AI Dynamics

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  • Smart AI coordinates cheaper models to boost performance and cut cost
    Smart AI coordinates cheaper models to boost performance and cut cost

    Claude just sabotaged its own business model (and it did it on purpose) Now the smart AI (Opus) can tell the cheap AI (Sonnet or Haiku) what to do, and the cheap AI executes it perfectly The result:
    > +2.7% performance
    > -12% cheaper It's like Opus performance without

    → View original post on X — @nicos_ai

  • Scrapling AI Agent Fixes Brittle Bot Web Automation
    Scrapling AI Agent Fixes Brittle Bot Web Automation

    Unleash your AI agent on the open web right now. @Scrapling_dev just smashed through 35k on GitHub Here is exactly why it’s the absolute best engine for modern agents. It finally fixes the dreaded "Brittle Bot" syndrome. When a frontend dev changes a CSS selector,

    → View original post on X — @datachaz

  • OpenClaw: Non-Technical Users’ First Contact with Agent Models

    Someone recently suggested to me that the reason OpenClaw moment was so big is because it's the first time a large group of non-technical people (who otherwise only knew AI as synonymous with ChatGPT as a website) experienced the latest agentic models. [Translated from EN to English]

    → View original post on X — @karpathy, 2026-04-09 20:38 UTC

  • Understanding AI Agents: Components and Orchestration Explained

    A simple way to think about AI agents: LLM = reasoning Tools = actions Memory = context Orchestration = the loop The first three are components. The last one is what makes them an agent.

    → View original post on X — @akshay_pachaar, 2026-04-09 20:21 UTC

  • AI Capability Gap: Free Models vs Frontier Agentic Systems

    Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are. staysaasy (@staysaasy) The degree to which you are awed by AI is perfectly correlated with how much you use AI to code. — https://nitter.net/staysaasy/status/2042063369432183238#m

    → View original post on X — @karpathy, 2026-04-09 20:10 UTC

  • Global Robotics Community Directory Worldwide

    More accurately this is everyone I can find in robotics world wide. 🙂 Not just Bangalore.

    → View original post on X — @scobleizer

  • DeepAgents vs LangChain: Agent Framework Comparison Guide

    great q! deepagents has more "batteries included", which langchain v1 is a very minimalistic agent harness if you are doing more complex workflows (eg claude code for X) -> deepagents if you want something simple -> langchain both are customizable with middleware

    → View original post on X — @hwchase17

  • Open Standards for AI Agents and Memory Access Requirements

    i agree but there are some open standards (agents.md, skills) and you at least need to be able to access the memory

    → View original post on X — @hwchase17

  • Linq API enables FaceTime video support for AI agents

    FaceTime video support for AI agents through Linq’s API is now in early preview. Your AI assistant, personal trainer, or therapist – available to users through native apps like FaceTime and iMessage. Existing customers like @pika_labs are already building on it. No new apps needed 📈

    → View original post on X — @scobleizer, 2026-04-09 19:54 UTC

  • Cabinet: An Open Source Clone of Claude Managed Agents

    Someone already built an open source version of Claude Managed Agents. It's called Cabinet. The gap between official release & open source clone keeps getting shorter. [Translated from EN to English]

    → View original post on X — @ceobillionaire, 2026-04-09 19:45 UTC