<h2>Must know</h2>
<ul>
<li><strong>India’s smartphone security demands spark industry backlash</strong>: India is proposing 83 new smartphone security standards, including source code access, pre-update notifications, and 12-month device log storage. Major players like Apple, Samsung, and Google are pushing back, calling the requirements unprecedented and invasive, according to Reuters. The Indian IT ministry publicly denies seeking source code, but leaked documents suggest otherwise, creating significant regulatory uncertainty and potential commercial risks for proprietary technology. <a href="https://app.daily.dev/posts/C0BEamxdR" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Meta secures nuclear power for AI infrastructure</strong>: Meta announced partnerships with Vistra, TerraPower, and Oklo to secure up to 6.6 GW of nuclear energy by 2035. This massive investment, detailed in Meta’s official release, aims to provide reliable baseload power for its AI infrastructure and data centers, including the Prometheus supercluster in Ohio. The plan involves extending the life of existing plants and developing new advanced reactors, underscoring the extreme energy demands of scaling AI. <a href="https://app.daily.dev/posts/elp6Y0W2r" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>D-Wave acquires Quantum Circuits for gate-model expansion</strong>: D-Wave Quantum is acquiring Quantum Circuits Inc. for $550 million to integrate annealing quantum computing with error-corrected gate-model technology. This move aims to accelerate the delivery of commercially available gate-model quantum systems by 2026, leveraging Quantum Circuits’ dual-rail error detection and D-Wave’s scalable superconducting control systems. The acquisition, reported by D-Wave, positions the combined entity to offer more robust quantum solutions. <a href="https://app.daily.dev/posts/rdMlkyvEb" target="_blank" rel="noopener nofollow">Read more</a></li>
</ul>
<h2>Good to know</h2>
<ul>
<li><strong>Linus Torvalds uses AI for Python tooling</strong>: Linus Torvalds released AudioNoise, an open-source guitar pedal simulator, using Google’s Antigravity AI-assist IDE for its Python visualization tool, showcasing practical AI coding adoption by a major open-source leader. <a href="https://app.daily.dev/posts/fe8LDMARY" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Python 3.14 to boost performance and concurrency</strong>: Python 3.14, expected in 2026, will introduce lazy imports for performance gains and official free-threading support, aiming for up to 10x speedups in parallel workloads. <a href="https://app.daily.dev/posts/quf6PiAcD" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>AI-powered merge conflict resolution for Linux kernel</strong>: LLMinus is developing AI-powered merge conflict resolution for the Linux kernel, with an updated RFC patch series exploring how large language models can automate this critical development workflow. <a href="https://app.daily.dev/posts/JxR62Z8wv" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>New quantum initiative reauthorization act introduced</strong>: U.S. lawmakers introduced the National Quantum Initiative Reauthorization Act to extend federal coordination of quantum research through 2034, establishing new NIST quantum centers and expanding NASA’s quantum programs. <a href="https://app.daily.dev/posts/fWH0q50O1" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Monarch Quantum unveils integrated photonics for quantum hardware</strong>: Monarch Quantum launched with Quantum Light Engines, integrated photonics systems designed to consolidate optical components for quantum computing, sensing, and communications, using robotic assembly and machine learning. <a href="https://app.daily.dev/posts/VcJjUEDTv" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>InfluxDB 3.8 enhances Linux and Kubernetes support</strong>: InfluxDB 3.8 introduces Linux service management, a beta Helm chart for Kubernetes, and smarter Ask AI features, focusing on operational maturity and easier deployment for enterprise users. <a href="https://app.daily.dev/posts/J0U8XsutD" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Firefox 147 fixes 20-year-old Linux bug</strong>: Firefox 147 now supports XDG Base Directory Specification on Linux, organizing config files into standard locations, alongside improved GNOME rendering and AMD GPU video playback performance. <a href="https://app.daily.dev/posts/lvJEba0su" target="_blank" rel="noopener nofollow">Read more</a></li>
</ul>
<h2>Bullshit police</h2>
<ul>
<li><strong>AI code generation: 70-90% of production code, 100% of the hype</strong>: Apparently, AI code generation tools now create 70-90% of production code, according to some unnamed report. Developers are told to adapt or fall behind, treating AI as ‘core infrastructure’ rather than a pilot project. The article, which conveniently lacks any actual data or named sources, suggests we just give AI full access to our tooling and trust the process. What could possibly go wrong? <a href="https://app.daily.dev/posts/LeN1TdPNx" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>GenAI project failures: blame the infrastructure, not the magic</strong>: An anonymous expert claims 80% of GenAI projects fail, not because the AI isn’t magical enough, but due to ‘lack of production-ready infrastructure.’ The solution? More folders for config, LLM client abstraction, and prompt versioning. So, it’s not the AI’s fault it’s hallucinating credit card numbers; it’s your fault for not having a proper ‘error handler’ folder. Got it. <a href="https://app.daily.dev/feed-by-ids?id=ExsMXw27a&amp;id=yocwu10Ql" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Prompt engineering won’t fix your architectural dumpster fire</strong>: Turns out, ‘prompt engineering’ isn’t a magic wand for bad software architecture. When AI systems fail, it’s usually because they’re faithfully executing within your already broken abstractions, inconsistent data models, and scattered business logic. As InfoWorld points out, LLMs just amplify the architectural debt you’ve been ignoring. So, maybe fix your actual code before you expect AI to make it ‘predictable and boring.’ <a href="https://app.daily.dev/posts/ioJPO54WS" target="_blank" rel="noopener nofollow">Read more</a></li>
</ul>
