New AI tool alert 🛠️, Disney x OpenAI 🎬, GPT‐5.2 drops 🤖

Find every AI opportunity hiding in your workflows

Hi friends, Julie Grumman here. (co-writer of Her AI Drop) 

Something you might not know about me: I've been a tech consultant for over 13 years. For all those years, companies paid me to find opportunities hiding in their workflows. Ways to streamline, automate, and transform how they operate.

I'd inventory their platforms. Map their processes. Identify bottlenecks. Recommend where technology would actually move the needle.

It worked. But it came with the consultant-sized price tag.

Now, with AI, the opportunities are bigger than ever. But most companies still can't see them.

So I built UseCaseGPT.ai

Everything I've learned about spotting AI opportunities is now packaged into a tool anyone can use.

If you've ever asked yourself, "Where should I be using AI in my business?" this is for you.

Here's how it works:

1. Describe any business process where you think there's room to automate or improve. The more detail in your prompt, the better your results.

2. You'll get a visual workflow map (also known as the Value Stream Map in the consulting world, which used to take me HOURS to create), a breakdown of bottlenecks, and prioritized AI recommendations.

3. You walk away knowing exactly where AI fits in your workflows and where to focus first.

Your first analysis is free. No account required. Want to save your work or run unlimited analyses? Beta pricing is just $10/month.

Oh, did I mention Beta users also get a seat at the table? You’ll have direct roadmap input into what we build next. Send me an email ([email protected]) if you want in.

I used to sell this expertise. Now I'm giving away the playbook.

Try it here: UseCaseGPT.ai

AI Quick Takes ⚡

1. OpenAI Rolls Out GPT -5.2 📈 

OpenAI has released GPT‑5.2, its latest and most advanced model, now live in ChatGPT for pro users. This launch closely follows CEO Sam Altman’s internal “Code Red” directive, where the company reprioritized engineering efforts to accelerate improvements to ChatGPT and its core models in response to mounting competitive pressure from rivals like Google’s Gemini 3.

Why it matters: “Code Red” signaled a focused, company‑wide shift toward strengthening foundational model performance amid a tightening competitive landscape. Read more 

2. Google Updates Deep Research Agent Amid GPT‑5.2 Launch 🧠 

Google unveiled a significantly upgraded Gemini Deep Research agent, powered by its latest Gemini 3 Pro model and now available to developers via a new Interactions API. The agent can autonomously synthesize large amounts of information, refine search queries, and generate structured insights, making it useful for tasks from due diligence to scientific research.

Why it matters: It represents a shift toward agentic AI that can function more independently and be embedded into developer workflows. It’s a clear signal that Google is doubling down on making research‑grade AI tools broadly accessible as competition with OpenAI intensifies. Read more 

3. Disney Signs $1B AI Deal with OpenAI 🎬

The Walt Disney Company is investing $1 billion into OpenAI and giving it access to a massive trove of licensed content (from Pixar and Marvel to Star Wars) for use in its AI tools like Sora and ChatGPT. Read more 

Why it matters: This is a watershed moment in AI and media. For the first time, a major IP holder is not just tolerating AI but partnering to build with it. Expect branded content, character-driven experiences, and new storytelling formats powered by generative AI.

4. EU Council Advances AI Act Implementation 📔 

The European Union AI Act, the world’s first comprehensive AI regulatory framework, is moving deeper into the implementation phase after earlier political approval by the European Council and Parliament. Member states and EU institutions are now focused on outlining how the law will actually be enforced and rolled out, which includes national authorities preparing for compliance timelines and supporting guidance.

Why it matters: Europe continues to lead in AI governance by pushing beyond legislation into real implementation details. The outcomes will ripple globally, influencing how companies design, deploy, and document AI systems, not just in the EU, but wherever those systems are used.

One Big Idea 💡 

✨ From “Build Me an App” to “Build Me an Agent”

This week on LinkedIn, Julie Grumman dropped a riff on Andreessen Horowitz’s “Big Ideas for 2026” and added her own: the rise of the Individual Agent Stack.

The a16z team predicts a world where backend infrastructure is completely reinvented for AI agents that think, act, and collaborate faster than any human-clicking UI ever could. Here’s what a few a16z partners are predicting:

• Agent-Native Infrastructure: New APIs and databases built for machine-speed interactions.

• System of Record Decline: When agents execute workflows, traditional software fades into the background.

• Multi-Agent Orchestration: Fleets of coordinated AI agents, not just a bunch of disconnected tools.

Julie’s take? The next leap is making “building personal agents” accessible. She calls out the gap between easy “vibe coding” apps (hello Replit) and complex agent frameworks (hi LangChain), and predicts a shift where non-engineers can spin up personalized agent stacks that reflect their unique roles, goals, and workflows.

👉️ Join the conversation on LinkedIn

You Asked 🙋‍♀️

“How do you drive companywide focus on a few big AI bets without accidentally squashing smaller, organic AI wins from individual teams?”

This is such a common tension in AI transformations. In our experience, you need both, the top-down alignment on critical, high-impact AI big bets and space for bottom-up experimentation that surfaces unexpected value and, more importantly, signals employee buy-in.

Here are a few ways to support both tracks:

1. Establish a Center of Excellence (CoE): A cross-functional team or structure that tracks AI initiatives across the company. This creates visibility, reduces duplication, and gives leadership insight into what's happening beyond just the headline bets.

2. Formalize time and space for experimentation: Teams need dedicated capacity to explore and implement AI in their domain. This could look like protected time each sprint, internal hackathons, or lightweight funding for pilot projects.

3. Invest in internal knowledge sharing: Build mechanisms like newsletters, internal demos, and town halls, to celebrate and circulate wins from across the org. Small-scale successes often seed larger breakthroughs, but only if they’re seen.

The takeaway: Top-down focus ensures strategic coherence. Bottom-up momentum fuels cultural adoption. Sustained AI transformation requires intentional design for both.

Your Turn 🔁

Got an AI win? Found a tool that made your life 10x easier? Building something cool that deserves a little hype (or know a woman who is)? We want to hear it! You might just see your story in the next edition (with your permission, of course). Because when one of us figures something out, we all get smarter. 🫶 

Her AI Vault 🗂️

Your go-to stash of top resources we’ve created so you never have to dig through old emails to find that one gem.

📘 5 Ways To Get Started With AI At Work: Quick-start guide to delegate the “ugh” tasks and focus on what actually matters.

🔐 AI Privacy Guide: What your AI tools really collect and how to lock down your settings like a pro.

🔍 Her AI Glossary: 40+ essential AI terms, broken down in plain English.

🧠 AI Model Cheat Sheet: Claude, ChatGPT, Gemini... we decoded who does what best, so you can stop guessing and start impressing.

🛠️ Build-Your-Own Productivity Tool: A one-prompt web app for tasks, timers, and focus that is custom-built by Claude and copy-pasted by you.

Before You Go... 💭