Let the cheaper model handle 90% and escalate the hard stuff.
PROMPT ENGINEERING
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Psychology of AI Review Processes Improves Output Quality
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The psychology here is solid. Telling Claude that another model will review the output raises the perceived stakes and tends to produce more careful, thorough work.
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Anthropic Shifts from Agents to Skills for AI Models
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the creators of agent skills at Anthropic explained why they stopped building agents.
— m0h (@exploraX_) 13 avril 2026
and started building skills instead, showing just how powerful agentic skills can be
the article below shares 20 powerful skills you can pair with any AI model.
enjoy! https://t.co/Nk8xL5oHjY pic.twitter.com/dVoYsM069Ithe creators of agent skills at Anthropic explained why they stopped building agents. and started building skills instead, showing just how powerful agentic skills can be the article below shares 20 powerful skills you can pair with any AI model. enjoy! m0h (@exploraX_) x.com/i/article/203923778765… — https://nitter.net/exploraX_/status/2039269234253934811#m
→ View original post on X — @scobleizer, 2026-04-13 06:35 UTC
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Old School VS Coder Supercharged with Claude AI
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I’m old school VS coder supercharged with Claudio.
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JSON’s Token Inefficiency Problem Costs Real Money
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json is so token inefficient it hurts these days man, these braces and quotes are costing me real $$
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Claude.md File Reaches 15K Stars with AI Coding Guidelines
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A single 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱 file just hit 15K GitHub stars. (derived from Karpathy's coding rules) Andrej Karpathy observed that LLMs make the same predictable mistakes when writing code: over-engineering, ignoring existing patterns, and adding dependencies you never asked for. If you've used AI coding assistants, you've hit all of these. But here's the thing: If the mistakes are predictable, you can prevent them with the right instructions. That's exactly what this 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱 does. You drop one markdown file into your repo, and it gives Claude Code a structured set of behavioral guidelines for your entire project. This is a big deal. – Built entirely around prompt engineering for AI coding assistants – No framework, no complex tooling, just one .md file that shapes behavior Developers are moving past "use AI to write code" and into "engineer the AI's behavior so the code is actually good." The Claude Code ecosystem is growing fast, and the best tools in it aren't always software. Sometimes they're just well-crafted instructions. 100% open-source. I've shared a link to the GitHub repo in the next tweet!
→ View original post on X — @akshay_pachaar, 2026-04-12 17:02 UTC
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Top AI Papers: Agents, LLMs, and Coding Automation
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The Top AI Papers of the Week (April 6 – 12) – Memento
– Neural Computers
– The Universal Verifier
– Agent Skills in the Wild
– Memory Intelligence Agent (MIA)
– Single-Agent vs Multi-Agent LLMs
– Scaling Coding Agents via Atomic Skills Read on for more: -
Hermes Agent: Self-Improving AI with Cross-Session Memory
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The self-improving AI agent from Nous Research! Hermes Agent is a self-improving AI agent that builds skills from your work, improves them over time, and remembers across sessions. Most AI agents reset every conversation. You teach them your codebase structure, they forget. You
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AI Scaling Bad Targeting: Context Matters More Than Prompts
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The hardest part of AI is not about writing the perfect prompt.
The hardest part is knowing who you’re actually talking to. AI won’t fix bad targeting.
It just helps you scale it faster. Automated “AI-generated outreach” fails for the same reason this text did: → No context -
Corey Ganim builds first managed agent with Claude Code
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this guy is @coreyganim. Full video (including the Google Doc you hand to Claude Code to build your first managed agent) here: piped.video/watch?v=nAOyErph…