iFeeling Daily
Daily curated AI insights you can't miss.
From Agent Traces to Agent Simulations — Rustem Feyzkhanov, Snorkel AI
基于生产环境 Agent 轨迹重建私有仿真环境，用于评估成本、延迟和策略合规性，替代依赖公共基准测试的思路。
In the Land of AI Agents, the Verifiers Are King
AI agents are getting more capable, but their failures become more convincing, creating a crisis of verification. Shaukat argues that rigorous verification infrastructure, not just generation, is the key competitive advantage and safety requirement.
Special Topics in Kernels, RL, Reward Hacking in Agents — Daniel Han, Unsloth
This seminar exposes a persistent tension in AI: models shrink dramatically without a proportional loss of intelligence. Daniel Han makes the case that if you make a model 86% smaller, it does not get 86% dumber—it only gets 14% less dumb. That single observation cuts through the hype around ever-larger models and reframes the problem as one of efficiency and infrastructure. At the same time, the talk reveals a darker side of progress: systematic cheating on benchmarks, where models or their harnesses are tuned to game leaderboards rather than solve real tasks.
Imagination Engineering — Y Combinator’s Head of Design on AI’s Next Bottleneck
Eve Bouffard argues that as AI models make technical execution trivial, the true bottleneck for builders becomes generating bold, original ideas. She shares concrete experiments—from streaming raw thoughts to generating a personal website—that reframe creativity as an engineering discipline for the AI age.
Garry Tan: The 400x Leverage of AI-Native Organizations
Garry Tan, president of Y Combinator, explains how AI-native companies achieve massive productivity gains by treating AI as a workforce and encoding roles as markdown skill files. The real leverage lies not in model weights but in how you wire the work, enabling lean teams to operate at scales previously requiring hundreds of employees.
How an AI Agent Became the #1 Contributor in OpenAI’s Hiring Challenge
In OpenAI's Parameter Golf competition, an autonomous AI agent became the top contributor—producing more merged records than any human—forcing us to rethink how we measure research contributions and collaborate with AI systems in practice.
Claude Code and the New Era of Agent-Driven Development
Simon Willison talks with Anthropic's Cat Wu and Thariq Shihipar about how Claude Code is shifting developers from manual coding to managing agent outputs, the rise of proactive agents like Claude Tag, and the importance of safety in autonomous coding workflows.
The Prime Intellect Stack — Will Brown
Will Brown details Prime Intellect's open-source post-training stack, including Verifiers V1, primaril for async RL, and the Lab platform, giving builders modular tools to train and improve their own agentic models without proprietary lock-in.
Prentis, AI Lab by Hoffman, Pincus, Seeks $100M at $1B Valuation
Prentis, a new AI lab for computer use models co-founded by Reid Hoffman and Marc Pincus, is raising $100M at a $1B valuation. It claims its Hive-32B model beats GPT-5.4 and Claude on benchmarks.