Acp

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. ...

OpenClaw v2026.3.8 dropped three days ago and it’s a release that’s easy to overlook if you’re only scanning headlines — but self-hosters should pay close attention. The headline addition is something the community has been quietly asking for since the early days: built-in backup commands. The Backup CLI: What’s New Before 3.8, backing up your OpenClaw configuration meant manually copying files and hoping you remembered everything. Now, the CLI handles it natively: ...

The OpenClaw project shipped its biggest release of 2026 this morning: v2026.3.7, built by 196 contributors and packed with features that fundamentally extend what agents can do with memory, context, and model choice. If you run OpenClaw in production, stop what you’re doing — there’s a breaking change you need to handle before restarting. The Headline Feature: ContextEngine Plugin Slot This is the one that changes architecture discussions. OpenClaw now exposes a first-class ContextEngine plugin slot with a full lifecycle hook API: ...

Most multi-agent tutorials stop at “here’s how to wire two agents together.” Production systems need more: structured message passing, durable state across restarts, and an audit trail you can debug when something goes wrong at 2am. This guide builds a Planner/Executor/Validator architecture with LangGraph that’s actually ready for production. Architecture Overview The system uses three specialized agents: Planner — Receives a task, decomposes it into steps, publishes to the message bus Executor — Consumes steps from the bus, executes them, publishes results Validator — Checks Executor outputs against criteria, flags failures, loops back to Planner if needed These agents communicate via a structured ACP-style message bus (Pydantic schemas), checkpoint state to SQLite via langgraph-checkpoint-sqlite, and log every message to JSONL for auditability. ...

A high-traction GitHub issue filed against the OpenClaw repository this week could fundamentally change how OpenClaw fits into the broader AI agent ecosystem — if it ships. Issue #28511 proposes building an AcpRuntime plugin that makes OpenClaw’s acpx harness speak the standard Agent Collaboration Protocol (ACP) using JSON-RPC 2.0. The practical implication: OpenClaw would become compatible with every agent in the ACP Registry — currently 19+ agents including Kiro, GitHub Copilot, Cline, Goose, Junie, Qwen Code, and more. ...