Large language models in global health - Nature
<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5kV1RtelJhcEUtX05mZ28taHRrU0g0MmRpQzlzY3pWc0ZVeURCbU96dnNZMXRVSGl5QW5uX0E0ME1ENHBoemhIV2x3UHY3bXN5emk5VWd5OHNlOThwZmg4?oc=5" target="_blank">Large language models in global health</a> <font color="#6f6f6f">Nature</font>
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The Fallback That Never Fires
<p>Your agent hits a rate limit. The fallback logic kicks in, picks an alternative model. Everything should be fine.</p> <p>Except the request still goes to the original model. And gets rate-limited again. And again. Forever.</p> <h2> The Setup </h2> <p>When your primary model returns 429:</p> <ol> <li>Fallback logic detects rate_limit_error</li> <li>Selects next model in the fallback chain</li> <li>Retries with the fallback model</li> <li>User never notices</li> </ol> <p>OpenClaw has had model fallback chains for months, and they generally work well.</p> <h2> The Override </h2> <p><a href="https://github.com/openclaw/openclaw/issues/59213" rel="noopener noreferrer">Issue #59213</a> exposes a subtle timing problem. Between steps 2 and 3, there is another system: <strong>session model recon
I Asked AI to Do Agile Sprint Planning (GitHub Copilot Test)
<p>AI tools are getting very good at writing code.</p> <p>GitHub Copilot can generate entire functions, review pull requests, and even help refactor legacy codebases. But software development isn’t just about writing code.</p> <p>A big part of the process is <strong>planning the work</strong>.</p> <p>So I decided to run a small experiment:</p> <p><strong>Can AI actually perform Agile sprint planning?</strong></p> <p>Using <strong>GitHub Copilot inside Visual Studio 2026</strong>, I asked AI to review a legacy codebase and generate a <strong>Scrum sprint plan for rewriting the application</strong>.</p> <p>The results were… interesting.</p> <h1> Watch Video </h1> <h2> <iframe src="https://www.youtube.com/embed/ErwuATHHXw4"> </iframe> </h2> <h1> The Setup </h1> <p>The experiment was intention
OpenSpec (Spec-Driven Development) Failed My Experiment — Instructions.md Was Simpler and Faster
<p>There’s a lot of discussion right now about how developers should work with AI coding tools.</p> <p>Over the past year we’ve seen the rise of two very different philosophies:</p> <p><strong>1. Vibe Coding</strong> — just prompt the AI and iterate quickly<br> <strong>2. Spec-Driven Development</strong> — enforce structure so AI understands requirements</p> <p>Frameworks like <strong>OpenSpec</strong> are trying to formalize the second approach.</p> <p>Instead of giving AI simple prompts, the workflow looks something like this:</p> <ul> <li>generate a proposal</li> <li>review specifications</li> <li>approve tasks</li> <li>allow the AI agent to execute the plan</li> </ul> <p>In theory, this should produce <strong>better and more reliable code</strong>.</p> <p>So I decided to test it on a r
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Walmart expands AI-powered shopping — and checkout — with Google Gemini - axios.com
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Google’s Gemini AI is getting a bigger role across Docs, Sheets, and Slides - The Verge
<a href="https://news.google.com/rss/articles/CBMiiAFBVV95cUxPMHdiN2dqSUwyNDlzaVRCU1RUSW1iYnZZdmgxVXJtUm9JR2pqbE5LQ3V3eWRZV3htREYwNDMwaThfYVd2RjhhQUZqZWRtVHd3aFhuOFRZMDNRbGQwUmFMTm0wckpLMThLTlZyU2RlX1ZfaGI2WThSMVEtLU9qZXlPSS11dzREUnBv?oc=5" target="_blank">Google’s Gemini AI is getting a bigger role across Docs, Sheets, and Slides</a> <font color="#6f6f6f">The Verge</font>
The Fallback That Never Fires
<p>Your agent hits a rate limit. The fallback logic kicks in, picks an alternative model. Everything should be fine.</p> <p>Except the request still goes to the original model. And gets rate-limited again. And again. Forever.</p> <h2> The Setup </h2> <p>When your primary model returns 429:</p> <ol> <li>Fallback logic detects rate_limit_error</li> <li>Selects next model in the fallback chain</li> <li>Retries with the fallback model</li> <li>User never notices</li> </ol> <p>OpenClaw has had model fallback chains for months, and they generally work well.</p> <h2> The Override </h2> <p><a href="https://github.com/openclaw/openclaw/issues/59213" rel="noopener noreferrer">Issue #59213</a> exposes a subtle timing problem. Between steps 2 and 3, there is another system: <strong>session model recon
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