The roadmap to building AI agents is becoming clearer Learn LLMs & prompting Add tools & APIs Implement memory Build workflows Orchestrate multi-agent systems Deploy, monitor, improve Great agents are not just intelligent.
They are connected, stateful,
AUTOMATION
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AI Agent Development Roadmap: From LLMs to Orchestration
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Context Hub Launched for AI Agent Context Management
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We launched Context Hub as a way to manage skills, AGENTS.md files, and other context files an agent might need You can easily use it as a virtual filesystem in deepagents See this video for more info!
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Fleet AI Agents Now Capable of Secure Code Execution and Analysis
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Fleet agents can now securely write and run code. With computer use in LangSmith Fleet, agents get isolated execution environments. Analyze data, transform files, generate & write code, and run shell commands all within a secure virtual computer. Now in public beta.
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Starbucks learns that AI can’t even count
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Starbucks learned the hard way: you literally can't even trust (current) AI to count.
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Google Gemini Projects and Workflow Agents for Teams
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GOOGLE 🔥: Gemini for Business will get a new experience for collaborative Projects, where teams can work in a shared environment.
— 🚨 AI News | TestingCatalog (@testingcatalog) 27 mai 2026
Besides that, Google is rolling out Workflow Agents that can work on automation tasks across various apps. The same functionality is now available… pic.twitter.com/kkVRgh4F14GOOGLE : Gemini for Business will get a new experience for collaborative Projects, where teams can work in a shared environment. Besides that, Google is rolling out Workflow Agents that can work on automation tasks across various apps. The same functionality is now available
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Codex for real-time meeting transcription and Q&A
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Codex for transcribing and answering questions about a meeting in real time:
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Lyft’s AI Assist: How Ops Teams Ship Agents and Iterate with Prompts
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Today, Ops teams, VoC leads, and PMs are now writing prompts, shipping agents, and iterating. No MLEs required. Read @Lyft
’s guest blog to see how they improved AI Assist, why they treated prompts like product specs rather than code comments, + what’s next. -
Lyft Enhances AI Agent Development with LangGraph and LangSmith
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@Lyft accelerated agent development from 6 months to just a few weeks with LangGraph and LangSmith. Hallucinations decreased by 20% AI Resolution rate up by 16%
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LangSmith Engine Automates AI Agent Improvement Cycles
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Improving your agent has been a manual process of:
— LangChain (@LangChain) 27 mai 2026
✅ Reading traces
✅ Looking for patterns
✅ Writing evals
✅ Creating fixes
Now, LangSmith Engine runs that cycle for you. pic.twitter.com/YsFn37mtA3Improving your agent has been a manual process of: Reading traces Looking for patterns Writing evals Creating fixes Now, LangSmith Engine runs that cycle for you.
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Highly rated new book on generative AI applications with LLMOps
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Highly rated new book from @PacktPublishing @PacktDataML … "Architecting Generative AI Applications: Build, deploy, and scale production-ready GenAI systems with LLMOps best practices" See it at https://
amzn.to/3Pv4dyF