16 posts tagged with “ai-agents”
Single-agent architectures hit a wall the moment your task needs planning, research, and execution in parallel. Multi-agent systems solve this — but most tutorials skip the hard parts. This guide doesn't.
Everyone's building with agents, MCP servers, skills, and subagents. Almost nobody can explain when to use which. This is the guide that fixes that — with architecture diagrams, production code, and a decision framework you can apply today.
Most RAG pipelines retrieve garbage, stuff it into context, and pray. Agentic RAG replaces the prayer with a judge, a retry loop, and a routing layer that actually works.
Your agent framework handles the happy path. Erlang's supervision trees handled telecom uptime for 40 years. Here's how to apply the same 'let it crash' philosophy to make AI agents self-healing.
On April 2, 2026, Google shipped Gemma 4 (89% on AIME, 80% on LiveCodeBench, 86% on agentic tool use) and Cursor shipped a ground-up agent-first IDE. Here is what the new developer stack looks like.
Every AI coding session starts from zero. CLAUDE.md, AGENTS.md, and Cursor Rules are how you give agents institutional memory — and the difference between AI that guesses your conventions and one that ships to them.
ByteDance's DeerFlow 2.0 hit #1 on GitHub Trending with 39K stars in weeks. It's not another chatbot wrapper — it's a full-stack SuperAgent harness with sandboxed execution, persistent memory, sub-agents, and LangGraph orchestration. Here's everything you need to build with it.
Anthropic's Claude just became a remote digital operator for your Mac — clicking, typing, and navigating apps on your behalf. Here's how the tech works, what the privacy trade-offs are, and why this escalates the AI agent war.
ARC-AGI-3 just launched and current AI scores under 5%. The same week GPT-5.4 solved an open research math problem. This is not a contradiction. It is the most important insight about intelligence published this decade.
AI is leaving the cloud. The next revolution isn't AGI — it's a billion cheap, autonomous agents running on the device in your hand, your wall, and your factory floor.
GPT-5.4 ships native computer-use today, hitting 75% on OSWorld — surpassing the 72.4% human baseline. Here's how to build agents with it.
WordPress.com just shipped 19 write operations via MCP — your AI agent can now draft posts, fix SEO, and manage your entire site in plain English.
Step-by-step tutorial with complete Python code to build a production-ready event-sourced AI agent — orchestrator, planner, policy guard, tool executor, and replay engine.
NVIDIA's NemoClaw brings policy-based security, privacy guardrails, and local model execution to OpenClaw agents in a single install. Here's what developers need to know.
Most AI agents fail in production because they are not replayable, testable, or safe. Learn an event-sourced architecture that gives your agents deterministic behavior, cost control, and enterprise-grade reliability.
Model Context Protocol (MCP) is becoming the USB-C of AI integration — a single standard for connecting LLMs to any tool, database, or API. Here's the architecture, the primitives, and how to build your first server.
