GPT Image 2: two weeks after launching the model, usage is up 50% and 1.5bn images generated every week in ChatGPT only.
LLMS
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Levangie Labs Introduces Cognitive Architecture to Enhance LLM Capabilities
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Levangie Labs. Cognitive Architecture that greatly improves any LLM it sits on top of. Only used by big companies right now. I've seen people test it out against the others and it is way better.
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Standardizing Skills for Portable AI Coding Agent Workflows
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If you're building AI workflows for yourself or clients, the practical takeaway is simple: Write your Skills in the SKILL .md format. You're not locked to one vendor. Your thinking systems become portable across every major coding agent. One Skill, 30+ compatible tools. That's
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Comparative analysis of AI agent capabilities in Claude and Perplexity
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Here's what "Skills" actually means on each platform: Claude: Full code execution in a sandbox. Works across Claude. ai, Claude Code, the API, and the Agent SDK. Ships scripts. Persists across sessions. The deepest implementation. Perplexity: Same SKILL. md format running
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Industry-wide adoption of the SKILL.md format for AI agents
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Within months, the adoption list grew: → Perplexity adopted the format for Computer Skills (March 2026)
→ OpenAI adopted it for Codex CLI
→ Cursor adopted it
→ Windsurf adopted it
→ GitHub Copilot adopted it 30+ agents now support the same SKILL. md format. Anthropic -
Anthropic Introduces Claude Skills and Open Agent Standard
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October 2025: Anthropic launches Claude Skills. A folder with a SKILL .md file, YAML frontmatter, optional scripts. Claude auto-loads them based on relevance. No manual trigger needed. December 2025: Anthropic publishes the format as an open standard. Any agent can adopt it.
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Comparative Analysis of ‘Skills’ Features in Claude, Perplexity, and Grok
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Three companies launched a feature called "Skills" in the last 8 months. Claude. Perplexity. Grok. Same name. Completely different products. And one detail most people missed: Anthropic didn't just build Skills first. They open-sourced the standard that the other two are now
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The shift from pure LLMs to neurosymbolic AI architectures
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The pure LLM debate – which I had for many years, here and elsewhere – is indeed no longer relevant. Why? Because I won; nobody uses pure LLMs anymore. Nowadays all deployed objects are neurosymbolic, which was exactly the point of my infamous 2022 paper, Deep Learning is
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Automated 4-phase reality check workflow for Claude
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Now every time you ask Claude for a reality check, it runs the full 4-phase analysis automatically. No re-pasting. No setup. Just ask and it delivers. Follow @godofprompt for more prompts like this.
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Clear communication as the foundation of effective prompt engineering
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Prompt engineering is just communication with a specific audience. The "best prompt template" won't fix unclear thinking. The "perfect framework" won't fix vague instructions. Learn to communicate clearly, and every model gets better.