Good morning ☀️, leader of the next generation.

We will talk about agents. AI agents.

They will change the way how we do business, how we interract and even how we do our everyday lives.

Agents will build business.

Agents will organize your day.

Agents will fill up your fridge.

I will let that sit in here for a while, so we can imagine and build the future together one agent at a time...

⚡ WHAT'S AT STAKE TODAY ⚡

1. 🤖💊 AI is spitting out more potential drugs than ever. This startup wants to figure out which ones matter.
2. 🌐🤖 Google turns Chrome into an AI co-worker for the workplace
3. 🚀💰 SpaceX is working with Cursor and has an option to buy the startup for $60B
4. 🔍📊 Meta will record employees' keystrokes and use it to train its AI models
5. ☁️🚀 The most interesting startups showcased at Google Cloud Next 2026
6. 🗺️🤖 Google Maps is about to get a big dose of AI
7. 🤝💼 OpenAI teams up with Infosys to bring AI tools to more businesses
8. 🌐🤖 Google turns Chrome into an AI co-worker for the workplace
9. 💻⚡ Google Cloud launches two new AI chips to compete with Nvidia

Startup tackles AI drug discovery bottleneck with automated analysis platform

AI is spitting out more potential drugs than ever. This startup wants to figure out which ones matter.

Artificial intelligence has revolutionized drug discovery, with Google DeepMind's breakthrough in predicting protein structures leading the charge. However, as AI generates an unprecedented number of potential drug candidates, the pharmaceutical industry faces a new challenge: determining which ones are worth pursuing.

Enter 10x Science, a Stanford-born startup that raised $4.8 million in seed funding to solve this emerging bottleneck. Founded in December 2025 by chemical biologist David Roberts, biologist Andrew Reiter, and AI expert Vishnu Tejus, the company aims to streamline the crucial but time-intensive process of characterizing drug candidates.

"When biopharma tries to create a drug candidate, they have all of these really nice prediction tools," Roberts explained. "You can add as many candidates as you want to the top of the funnel, but they all have to pass through this characterization process. Everything needs to be measured."

The three founders previously collaborated in Nobel laureate Dr. Carolyn Bertozzi's lab at Stanford, studying interactions between cancer cells and immune systems. Their frustration with the inability to understand molecular-level processes precisely led them to develop their current solution.

10x Science addresses the challenge using mass spectrometry, the most accurate method for assessing molecular composition and structure. While this technique generates highly detailed data, interpreting it requires significant expertise and time – resources many biotech companies lack.

The startup's platform combines chemistry and biology-based algorithms with AI agents capable of interpreting complex spectrometry data. The team invested considerable effort training models specifically on spectrometry data while ensuring analyses remain traceable – essential for regulatory compliance in drug development.

Early user Matthew Crawford, a scientist at Rilas Technologies, has been testing the platform for several weeks. He reports significant improvements in workflow speed and efficiency. "I ran a particular protein through it, and it just kind of figured out, from what I named the file, what the protein probably was," Crawford said. "It then searched databases online for the sequence for that protein, so I didn't have to program in the sequence."

Crawford noted the system's ability to explain conclusions, autonomously find relevant data, and adapt to different molecule types – capabilities that distinguish it from other AI tools that often over-promise or lack accuracy.

The company is already working with major pharmaceutical companies and academic researchers. With seed funding led by Initialized Capital and backed by Y Combinator, Civilization Ventures, and Founder Factor, 10x Science plans to expand its engineering team and refine its model for broader customer adoption.

Roberts envisions expanding beyond protein characterization to offer comprehensive biological understanding by combining protein structure data with other cellular information. "The deeper thing behind what we're building is actually a new way to define molecular intelligence," he said.

For investors, 10x Science represents an attractive entry into biotech that doesn't depend on individual drug success. As Initialized partner Zoe Perret noted, "This is a SaaS platform that pharma has to pay for, every single month, to go through all of these potential candidates."

The platform could democratize advanced analytical techniques for researchers lacking resources or expertise. Crawford believes the software will help research groups "get a quick, simple answer out of mass spec" without opening "a whole can of worms," enabling them to focus on their core research objectives rather than getting bogged down in complex data interpretation.

Google introduces AI-powered Chrome features for enterprise users

Google turns Chrome into an AI co-worker for the workplace

Google announced new AI-powered "auto browse" capabilities for Chrome enterprise users, allowing Gemini to understand browser context and handle tasks like booking travel, data entry, and scheduling meetings. The feature requires human approval before executing actions.

Available initially to U.S. Workspace users, the tool aims to automate tedious tasks while keeping humans in control. Google is also expanding security features to detect unsanctioned AI tools and browser threats, positioning itself as the preferred enterprise AI solution while blocking competitors.

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Each episode dives deep with founders, operators, and builders who are actively working with AI — or building AI-first companies — to uncover how it’s truly changing the way work gets done.

From strategy and systems to real-world execution, these conversations are practical, honest, and focused on what actually works — not just what sounds good.

Google splits eighth-generation TPUs into training and inference chips.

⚡ Let’s Make AI Actually Useful:
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AI has potential — but generic advice rarely helps.

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Tell us what you’d want AI to handle — or where you feel stuck.

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