Compaction API, memory tool, effort parameter, web fetch, and MCP plugins — Claude's March 2026 API updates are not incremental improvements. They solve the hardest problems in agentic AI development.
How AI is reshaping software architecture from the inside — ML-powered pattern selection, LLM orchestration, AI gateways, event-driven agents, and a full team implementation roadmap with diagrams and production-ready code.
A comprehensive guide to ClawTeam — the open-source Agent Swarm Intelligence framework. Learn how to set up Dev, QC, and Tech Lead agents on a single laptop, handle security and performance concerns, prevent AI quality issues, and run a solo complex project with production-grade workflows.
Most people are stuck in Phase 1 of AI — asking questions and doing work themselves. Phase 2 is Agents: you set a goal, the agent delivers results. Here's the complete breakdown of what changed, how it works, and why it matters.
How Spec-Driven Development (SDD) transforms agentic AI from a vibe-coding toy into a production-ready engineering discipline. Real project experiences, frameworks, tooling, and hard lessons from leading teams with Claude Code, Kiro, and BMAD.
Deep dive into AI agent security threats in 2026. Covers prompt injection, data exfiltration, OpenClaw vulnerabilities, Claude Code hardening, and a complete defense architecture for teams deploying AI agents in client projects.
Implementation-ready guide to building the Brain agent in a multi-agent system. Covers LangGraph supervisor patterns, Command API routing, context injection, prompt engineering, state schema design, and cost-optimized model selection.
Production security patterns for multi-agent AI systems. Covers IAM least privilege per agent, prompt injection defense, input sanitization, output validation, audit logging, secrets management, and compliance requirements.
Complete implementation guide for worker agents in a multi-agent system. Covers tool design patterns, prompt engineering for cheap models, input/output contracts, error handling, and cost optimization with Haiku and DeepSeek.
Step-by-step guide to install NanoClaw on macOS, WSL Windows, and Proxmox. Includes real workflows for developers, QA engineers, marketers, and business users. Built on Claude AI.
Production-tested architecture for multi-agent AI systems using LangGraph on AWS. Brain/Worker cost optimization, Step Functions orchestration, DynamoDB checkpointing, CI/CD pipelines, and real-world cost modeling that achieves 5-10x savings.
The definitive guide to building AI Skills across Claude Code, GitHub Copilot, and Google Antigravity. Architecture deep-dive, SKILL.md standard, diagrams, practical examples, and best practices.
Learn how to set up Nanoclaw as your personal AI home assistant across WhatsApp, Telegram, and Discord — plus top optimization tips to get the most out of it.
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