We’re excited to be exhibiting at MWC Barcelona (March 2–5) as part of the Netherlands Pavilion! We'd love to see you at Booth CS54, 4YFN area. While the industry talks about Agentic AI, we’re providing the engines that power it. Ready to optimize your edge strategy? Book a
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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/hlGz7pLOaa
Open-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

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People are already using Kimi K2.5 with OpenClaw. The experience is just at the next level, and it's so affordable!!! No stress, just build

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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

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How to use LLMs for competitive intelligence (scraping, analysis, reporting):