Agent Explorative Policy Optimization for Multimodal Agentic Reasoning
AGENTS
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ProRL: Reinforcement Learning for Proactive Recommendations
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ProRL Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
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MS Office now powered by Perplexity Computer
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MS Office is now powered by Perplexity Computer https://t.co/fIcY5TZ7lT
— Aravind Srinivas (@AravSrinivas) 28 mai 2026MS Office is now powered by Perplexity Computer
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Managed Deep Agents: Features for Agent Creation and Workflow Support
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Managed Deep Agents lets you create a managed Deep Agent without standing up a custom agent server. Our runtime supports: Durable threads Streaming runs Checkpointing Human-in-the-loop workflows
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LangSmith Engine: AI Agent for Agent Optimization
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join us for a behind the curtains look at LangSmith Engine (our agent that helps make your agent better)
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Trend: Fewer Modes, More Autonomous AI Coding Agents
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This is the AI coding agent trend in one sentence: Fewer modes. More autonomy. TRAE is moving from “pick the right coding assistant” to “tell one agent what to build and let it orchestrate the workflow.” Try it here:
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SOLO Agent Dynamically Loading MCPs for Real-World Apps
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The MCP side is especially interesting. TRAE’s unified SOLO Agent can dynamically load configured MCPs as the project evolves, instead of getting boxed into one rigid setup. That matters when you’re building real apps with databases, payments, AI services, and deployment tools.
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AI agents that automate idea-to-deployment workflows
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That’s the real unlock: Less mode-switching.
Less setup friction.
Less “wait, which workflow do I need?” The agent can move from idea → app → tool connections → deployment without forcing you to babysit every step. -
SOLO Agent auto-selects tools and sub-agents
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This sounds small until you actually build with agents. Before, you had to pick the right agent for the right task. Now you just describe what you want. TRAE’s SOLO Agent decides which capabilities, tools, MCPs, and sub-agents to use automatically.
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Commentary on agent retraining inefficiency and funding
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letting agents relearn the EXACT same stuff every run is just burning cash. makes this $3M raise super obvious tbh Uber's CEO @dkhos will be happy to see this 😉
