Traditional inference wasn’t built for agentic coding. Agentic tools make hundreds of API calls per coding session, often with recomputed context, creating bottlenecks that drive up cost per token. NVIDIA Dynamo rebuilds the stack for agents with: → KV-aware routing →
CODE
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HF Platform Becomes Hub for AI Agent Collaboration
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We built HF for AI builders collaboration, fun to see it's increasingly becoming the place for agent collaboration! This morning I'm sending my ml-intern to participate in the @OpenAI Parameter Golf challenge which goal is to train the best language model that fits in a 16MB
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ChatGPT’s Evolution: How Codex Surpassed Its Predecessor
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ChatGPT walked so that Codex could run.
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AI Agents Dramatically Accelerate Task Breakdown and Code Generation
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I tested it today building causal agents. It was spectacular at breaking tasks. It wrote beautiful code. Amazing vibe coding tool. I also asked it to write the paper at the end and it did ok. With a bit of guidance, one can now do in a day what it used to take me about two weeks
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BytePlus Launches CodingPlan Developer Initiative Q2 2026
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https://
byteplus.com/en/activity/co
dingplan?utm_source=Developer_KOL&utm_medium=kol&utm_campaign=BP-Global-Codingplan&ArkClaw-publish-Q2APRFY26&utm_term=kimmonismus&utm_content=codingplan
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GLM-5.1 BytePlus: Opus-class Performance at 5x Lower Cost
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GLM-5.1 is now on BytePlus's Coding Plan — and the case is straightforward: Opus-class performance, 8-hour autonomous task loops, works natively in Cursor and Claude Code, 6 top models with smart routing. All at roughly 5x lower cost than http://
Z.ai official pricing. -
Security research evaluates Claude Code’s auto mode risk management
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How secure is the new "auto mode" for AI coding assistants? Researchers from HKUST and ETH Zurich put Claude Code's permission system to the test. They found it misses dangerous actions when a task's risk is ambiguous. In a stress test, it missed 81% of risky actions, far
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ML Workflow: Data Understanding to Deployment and Monitoring
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ML isn’t magic — it’s a workflow. 1. understand data 2. choose right algorithm 3. train 4. test 5. optimize 6. deploy + monitor + retrain The winners are the teams who run this loop consistently. #MachineLearning #AI #DataScience #MLops
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GPT 5.5 emerges as most reliable coding model
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pretty sure, maybe just not as reliable. GPT 5.5 is the most reliable coding model.