DiamantAI Blog
Weekly deep dives on AI agents, RAG systems, prompt engineering, and production AI. Read the latest on Substack.
Your First AI Agent: Simpler Than You Think
A beginner-friendly guide to building your first AI agent from scratch, covering what agents really are, how they work, and step-by-step instructions to build one.
Model Context Protocol (MCP) Explained
A deep dive into Anthropic's Model Context Protocol, what it is, how it works, and why it matters for connecting AI models to external tools and data sources.
You're Using Claude Code Wrong (And Wasting Hours Every Day)
Most developers use Claude Code like a fancy autocomplete. Here's how to unlock its full potential and 10x your productivity.
Stop Thinking Claude Code Is Magic. Here's How It Actually Works
A technical breakdown of how Claude Code works under the hood, from context management to tool use patterns and system prompts.
How to Choose Your AI Agent Framework
A practical comparison of AI agent frameworks, when each shines, their trade-offs, and how to choose the right tool for your project.
The Hidden Algorithms Powering Your Coding Assistant
What's really happening behind the scenes when your AI coding assistant generates code, the retrieval, ranking, and generation pipeline explained.
How to Stop AI Hallucinations
AI hallucinations are one of the biggest challenges in production AI. Here are battle-tested techniques to minimize and control them.
Graph RAG Explained
How Graph RAG combines knowledge graphs with retrieval-augmented generation to deliver more accurate, structured, and contextual AI responses.
The AI Arms Race Is Over. Smart Engineering Won
The era of scaling compute is ending. What's replacing it is smarter engineering, better architectures, evaluation, and deployment patterns.
Google's Agent2Agent (A2A) Explained
Google's new Agent2Agent protocol enables AI agents to communicate and collaborate across platforms. Here's how it works and why it matters.
Why AI Experts Are Moving from Prompt Engineering to Context Engineering
Context engineering is the new frontier, going beyond prompts to control the entire information environment around your AI system.
AI Deep Research Explained
How AI deep research tools work, from multi-step reasoning to iterative search and synthesis. A technical breakdown of the emerging research agent pattern.
Memory Optimization Strategies in AI Agents
How to give AI agents persistent memory, covering short-term, long-term, episodic, and semantic memory implementations with practical strategies.
Why AI Agents Need to Check Their Own Work
Self-verification is the missing piece in most AI agent architectures. Here's how to build agents that validate their own outputs before returning results.
Context Engineering: How AI Turns Email Chaos into Searchable Intelligence
A practical walkthrough of building an AI-powered email intelligence system using context engineering principles.
This Simple Trick Makes AI Agents Far More Reliable
Making AI agents argue with themselves dramatically improves reliability. Here's the self-debate pattern and how to implement it.
Moltbook - A Social Media for AI Agents - Explained
Moltbook is a new platform where AI agents interact on social media. Here's how it works, why it's interesting, and what it means for multi-agent systems.
Once and for All - What Clawdbot Actually Is and Why It's Not Claude Code
Clearing up the confusion between Clawdbot and Claude Code, what each tool does, how they differ, and when to use which.
OpenClaw Tutorial - Build an AI Agent That Manages Your Bills and Sends You a Daily Briefing on WhatsApp
Step-by-step tutorial for building a practical AI agent that monitors your bills, analyzes spending, and sends daily WhatsApp summaries.
Controllable Agent for Complex RAG Tasks
How to build controllable agents that handle complex RAG workflows, with user-guided retrieval strategies and transparent decision-making.