7- THE STEELMAN DEBATE MACHINE WITH CONSTITUTIONAL AI You are a debate partner operating under the constitutional principle of intellectual honesty from Anthropic, specifically practicing steelmanning, where instead of attacking the weaker version of the opposing argument, you build the MOST
AGENTS
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Building Autonomous 24/7 Agents with Shubham Saboo
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How to Build an Autonomous 24/7 Agent (feat. Shubham Saboo) nitter.net/i/broadcasts/1dJrPEMkg…
→ View original post on X — @saboo_shubham_, 2026-03-30 17:18 UTC
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Sycamore: New Enterprise Agent OS from Sri’s Team
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Sri is building Sycamore: an agent OS for the enterprise. Great team and great product concept. Can't wait for the launch 🙂
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Evaluating LLMs for Long-Context Tool Calling and Agentic Reliability
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Which models would you recommend for longer context tool calling? Are there any benchmarks for that which you find credible? I've not found a local model with tool calling good enough for me to trust with Claude Code or Codex, but I may not have been looking at the right options
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PokeeClaw: Securing Local AI Assistants with Isolated Sandbox
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OpenClaw has proven that local AI assistants have product-market fit. But the big issue with them has been security.
— François Chollet (@fchollet) 30 mars 2026
The team at @Pokee_AI is fixing it with PokeeClaw: works like OpenClaw, but with in a secure sandbox architecture with isolated environments, approval workflows,… https://t.co/7Q5cmQJbzhOpenClaw has proven that local AI assistants have product-market fit. But the big issue with them has been security. The team at @Pokee_AI is fixing it with PokeeClaw: works like OpenClaw, but in a secure sandbox architecture with isolated environments, approval workflows,
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Jensen Huang at Interrupt: Enterprise Agents and LangChain Partnership
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Jensen Huang is coming to Interrupt. May 13-14 in SF. Join Jensen and Harrison for a fireside chat to learn where enterprise agents are headed. We'll dive into the LangChain x @nvidia partnership and how Deep Agents, NVIDIA Nemotron models, and the NVIDIA Agent Toolkit enable production-grade claws for the enterprise. Get tickets: interrupt.langchain.com/
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Natural Language Agents Research Paper Pan et al
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Natural-Language Agent Harnesses Pan et al.: https://
arxiv.org/abs/2603.25723 #ArtificialIntelligence #AIAgents -
AI agents integration in modern workflows
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These impacts were measured before practical agents (like Claude Code) and companies are still early in figuring out how to incorporate AI into their workflows.
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LangSmith Experiments Detail View Redesigned for Better Debugging
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The hardest part of debugging an AI agent isn't knowing it failed–it's knowing why.
— LangChain (@LangChain) 30 mars 2026
We rebuilt the detail view in LangSmith Experiments from the ground up to answer that question faster.
Next time you click and inspect any experiment results, you will find:
* Less clutter
*… pic.twitter.com/x50OxCJxnWThe hardest part of debugging an AI agent isn't knowing it failed–it's knowing why. We rebuilt the detail view in LangSmith Experiments from the ground up to answer that question faster. Next time you click and inspect any experiment results, you will find:
* Less clutter
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Running Operational Workloads with Lakebase, Databricks Apps, Agents
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See how to run operational workloads on the lakehouse using Lakebase, Databricks Apps, and Agent Bricks. This BrickTalks session covers how teams are building data apps and AI agents on top of serverless Postgres to automate workflows and make data usable in real applications.