#chain-of-thought
163 related articles
Learning AI Agent Development from Scr…
·3 min
Learning AI Agent Development from Scratch: A Beginner's Path and Monetization Guide
A comprehensive guide to AI Agent development for beginners, covering low-code platforms, LangChain framework, and monetization strategies for building and deploying intelligent agents.
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LangChain from Beginner to Agent Devel…
·3 min
LangChain from Beginner to Agent Development: A Complete Learning Path for LLM Application Development
A systematic guide to LangChain LLM application development, covering environment setup, core components (RAG, Chain, Memory), and Agent development to help developers master LLM app building.
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AI Large Language Model Learning Roadm…
·3 min
AI Large Language Model Learning Roadmap for Beginners: A Three-Month Hands-On Guide
A detailed zero-to-hero AI large model learning roadmap covering four phases—fundamentals, RAG, Agents, and engineering deployment—with a practical three-month study plan and career advice.
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·2 min
Cherry Studio: A Deep Dive into the Open-Source AI Productivity Tool with Unified Access to 300+ LLMs
Deep dive into Cherry Studio, an open-source AI client supporting 300+ LLMs including OpenAI, Claude, and Gemini, with autonomous agents and pre-built assistants. Nearly 47K GitHub Stars.
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·2 min
Claude Has Written 80% of Its Own Code: Anthropic's Internal Data Reveals the State of AI Self-Development
Anthropic's internal data shows Claude writes 80% of its own code, engineers produce 8x more output, and open-ended task success jumped from 26% to 76%. The era of AI developing AI is accelerating.
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·2 min
Google Hides Gemini's Chain of Thought: Why This AI Transparency Rollback Is Sparking Controversy
Google now hides Gemini's thinking process by default, preventing users from verifying reasoning logic and search behavior. We analyze why this transparency rollback matters and how it compares to ChatGPT and Claude.
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·1 min
Gemini 3.5 Flash Early Experience: Balancing Speed and Capability
Developers share early hands-on experience with Google's Gemini 3.5 Flash model, showing fast speed, strong coding ability, and self-correction. A deep dive into its performance, testing, and positioning.
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·2 min
Gemini 3.5 Flash Teams Up with Antigravity: Multi-Agent Collaboration to Build an Entire City
Deep dive into how Gemini 3.5 Flash and Antigravity platform use multi-subagent architecture to design and build a complete virtual city from scratch.
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·2 min
Tokenmaxxing: OpenAI Invests $2M in Tokens to YC Startups — A New AI Startup Paradigm Emerges
What is Tokenmaxxing? OpenAI provides $2M in Token credits to each YC startup, marking a fundamental shift in AI startup investment. Analysis of Token-as-capital, how Tokenmaxxing startups operate, and potential risks.
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·2 min
OpenAI Launches Long-Term Token Discounts: As Compute Scarcity Becomes the Norm, How Should Enterprises Lock In AI Capacity
OpenAI launches 1-3 year Token commitment discounts as compute scarcity becomes the industry norm. Analysis of the compute bottleneck, business logic, and strategic implications for enterprises.
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·4 min
Legitimate Slacking for Programmers: The Art of Waiting from Code Compilation to AI Generation
From the classic XKCD compilation meme to AI coding era reinterpretations — exploring how waiting for compilation and AI generation is reshaping developer productivity.
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·4 min
The Art of Legitimate Slacking: From Code Compilation to AI Generation Waits for Programmers
From the classic XKCD compilation meme to AI coding era reinterpretations — exploring how waiting for compilation and AI code generation is reshaping developer productivity.
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·2 min
Two Years of AI Growth: From Passively Following Instructions to Proactively Understanding Intent
A look at AI's core evolution over two years: from a prompt-dependent instruction follower to an autonomous collaborator that understands intent, plans tasks, and self-corrects.
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·3 min
Cursor Auto-Review Mode Explained: Smart Tiered Approval for More Efficient AI Programming
Cursor launches Auto-review mode with smart risk assessment for tiered approval. Low-risk operations auto-approve while high-risk ones need manual confirmation.
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·3 min
Firebase AI Logic in Practice: Using Gemini to Automatically Break Down Tasks into Actionable Subtasks
A hands-on guide to Firebase AI Logic and Gemini integration, showing how to automatically break down large tasks into actionable subtasks with structured output and real-time sync.
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·4 min
Five Common Misconceptions in AI Agent Development: An Essential Guide Before You Start
Debunking 5 common AI Agent development misconceptions: Agents aren't smarter ChatGPTs, complexity doesn't equal power, and RAG can't cure hallucinations. Learn the right approach to building Agents.
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·3 min
Firebase Integrates with AI Studio: Four Core Capabilities for Production-Grade Agent Applications
Deep dive into Google Firebase's integration with AI Studio, covering four core capabilities—database auto-configuration, authentication, security rules drafting, and zero-config deployment—for production-grade AI agent apps.
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·3 min
Deep Conversation with Gemini's Four Co-Leads: Technical Roadmap, Current State, and Future Direction
Google Gemini's four co-leads — Jeff Dean, Noam Shazeer, and others — discuss Gemini's technical roadmap, multimodal capabilities, Agent direction, and future strategy in a rare joint conversation.
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Industry Insights·2 min
AI Product Development in Practice: Model Selection, Building Moats, and Paths to Commercialization
Practical strategies for AI product development: why not to train models from scratch, when to use APIs vs. fine-tuning, building product moats, and the full path from evaluation systems to commercialization.
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Tutorials·3 min
Agent Tuning: A Complete Guide to Training LLMs with Agent Capabilities
A deep dive into Agent Tuning principles and practices, covering why Agent training is needed, the evolution from Prompt to RAG to Agent, development workflows, and cost assessment for private deployment.
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