⚡Coding is Free and Power Scarce. Is there a Solution?Plus: AI Is Improving at Math Problems That Stumped Humans for Decades.
Hello Team, Happy Valentine’s Day. Code is now advancing so fast that it’s not just writing software, it’s improving itself and autonomously creating apps and platforms. As Chinese AI models continue closing the gap with Silicon Valley and AI systems grow stronger at math and reasoning, development is accelerating exponentially. The real constraint is no longer talent or ideas, but who controls the compute, data, and capital needed to build and scale it all.
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Coding is Free and Power Scarce
This week’s signals from Spotify, Elon Musk, and insiders at OpenAI and Anthropic all point to the same reality: “Software is becoming frictionless.” Spotify says its top engineers haven’t written code since Dec 2025, shipping 50+ features in 2025 using AI systems that deploy fixes from a phone, while Musk predicts that by 2026–2027. As we shared earlier, code is coding itself, and it will not change anytime soon. AI will bypass programming languages entirely and turn human intent directly into optimized machine code, shrinking the idea-to-product cycle from months to minutes. At the same time, AI researchers are resigning and warning of existential risks as capabilities scale faster than regulation can keep pace, even as valuations surge toward $380B and political spending rises. The common denominator is clear, and it’s that execution is being commoditized, productivity per worker is rising 5x–20x+, and power is concentrating around data, compute, and distribution. Over the next 1–3 years, most software will be built by autonomous agents; within 5 years, human coding will be a niche, with companies of five doing the work of hundreds. The upside is massive, cheaper innovation, faster science, and lower startup costs, but the downside is equally large: rapid job displacement, monopolized infrastructure, large-scale manipulation, and fragile systems humans no longer fully understand. In the AI economy, skill is becoming abundant, code is dissolving, and the real bottleneck is shifting to judgment, ethics, and who controls the machines that now build everything. China’s AI Models continue to close the gap and undercut Silicon Valley.China’s AI race is accelerating as MiniMax launched its new open-source flagship model M2.5, positioning it as a low-cost alternative to U.S. leaders like Anthropic for coding and agentic tasks, a move that helped push MiniMax’s Hong Kong-listed shares up nearly 10%. The release is part of a broader surge in Chinese models gaining global traction, including Zhipu AI’s GLM-5, praised for coding performance, and Moonshot AI’s Kimi K2.5, which recently became the most-used model on OpenRouter. Together, these launches signal that China is rapidly closing the gap in high-quality, low-cost AI models, increasing competitive pressure on U.S. providers and giving developers more affordable options worldwide. 📚Learning CornerDashboard Builders
AI Is Improving at Math Problems That Stumped Humans for Decades.AI is starting to meaningfully assist mathematicians by rapidly searching literature, combining known results, and occasionally generating valid proofs, helping resolve around 100 long-standing Erdős problems since late 2025. Researchers at OpenAI and Google DeepMind are increasingly using LLMs as research assistants that can cut weeks of work to days, though they still produce large volumes of confident but incorrect results. A new benchmark called First Proof is testing whether AI can solve unpublished problems, with mixed early outcomes. While no major journal has yet published an AI-assisted proof, many experts expect 2026 to be the turning point, positioning AI as a powerful collaborator rather than a replacement for human mathematicians. 🧰 AI Tools of The DayMath Help
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Friday, February 13, 2026
⚡Coding is Free and Power Scarce. Is there a Solution?
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