A few major use cases for agentic coding for me: 1. Adhoc data visualizations. Anytime I have a question that can be answered quantitatively, I generate some code to make a plot. 2. Adhoc data annotation UIs. In ML, "make your own dataset" is often the answer, and that used to
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AI performance varies: smart earlier, slow and dumb in evening
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Yeah I am usually in bypass but it was soooo slow and dumb this evening, earlier today so smart, maybe it's EU timezone evening and US wakes up or they moved to Colossus and it's not working well yet
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AI agent autonomously fixes production bug
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3/ Bug Sensor
— Charly Wargnier (@DataChaz) 7 mai 2026
An application crashes in production.
The sensor packages the error data, routing it to Claude Code, which analyzes the issue and drafts the PR fix.
Prod bug → Error signal → Agent fix
Your system practically heals itself! pic.twitter.com/r9ArAen2Dw3/ Bug Sensor An application crashes in production. The sensor packages the error data, routing it to Claude Code, which analyzes the issue and drafts the PR fix. Prod bug → Error signal → Agent fix Your system practically heals itself!
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AI agents autonomously audit codebases
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2/ X Sensor
— Charly Wargnier (@DataChaz) 7 mai 2026
Turning industry chatter into direct value.
A senior engineer posts an optimization trick.
The sensor formats the context, and your agent autonomously applies it to audit your current codebase.
Post → Signal → Codebase review
That's continuous intelligence… pic.twitter.com/5owVTgpl1k2/ X Sensor Turning industry chatter into direct value. A senior engineer posts an optimization trick. The sensor formats the context, and your agent autonomously applies it to audit your current codebase. Post → Signal → Codebase review That's continuous intelligence
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Autonomous AI agents capture free game opportunities
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1/ Deal Sensor
— Charly Wargnier (@DataChaz) 7 mai 2026
A perfect example of autonomous opportunity capture.
A limited-time free game drops online.
The sensor emits the state change, and the agent takes immediate action.
Free game → Sensor catches signal → Agent auto-claims it
Proactive agents never miss a window! pic.twitter.com/Xvz7VvlOOU1/ Deal Sensor A perfect example of autonomous opportunity capture. A limited-time free game drops online.
The sensor emits the state change, and the agent takes immediate action. Free game → Sensor catches signal → Agent auto-claims it Proactive agents never miss a window! -
World2Agent Open-Sources AI Agent Perception Layer
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🚨 THE MISSING LAYER IN AI AGENTS IS NOW OPEN-SOURCE
— Charly Wargnier (@DataChaz) 7 mai 2026
If MCP gave AI agents hands to work, @MachinePulse_AI's World2Agent gives them eyes to see.
…and they've officially made it open-source.
The current agent ecosystem has a critical flaw.
They've equipped models with… pic.twitter.com/TlMSGxKwuTTHE MISSING LAYER IN AI AGENTS IS NOW OPEN-SOURCE If MCP gave AI agents hands to work, @MachinePulse_AI
's World2Agent gives them eyes to see. …and they've officially made it open-source. The current agent ecosystem has a critical flaw. They've equipped models with -
The Emerging AI Platform War and Infrastructure Shifts
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the ai platform war is coming@kieranklaassen and i recorded a quick dispatch from code with @claudeai on the xAI compute deal, managed agents, and why anthropic is turning their api into a full cloud infrastructure for developers: pic.twitter.com/CCOs5G4VYl
— Dan Shipper 📧 (@danshipper) 7 mai 2026the ai platform war is coming @kieranklaassen and i recorded a quick dispatch from code with @claudeai on the xAI compute deal, managed agents, and why anthropic is turning their api into a full cloud infrastructure for developers:
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Demo at OpenAI event London 2025: model trained on UN translators
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Fun fact, I saw a demo of this at an OpenAI event in London in something like October 2025 – over half a year ago. They told us that they trained the model on UN synchronised translators. Not sure why it took so long to release it https://t.co/lwoaaZy7eB
— Peter Gostev (@petergostev) 7 mai 2026Fun fact, I saw a demo of this at an OpenAI event in London in something like October 2025 – over half a year ago. They told us that they trained the model on UN synchronised translators. Not sure why it took so long to release it
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AI Hallucinations: The Real Trust Bottleneck for Agents
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Most AI products are still one confident hallucination away from embarrassing your entire company.
— God of Prompt (@godofprompt) 7 mai 2026
Everyone wants “agents.”
Nobody wants to admit the real bottleneck is trust.
If Giga really got hallucinations down to ~1%, that’s not a feature.
That’s the difference between… https://t.co/HTiJhhJvf1Most AI products are still one confident hallucination away from embarrassing your entire company. Everyone wants “agents.” Nobody wants to admit the real bottleneck is trust.
If Giga really got hallucinations down to ~1%, that’s not a feature. That’s the difference between -
Optimizing AI model inference with CUTLASS stack
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Perplexity runs on NVIDIA. Nice breakdown from the team on how they’re using the CUTLASS Python stack to optimize their models for inference