Every millisecond matters. We’re open sourcing the tokenizer we built and deployed on production; that’s far efficient than huggingface and sentencepiece.
CODE
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Fleet Agents Now Execute Code for General Tasks
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Fleet agents now come with a computer! They can write and execute code, which is helpful for general purpose tasks beyond coding
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AI Agent Development Roadmap: From LLMs to Orchestration
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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, -
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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AI Safety & Agent Security Tools: Claude, Google, Microsoft, OpenAI
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Doc of Claude Code plug-in: https://
code.claude.com/docs/en/securi
ty-guidance
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Google AI Threat Defense blog: https://
cloud.google.com/blog/products/
identity-security/introducing-google-ai-threat-defense
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Microsoft's RAMPART Blog: https://
microsoft.com/en-us/security
/blog/2026/05/20/introducing-rampart-and-clarity-open-source-tools-to-bring-safety-into-agent-development-workflow/
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OpenAI's Daybreak website: https://
openai.com/daybreak/
Perplexity's Bumblebee: https://
perplexity.ai/hub/blog/perpl
exity-is-open-sourcing-bumblebee
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AI Encoder Tokenizer Performance: 5× Latency Improvement
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At production input lengths, the encoder cuts p50 latency by roughly 5× vs. HuggingFace tokenizers, 2× vs. SentencePiece C++, and 1.5× vs. IREE C. At 514 tokens, it runs in 63 µs with zero heap allocations.
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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. -
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 -
Ruflo Transforms Claude Code into Multi-Agent System
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One command just turned Claude Code into 100 agents that learn. Claude Code is powerful, but it runs as a single agent. No shared memory, no parallel delegation, no cross-task coordination. Ruflo, formerly claude-flow, fixes that with one command. A single npx init spins