AI agents are tackling more and more "human work" But are they benchmarked on the work people actually do? tl;dr: Not really Most benchmarks focus on math & coding, while most human labor and capital lie elsewhere. 📒 We built a database linking agent benchmarks & real-world work Submit new tasks + agent trajectories today 🧵
AGENTS
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Agentic AI: From Generation to Autonomous Orchestrated Systems
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Agentic AI = layered intelligence.
AI/ML → Deep Learning → GenAI → AI Agents → Agentic AI.
From: • Data → Decisions
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• Content → Tasks
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• Autonomous, governed systems.
The future isn’t just generation.
It’s orchestration + memory + planning + safety.
That’s the real -
AI Error Monitoring Agent: Code and Functionality Detailed
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You can find the code for the error monitoring Agent here: https://
github.com/airweave-ai/er
ror-monitoring-agent
… Here's how it works: – Pulls raw errors from Sentry or Azure Log Analytics
– Clusters them semantically by root cause (20 errors become ~4 actual issues)
– Searches GitHub for the exact code -
Open-Source AI Error Monitoring Agent Reduces Downtime by 95%
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Software engineers are going to love this!
— Akshay 🚀 (@akshay_pachaar) 3 mars 2026
I found an open-source error monitoring agent that scans production logs, finds the root cause, and sends a Slack message with full context before you even notice something broke.
Cuts down production downtime by 95%!
Check this: pic.twitter.com/XjWByJVzGFSoftware engineers are going to love this! I found an open-source error monitoring agent that scans production logs, finds the root cause, and sends a Slack message with full context before you even notice something broke. Cuts down production downtime by 95%! Check this:
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Live Training Session on Building AI Agents Announced
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On March 14-15, @PacktPublishing will host a live training session on "Building AI Agents" over the weekend, led by Valentina Alto, Leonid Kuligin, and Lior Gazit Register here: https://
landing.packtpub.com/ai-agents-over
-the-weekend/
… another great offering from @PacktDataML -
Five Pillars of Modern AI: From Answers to Execution
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Modern AI = 5 pillars Generative AI (create) LLMs (reason) RAG (ground + verify) AI Agents (act) Agentic AI (coordinate + scale) We’re moving from AI that answers → AI that executes outcomes. Which pillar wins next? #AI #GenerativeAI #LLMs #RAG
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AI Agents Productivity: Balancing Security and Internal Policies
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AI agents can be game-changers, but how can they increase productivity if they are bound by internal policies? Watch this episode of the AI Security Podcast as @RubrikInc GM of AI Dev Rishi reveals how organizations can unleash their AI agents, without the risk 👉 go.rbrk.co/omquj6
→ View original post on X — @predibase, 2026-03-02 18:09 UTC
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Computer Use moving from research to production with impressive demos
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We're soon going to see Computer Use move from research to production use cases.
— m_ric (@AymericRoucher) 2 mars 2026
Standard Intelligence's demos are stunning, the model seems to have a very natural way of interacting with the computer. It can even drive a car through a webapp!
And Anthropic is working on it as… pic.twitter.com/FeGvZVFNeNWe're soon going to see Computer Use move from research to production use cases. Standard Intelligence's demos are stunning, the model seems to have a very natural way of interacting with the computer. It can even drive a car through a webapp! And Anthropic is working on it as
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4B model rivals 120B on knowledge, ideal for agentic core
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It's crazy that a 4B model can match GPT-OSS-120B **even on knowledge benchs** like MMLU and GPQA! Knowledge was long a limitation of smol models ; not anymore. This 4B could be a good candidate for the "agentic core" model described by @karpathy
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Simplistic Language with AI Agents: A Personal Experience
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One of my favorite things about working with AI agents is that I can use very simplistic language to describe what I want them to work on without fearing I come across an imposter.