Agent-Frameworks

The question has been everywhere in DMs, group chats, and comment sections for weeks: did Anthropic just kill OpenClaw with Claude Code Channels? It’s a fair ask. Channels dropped recently. Anthropic also temporarily banned the OpenClaw harness from running on their subscriptions. Suddenly, the community started questioning everything. Dheeraj Sharma and the team at AI Maker decided to stop speculating and actually run both tools live. They scored them across eight categories with real deployments, not synthetic benchmarks. The verdict? No, Anthropic didn’t kill OpenClaw. But the gap is closing faster than most people expected — and the actual decision between these two tools is more nuanced than the tribal debates suggest. ...

The AI agent framework landscape has shifted significantly in the last 90 days. The framework you chose for your agentic project in January 2026 might not be the right choice in April — and one major player has effectively retired. This is the freshest comparison available as of this morning, covering 8 SDKs and 3 inter-agent protocols. The 8 Frameworks 1. Claude Agent SDK (Anthropic) Anthropic’s first-party SDK for building agents on Claude. Deep integration with Claude Code’s subagent architecture, native MCP tool support, and CLAUDE.md context injection. Best choice if you’re building Claude-native workflows and want tight model-SDK alignment. Not model-agnostic. ...

We’ve covered the “big three” AI agent frameworks — LangGraph, CrewAI, and Pydantic AI — in our 2026 framework decision guide. That guide remains the place to go for deep dives on those three. But the landscape has shifted. GitHub repositories for AI agent frameworks grew 535% between 2024 and 2025. Four more frameworks now have production deployments and genuine trade-offs worth understanding: the OpenAI Agents SDK, Claude SDK (Anthropic), Google ADK, and Dify. ...

The AI agent framework landscape looked very different eighteen months ago. In mid-2024, there were somewhere north of 14 actively-maintained frameworks competing for developer attention — AutoGen, MetaGPT, SuperAGI, AgentVerse, and a long tail of others all vying for the same mindshare. By early 2026, the field has consolidated dramatically. Three frameworks have emerged as the clear dominant players: LangGraph, CrewAI, and Pydantic AI. This isn’t a comprehensive benchmark — it’s a practical decision guide. Here’s how to choose. ...

If you’ve been in the AI agent space for more than a few months, you’ve heard the word “prompt engineering” approximately ten thousand times. LangChain co-founder and CEO Harrison Chase wants to retire it — and replace it with something more fundamental. His argument: context engineering is the skill that separates agents that actually work in production from ones that fall apart after five steps. And LangChain just shipped a framework to prove the point. ...

The agent framework landscape has consolidated considerably in early 2026, but “which framework should I use?” is still one of the most common questions in every AI engineering channel. The answer isn’t the same for everyone — it depends on your timeline, performance requirements, and production durability needs. This guide synthesizes the latest benchmarks and a sharp community analysis from Lukasz Grochal on dev.to to give you a practical decision framework. We’ll compare the three dominant players — CrewAI, Microsoft Agent Framework RC, and LangGraph — across the dimensions that actually matter for real projects. ...