Google led I/O 2026 with a cheap, fast Gemini Flash instead of a frontier behemoth, and everyone read it as conceding the top of the market. Wrong read. Cheap isn't a model strategy, it's a silicon strategy. Google owns every layer from the TPU to the search box, which is why it can give intelligence away while its rivals rent the compute to compete with it, some of them for $40 billion.
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OpenAI just shipped their first model on non-Nvidia hardware. GPT-5.3-Codex-Spark runs on Cerebras wafer-scale silicon at 1,000 tokens per second. The AI coding war is now a chip war.
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Top 3 intelligence. Top 5 price. Top speed. Flash beats Pro on SWE-bench and changes the economics of agentic workflows.
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Anthropic's first acquisition ever. A $183B AI company just bet their fastest-growing product on a JavaScript runtime. Claude Code hit $1B in 6 months - built on Bun.
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Google's Gemini 3 just broke every benchmark that matters. What that means for the 'AI has hit a wall' narrative, and where it actually helps.
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The latest C# release continues its quiet war on ceremony with field-backed properties, extension members, and smarter spans. Here's what matters and what doesn't.
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I fought to move teams from npm to pnpm. I was all in. Then a friend said 'lol use bun' and I converted every project within days. Here's why I'll never go back.
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Converting text to images for 20x token compression. Interesting research or production-ready breakthrough? A critical look at the trade-offs.
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Real-time AI generation vs curated libraries: lessons from building the same product twice with radically different architectures.
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Real lessons from shipping multiplayer games with Firebase: what works for small groups, where it breaks down, and the scalability limits you need to know upfront.
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Building realistic voxel explosion effects in Unity that break objects into their constituent cubes with physics and particle systems.
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Building cross-platform image resizing middleware for ASP.NET Core using SkiaSharp before mature libraries existed.
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