THE AI PULSEEN

The Pulse — July 31, 2026

The signals that entered our radar, organized with sources and context to understand what changed.

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The Pulse — July 31, 2026
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  1. 01OpenAI — Advancing the price-performance frontier with GPT-5.6

    GPT-5.6 pricing drop turns model routing into the product

    SUGGESTED EDITORIAL ANGLE

    “The winning AI stack is now a team, not a single model: use the genius for decisions and the cheap model for execution.” Show the planner → executor → verifier loop.

    Open original source ↗
  2. 02DeepSeek — Change log / V4-Flash update

    DeepSeek V4-Flash public beta: another serious coding-agent executor

    SUGGESTED EDITORIAL ANGLE

    “DeepSeek just made its fast model the coding-agent bet—what should you test before swapping it into Codex?” Emphasize that vendor benchmarks are a starting point, not a purchase order.

    Open original source ↗
  3. 03Google DeepMind — Gemini Robotics 2

    Gemini Robotics 2 moves from robot arms to whole-body agents

    SUGGESTED EDITORIAL ANGLE

    “The real robotics leap is not a prettier humanoid demo—it’s a three-layer agent stack: reason, act, adapt locally.” Use the watering-can task as the visual narrative.

    Open original source ↗
  4. 04Google Chrome Security — Stronger with every update

    Chrome says AI found and helped fix more than a thousand security bugs in two releases

    SUGGESTED EDITORIAL ANGLE

    “This is what mature agentic coding looks like: not an unrestricted bot, but separate finder, fixer, critic and test agents inside a constrained environment.” Great counterweight to reckless ‘give the agent root’ content.

    Open original source ↗
  5. 05Murphy Randle — €11 for 18 Minutes: My GreenPT Experiment Hit 10M Input Tokens

    Context caching can make the same agent session cost 100× less

    SUGGESTED EDITORIAL ANGLE

    “Your agent isn’t expensive because it thinks too much—it may be paying to re-read its own history.” Explain the repeated-context tax with one simple whiteboard diagram.

    Open original source ↗
  6. 06arXiv — Intelligence per Watt: Measuring Intelligence Efficiency of Local AI

    “Intelligence per watt” is a better local-AI metric than tokens/sec

    SUGGESTED EDITORIAL ANGLE

    “Stop asking whether local AI is as smart as the cloud. Ask: which 70% of your tasks should never leave your laptop?” Frame it as privacy, latency and power—not ideology.

    Open original source ↗
  7. 07arXiv — ParallelKittens

    The unglamorous bottleneck: communication between GPUs

    SUGGESTED EDITORIAL ANGLE

    “Why buying more GPUs does not automatically make your AI faster.” Explain the ‘workers waiting on each other’ analogy before showing the numbers.

    Open original source ↗
  8. 08AI Builder Club — open-agent-teams SKILL.md

    Upstream implementation pattern: an open protocol for heterogeneous agent teams

    SUGGESTED EDITORIAL ANGLE

    “Multi-agent systems fail at the handoff, not the intelligence.” Demonstrate why a durable result file and completion signal beat a chat-only orchestration.

    Open original source ↗
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