The last two weeks in AI have been the most absurd period in the history of tech. I can't even keep up. And that's literally what I do for a living. → Anthropic launched Claude Fable 5, its most powerful model ever made public. At the forefront of
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Adaline reads traffic, writes evals, assembles stronger agent candidates
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Went in expecting another trace dashboard. Instead Adaline reads the production traffic nobody on the team has time to read, clusters it into real behaviors, and writes hundreds of fresh evals against them every day.
— Chubby♨️ (@kimmonismus) 13 juin 2026
Then it assembles the stronger agent candidates and hands… https://t.co/giNgHgeUtKWent in expecting another trace dashboard. Instead Adaline reads the production traffic nobody on the team has time to read, clusters it into real behaviors, and writes hundreds of fresh evals against them every day. Then it assembles the stronger agent candidates and hands
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Databricks introduces Omnigen meta-harness for agent orchestration
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Introducing 𝗢𝗺𝗻𝗶𝗴𝗲𝗻𝘁, a meta-harness to combine, control, and share your agents. The best teams already mix models and harnesses and design loops that drive teams of agents. No single harness can keep up with that alone. So we built the layer above — we call it a
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CUA-Gym automates training data bottleneck for computer-use agents
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The biggest bottleneck for computer-use agents just got automated away.
— AlphaSignal (@AlphaSignalAI) 13 juin 2026
Reinforcement learning broke open math and coding.
But for agents clicking around real software, progress stalled.
The bottleneck was generating training data at scale.
CUA-Gym is a pipeline that… pic.twitter.com/ck87dsJjikThe biggest bottleneck for computer-use agents just got automated away. Reinforcement learning broke open math and coding. But for agents clicking around real software, progress stalled. The bottleneck was generating training data at scale. CUA-Gym is a pipeline that
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Evaluating AI with Rubrics: Beyond Right or Wrong
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How do you evaluate an AI that writes research, diagnoses diseases, or uses tools—when “right or wrong” no longer cuts it? Researchers from Renmin University of China (Liu et al.) surveyed the emerging use of rubrics for LLMs. Rubrics are structured checklists that break down
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Top Claude Code CLI integrations for GitHub superpowers
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The top Claude Code CLI integrations to give you superpowers:
— Akshay 🚀 (@akshay_pachaar) 13 juin 2026
1. GitHub
The repo stops being a folder of files and becomes something the agent actually runs.
It reads and writes issues, PRs, Actions, and releases, so it works the codebase the way an engineer does, not by… https://t.co/vkws3sfWNu pic.twitter.com/s1pES1yZIqThe top Claude Code CLI integrations to give you superpowers: 1. GitHub The repo stops being a folder of files and becomes something the agent actually runs. It reads and writes issues, PRs, Actions, and releases, so it works the codebase the way an engineer does, not by
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GoalOS AGIALPHA Ascension: Experimental Framework for Persistent and Self-Improving AI
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GoalOS AGIALPHA Ascension is an experimental framework for a persistent, goal-oriented, self-improving intelligence system that accumulates capabilities, evidence, and economic value over time. GitHub: https://
github.com/MontrealAI/goa
los-agialpha-ascension
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AA methodology and Nvidia technical blog on agentic coding performance
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AA methodology: https://
artificialanalysis.ai/methodology/ag
entperf
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Nvidia technical blog: https://
developer.nvidia.com/blog/nvidia-ac
hieves-leading-agentic-coding-performance-on-first-agentic-ai-benchmark/
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DeepSeek, GLM, Kimi solve real code issues with reasoning and tools
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(DeepSeek V3.2, GLM 4.7, and Kimi K2.5) prompted to resolve issues in real public code repositories. All trajectories include interleaved reasoning and tool calls. 2/4