Pro-tip: add to Claude Md to be brutally honest and that it should be as objective as possible
PROMPT ENGINEERING
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Agentic Engineering: Fireside Chat at Pragmatic Summit
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I spoke about agentic engineering at the Pragmatic Summit last month, in a fireside chat hosted by Eric Lui – here's the half hour video plus highlight quotes and extra notes from our conversation
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Identifying AI Usage: Verbose vs Dense Writing Patterns
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How do you tell who’s using AI? Overly verbose vs super dense?
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Adapting AI Prompting Strategies for Better Results
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Same task. Different AI. Different prompt. ChatGPT → Instructor mode
Perplexity → Research analyst mode
Grok → Candid friend mode
Gemini → Project planner mode If your results feel average, it’s probably not the model.
It’s the prompting strategy. Adapt your style to the -
Prompt Engineering’s Persistence: A Sign We’re Far From AGI
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The persisting importance of prompt engineering — and now harness engineering — is one of the best indicators of how far we are from AGI. A general system doesn't need a task-specific harness. And when provided with instructions, it is robust to phrasing variations.
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Standard Configuration Files Improve LLM Efficiency and Token Usage
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Having a known place you can get that information for a given URL, rather than having to create it from scratch yourself, is rather convenient. E.g if you tell Claude Code about the claude llms.txt, it's way faster and more token efficient at getting info about how it works.
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llms.txt pioneered markdown foundation for modern AI agents
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Exactly. llms.txt literally pioneered the idea that we should simply give our agents a markdown list of links with descriptions of what they can find in each, and let them decide what to read. That's basically the foundation of how agents work today.
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Claude Sonnet 4.6 Outperforms Supabase MCP in MCPMark Benchmarks
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2/ They ran MCPMark v2 benchmarks with Claude Sonnet 4.6 Vs. Supabase MCP. → Pass@4: 76% (vs 66%)
→ Tokens/run: 7.3M vs 17.9M
→ Speed: 156s vs 198s Agents complete tasks faster and use way fewer tokens. That gap only grows with smarter models. → https://
insforge.dev/blog/mcpmark-b
enchmark-results-v2
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Generate Videos in Seconds with ChatLLM by Abacus AI
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Generate videos in seconds with ChatLLM by Abacus AI.
— Abacus.AI (@abacusai) 13 mars 2026
Access top AI video models like Kling AI v3, Sora 2, Wan 2.5, and Seedance 1.5 pro all in one place.
Type a prompt. Get a video. pic.twitter.com/RGlbgY1DDAGenerate videos in seconds with ChatLLM by Abacus AI. Access top AI video models like Kling AI v3, Sora 2, Wan 2.5, and Seedance 1.5 pro all in one place. Type a prompt. Get a video.
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Prompt Engineering Value Questioned Against Gemini Performance
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Sure, but it makes me question the value of spending so much effort on prompt engineering if the output ultimately ends up being inferior to Gemini.