<h2>Must know</h2>
<ul>
<li><strong>Anthropic and OpenAI drop new models, AWS invests big in AI infrastructure</strong>: Anthropic released Claude Opus 4.6 with ‘agent teams’ for parallel tasking and a 1 million token context window, aiming for broader enterprise appeal. Shortly after, OpenAI countered with GPT 5.3 Codex, which reportedly outperformed Opus 4.6 on benchmarks and offers real-time steering. Meanwhile, AWS announced a massive $200 billion investment in 2026 to double its datacenter capacity by 2027, primarily for AI infrastructure, indicating a fierce battle for AI compute dominance. <a href="https://app.daily.dev/feed-by-ids?id=G7Sre82A1&amp;id=Ijw4mCG7B&amp;id=CZUzCGBQG&amp;id=1BAlXIloL" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>AI bot traffic escalates, sparking an arms race with publishers</strong>: AI bots are now a significant portion of web traffic, both for model training and real-time information retrieval for AI agents. This has led to an “arms race” where publishers implement aggressive defenses, and bots develop sophisticated tactics to bypass them. Data from Akamai and TollBit suggests this dynamic is fundamentally reshaping the internet, potentially changing who the primary users are. <a href="https://app.daily.dev/posts/5O2tzW5oh" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Old driver exploit disables modern EDR security</strong>: Threat actors are weaponizing a legitimate, decade-old Windows kernel driver from EnCase to disable endpoint detection and response (EDR) products. This exploit leverages a critical gap in Windows Driver Signature Enforcement, allowing a revoked 2010 certificate to bypass modern verification due to backward compatibility. Huntress detected this during a SonicWall VPN breach, highlighting how legacy flaws can compromise contemporary defenses. <a href="https://app.daily.dev/posts/9GskJTmwz" target="_blank" rel="noopener nofollow">Read more</a></li>
</ul>
<h2>Good to know</h2>
<ul>
<li><strong>Google launches developer knowledge API for AI tools</strong>: Google introduced a Developer Knowledge API and Model Context Protocol (MCP) server in public preview, providing programmatic access to official Google developer documentation to keep AI-powered tools updated. <a href="https://app.daily.dev/posts/X3xuKKIe1" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Databricks introduces MemAlign for LLM evaluation</strong>: Databricks launched MemAlign, a new MLflow framework using dual-memory systems (semantic and episodic) to reduce the cost and latency of training LLM-based judges and maintain evaluation consistency. <a href="https://app.daily.dev/posts/eCdeDEih6" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Microsoft develops LLM backdoor scanner</strong>: Microsoft has developed a scanner to detect malicious triggers and backdoors embedded in open-weight AI models during training, addressing a critical supply chain risk for enterprises. <a href="https://app.daily.dev/posts/O9jvh85A8" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Postgres consolidates database functions with new extensions</strong>: Postgres, through extensions like pg_textsearch, pgvector, and TimescaleDB, is being positioned as a unified solution capable of replacing specialized databases for 99% of companies, reducing operational complexity. <a href="https://app.daily.dev/feed-by-ids?id=QtM7zNGDf&amp;id=VBHSJlMha&amp;id=pKNE7iWlw&amp;id=xEaqTmGWC" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>ScyllaDB integrates vector search with USearch</strong>: ScyllaDB has integrated vector search capabilities using the open-source USearch library, allowing efficient storage and retrieval of vector embeddings alongside structured data. <a href="https://app.daily.dev/feed-by-ids?id=QtM7zNGDf&amp;id=VBHSJlMha&amp;id=pKNE7iWlw&amp;id=xEaqTmGWC" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Enterprise AI agent security solution launched</strong>: Operant AI launched Agent Protector, a real-time security solution for autonomous AI agents, addressing challenges like shadow agent discovery, privilege escalation, and data exfiltration in enterprise environments. <a href="https://app.daily.dev/feed-by-ids?id=0e28QTlYb&amp;id=2vNCw5dB4&amp;id=the2EenMO" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Valve delays hardware due to AI-driven component shortages</strong>: Valve has delayed its Steam Machine, Steam Frame VR headset, and new Steam Controller due to industry-wide memory and storage component shortages, primarily driven by AI data center demand. <a href="https://app.daily.dev/posts/iXYPYa4qJ" target="_blank" rel="noopener nofollow">Read more</a></li>
</ul>
<h2>Bullshit police</h2>
<ul>
<li><strong>Vibe coding is the new prompt engineering, apparently</strong>: We’re told ‘vibe coding’ is the next evolution of prompt engineering, where AI agents autonomously operate within predefined frameworks. So, instead of writing code, developers will now be ‘vibing’ with AI to extend existing codebases. Because, you know, writing specifications for AI to implement is totally different from, say, writing specifications for humans to implement. It’s just more ‘vibe-y.’ <a href="https://app.daily.dev/posts/wypgtlifg" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>Starlink wants to sell you an AI-optimized phone</strong>: SpaceX is reportedly exploring a Starlink-branded mobile phone optimized for AI neural networks, aiming to rival traditional smartphones. Because what we really need is another phone, especially one that’s ‘optimized for AI neural networks’—whatever that means for a handheld device. I’m sure it’ll solve all our problems, right after we figure out how to get global cellular coverage from space. <a href="https://app.daily.dev/feed-by-ids?id=MXFPbStCq&amp;id=afU8DAFQ0" target="_blank" rel="noopener nofollow">Read more</a></li>
<li><strong>The ‘time horizon plot’ for AI progress is still being misunderstood</strong>: Apparently, METR’s ‘time horizon plot’ for AI progress is widely misunderstood, with ‘AI doomsayers and boosters’ misinterpreting its meaning. It measures human task completion time, not AI operational independence, and is based mostly on coding tasks with ‘substantial error bars.’ So, when Claude Opus 4.5 achieved a five-hour time horizon, it didn’t mean it could replace five hours of human work, just that it could do some coding tasks in that timeframe. Shocking, I know. <a href="https://app.daily.dev/feed-by-ids?id=CZUzCGBQG&amp;id=I2PdjppNx&amp;id=IDVrBk7Fu&amp;id=J2cljSBHP" target="_blank" rel="noopener nofollow">Read more</a></li>
</ul>
