Anthropic just dropped research on how people actually use AI agents, and I keep thinking about one number. Claude asks for clarification more than twice as often as humans bother to interrupt it. We're sitting there watching the agent work, and it's already flagged its own uncertainty before we noticed anything was off. The other stats are interesting too: sessions have nearly doubled (25 min → 45+ min), experienced users run full auto-approve 40% of the time. Anthropic calls the bigger pattern a "deployment overhang" where the agents can handle more autonomy than we're giving them. Make of that what you will.

Today in AI:
→ Google's new model lets you dial reasoning up or down
→ AI music generation is now free in Gemini
→ How to create your first track with Lyria 3

Let’s dive in..

Gemini 3.1 Pro delivers. Google's first ".1" increment adds a three-tier thinking system: Low, Medium, and High. Low for quick chatbot responses. Medium for code generation. High for multi-minute deep thinking on hard problems. Previous models were binary and could think hard or don't think. This gives you a dial, and honestly, I'm surprised it took this long for someone to ship it.

What caught my attention is what users built within hours of launch. One developer one-shot an entire Windows 11-style web operating system in a single prompt with start menu, taskbar, window management, the works. Another created a Minecraft-style 3D sandbox with movement controls, block interactions, and crafting logic running directly in the browser. Someone else got a voxel-style Flappy Dragon game from a single complex prompt. The pattern: problems that used to require back-and-forth iteration now land on the first try.

For your team: Test the three-tier system on your actual workloads. Route simple queries to Low, save High for complex reasoning. You might cut costs without sacrificing quality where it matters.

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Lyria 3 is Google's most advanced music model, and it's now live in the Gemini app, free for anyone. Describe a genre, mood, or scenario, and you get a 30-second track complete with vocals, lyrics, and custom cover art generated by Nano Banana.

Here's what makes this interesting. Previous AI music tools either required technical setup (Suno, Udio) or lived in separate apps you had to find and learn. Lyria 3 is just... in Gemini. The same app 750 million people already use. That's a different kind of reach.

The creative controls go deeper than I expected:

Google built in artist protection: if you name a specific artist, Lyria takes it as "broad creative inspiration" rather than mimicking their voice. Every track gets SynthID watermarking so AI-generated music can be identified later. And Dream Track on YouTube is expanding globally, letting creators use Lyria 3 for their videos.

For your team: If you're building content tools or marketing workflows, music just became another modality users will expect. Expect a boom in music driven apps.

Lyria 3 turns text descriptions into 30-second tracks with vocals, lyrics, and cover art. Here's how to try it:

Tips for better results:

💬 ChatGPT ads now hit on your very first message. OpenAI's ad rollout is live with cost to advertise at $60 CPM, $200K minimum buy. If you're on Free, expect sponsored cards below your responses.

🛠️ Microsoft AI Toolkit 0.30 makes agent development feel like real software. The February VS Code update adds a Tool Catalog for discovering agent capabilities, an end-to-end Agent Inspector for debugging, and evaluations as first-class tests.

🍓 Raspberry Pi shares surge 43% on OpenClaw buzz. Turns out you can run AI agents on a $35 single-board computer. OpenClaw on a Raspberry Pi gives you an always-on, energy-efficient agent that handles research tasks in the background and running it on separate hardware means better isolation from your main system.

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