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[Release] openclaw/openclaw v2026.6.1-beta.3: openclaw 2026.6.1-beta.3
OpenClaw v2026.6.1-beta.3 introduces significant stability improvements for agent runtimes, CLI tools, and multi-channel delivery across Telegram, WhatsApp, iMessage, Slack, Discord, and Teams. The release features a new Skill Workshop with proposal-based skill creation, externalized plugins (Tokenjuice and Copilot), SQLite-backed state management for better recovery, and enhanced Control UI with improved chat composition and latency tracking. Multiple fixes address tool-call recovery, streaming argument parsing, and process lifecycle management to prevent hanging runs and stale session bindings.
- Agents and CLI runtimes now recover cleanly from interrupted tool calls, stale session bindings, and media delivery retries through improved error handling
- Multi-channel delivery stabilized across 9+ platforms (Telegram, WhatsApp, iMessage, Slack, Discord, Teams, Google Chat/Meet, iOS) with realtime Talk support
- New Skill Workshop enables governed skill creation with proposal lists, revision handoff, searchable file previews, and approval workflows via agent tools
- +7 more key points...
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See all 8 →[Release] openclaw/openclaw v2026.6.1: openclaw 2026.6.1
OpenClaw v2026.6.1 is a stability and reliability release focusing on improved recovery from interruptions, enhanced multi-channel support across messaging platforms, better resource management with bounded timers and retries, and new Skill Workshop features for governed skill creation and review. The release includes SQLite-backed state persistence for iMessage and plugin metadata, expanded provider coverage (MiniMax M3, Copilot Claude 1M), and significant UI/UX improvements in Chat and Control interfaces with streaming optimizations and draft management.
github-actions[bot]
[Release] anthropics/claude-code v2.1.161: v2.1.161
Claude Code v2.1.161 introduces enhanced observability through OTEL metric labels, improves parallel tool execution by allowing independent failures, and fixes critical issues with clipboard handling, authentication policies, and background session management. The release includes UI/UX improvements for agent progress display, MCP connector management, and accessibility features like motion reduction support. Multiple regressions and edge cases are resolved, particularly around git worktrees, file editing in isolated workflows, and telemetry initialization.
ashwin-ant
[Release] langchain-ai/langchain langchain==1.3.3: langchain==1.3.3
LangChain version 1.3.3 introduces improvements to subagent run projection onto typed channels and enhances the HumanInTheLoopMiddleware with interrupt_mode and conditional predicate support. The release includes a dependency bump for langgraph to 1.2.4 and loosens the langgraph version constraint for better compatibility. These changes improve agent orchestration capabilities and middleware flexibility for human-in-the-loop workflows.
github-actions[bot]
MCP Servers
[Release] langchain-ai/langchain langchain==1.3.4: langchain==1.3.4
LangChain version 1.3.4 has been released with improvements to Human-in-the-Loop (HITL) rejection guidance. This patch release follows version 1.3.3 and includes bug fixes and enhancements to the HITL workflow, making it easier for users to handle rejection scenarios in agent-based applications.
github-actions[bot]
Google ADK vs LangChain — Which Should You Build On? #Shorts
This video compares Google ADK v2 and LangChain as frameworks for building AI agents in 2026. Both are production-ready options, but they differ in their strengths and ecosystem integration. The comparison helps developers choose the right framework based on their specific stack and requirements.
Decoding GCP with Ankur
Skills & Tools
Gemini Spark vs. OpenClaw: AI Agent Tool Showdown! #shorts
This video compares Gemini Spark's agent tool capabilities with OpenClaw (Hermes), highlighting differences in functionality and performance. It discusses SuperGrok subscription benefits and explores cost-saving strategies for API usage. The content focuses on helping developers choose the right AI agent tool based on their needs and budget constraints.
Tye Grisel
Google ADK: Build AI Agents Fast! 🤖⚡#GoogleADK #AgenticAI #AIAgents #MachineLearning #BuildWithAI
Google's Agent Development Kit (ADK) is a framework designed to accelerate AI agent development and deployment. It provides developers with tools and abstractions to build, test, and scale intelligent agents efficiently. ADK simplifies the complexity of agent architecture, enabling faster iteration and reducing time-to-market for AI-powered applications.
Kiran Ingale
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