#iterative thinking
393 related articles
·2 min
Bun Now Generates CLAUDE.md by Default: The AI-Native Development Era Has Arrived
Bun runtime now generates a CLAUDE.md file by default with bun init, signaling AI assistants becoming first-class citizens in the development toolchain.
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·3 min
Lessons from Claude Code's 80% Prompt Reduction: Less Is More in Prompt Engineering
Anthropic cut Claude Code's system prompt by 80% and got better results. Learn why verbose prompts hurt performance, how to streamline them, and key lessons for AI developers.
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·2 min
Training AI to Play Devil May Cry 3 with Reinforcement Learning: Challenges and Practices in Action Game AI
An indie developer trains AI to autonomously play Devil May Cry 3 using reinforcement learning. Explore the core challenges of action game AI including sparse rewards, high-dimensional action spaces, and real-time decision-making.
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·2 min
Training AI to Play Devil May Cry 3 with Reinforcement Learning: Challenges and Practices for Action Game AI
An indie developer trains AI to autonomously play Devil May Cry 3 using reinforcement learning. This article analyzes the core challenges including sparse rewards, high-dimensional action spaces, and real-time decision-making.
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·3 min
ChatGPT as Your Home Tech Advisor: How It Helped Me Save $20 a Month
A Reddit user used ChatGPT to diagnose home network issues, discovered the bottleneck was the router not the ISP, and saved $20/month by downgrading their plan. Learn the AI collaboration method.
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·3 min
Kimi K3 Hands-On Review: 2.5 Trillion Parameter Open-Source Model Challenges Claude
Kimi K3 hands-on review: Moonshot AI's 2.5T parameter MoE model matches Claude in coding, surpasses it in 3D game development, with API pricing at one-tenth the cost of competitors.
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·3 min
Network Doctor: An Open-Source Terminal Tool for Network Fault Diagnosis
Network Doctor is an open-source terminal network diagnostic tool that integrates ping, dig, curl, and traceroute, automatically detecting connectivity in stages and outputting fault conclusions in natural language.
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·3 min
Practical Guide to Agent Development: The Complete Path from Zero to Commercial Deployment
A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.
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·3 min
Backend Developer Transition to AI/LLM: 4 Core Skills and a Practical Learning Roadmap
Complete guide for backend developers transitioning to AI/LLM engineering. Covers the 4 core skills—Python, RAG, Fine-tuning, and Agents—with a phased learning roadmap and practical project advice.
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·3 min
Agent Skill Routing: Engineering Trade-offs Between Retrieval and LLM, and the Two-Stage Layered Architecture
Deep dive into Agent skill routing: comparing pure model vs. pure retrieval approaches, with a detailed two-stage layered architecture balancing accuracy, latency, and cost.
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·4 min
Spring AI 2.0 in Practice: Building an Enterprise RAG Knowledge Base Q&A System with Cursor
Build an enterprise RAG knowledge base Q&A system using Spring AI 2.0, Cursor AI programming, Ollama local deployment, and Redis vector storage. Runs on just 4GB VRAM.
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·3 min
Deep Dive into Inkling: The First Frontier Open-Source Multimodal LLM from the West
Thinking Machines releases Inkling, an open-source multimodal LLM with near-trillion MoE parameters, 1M token context, Apache 2.0 license. Deep dive into architecture, benchmarks, and pricing.
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·2 min
How Gamma Uses AI to Reinvent Presentations: A Complete Revolution from Product to Workflow
Gamma CEO Grant Lee shares how the company deeply integrates OpenAI technology to drive presentation innovation with AI—from image generation to content creation and internal development workflows.
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·4 min
Getting Started with AI Agent Development: A Complete Guide from Concept to Practice
A comprehensive guide to AI Agent architecture and development, covering automated marketing, intelligent customer service, and investment analysis scenarios with single and multi-agent collaboration.
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·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·3 min
From RAG to Agent Tuning: A Complete Guide to Deploying LLM Agents
A deep dive into LLM Agent frameworks covering RAG, Agent core components (tools, memory, planning), and Agent Tuning workflows with cost considerations for production deployment.
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·2 min
Codex Beginner's Guide: Understanding the Difference Between OpenAI's Coding Agent and ChatGPT
A detailed guide to OpenAI Codex coding agent: understand how it differs from ChatGPT, how AI agents autonomously generate, debug, and test code, and why developers need to learn this new paradigm.
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·2 min
Codex Beginner's Guide: Understanding the Difference Between OpenAI's Coding Agent and ChatGPT
A detailed guide to OpenAI's Codex coding agent: understand what it is, how it differs from ChatGPT, and why developers should master AI coding agents now.
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·2 min
The Complete Methodology for Landing an Offer Using Claude for Mock Interviews
A job seeker used Claude for AI mock interviews, fixing rambling answers and buried examples through iterative feedback, and landed the offer. Full methodology inside.
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·3 min
Why Can't AI Draw Charts Properly? The Cognitive Blind Spots in LLM Visualization Capabilities
Top AI LLMs can write code and pass professional exams, yet can't produce an accurate chart. This article analyzes why AI fails at chart generation and reveals the uneven nature of AI intelligence.
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