Watching the Claude CoWork conversations and the takeaway feels pretty simple: AI doesn’t replace thinking or trust. It just makes it way harder to justify moving slowly.
Chatted with Windsurf’s Anshul months ago at an MIT AI conference about agent-first IDEs and real-time, multi-model workflows. Today, the Google acquired, Windsurf team, dropped Antigravity.
Wild to see that vision ship this fast, and can’t wait to spin it up.
Google Antigravity is our new agentic development platform.
It helps developers build faster by collaborating with AI agents that can autonomously operate across the editor, terminal, and browser.
It uses Gemini 3 Pro 🧠 to reason about problems, Gemini 2.5 Computer Use 💻 for end-to-end execution, and Nano Banana 🍌 for image generation.
@AndrewYNg Teams underestimate how much value gets trapped inside vendor silos until they try building cross-system agents. It’s especially painful for growing startups that need flexibility but end up boxed in by their own tools.
AI agents are getting better at looking at different types of data in businesses to spot patterns and create value. This is making data silos increasingly painful. This is why I increasingly try to select software that lets me control my own data, so I can make it available to my AI agents.
Because of AI’s growing capabilities, the value you can now create from “connecting the dots” between different pieces of data is higher than ever. For example, if an email click is logged in one vendor’s system and a subsequent online purchase is logged in a different one, then it is valuable to build agents that can access both of these data sources to see how they correlate to make better decisions.
Unfortunately, many SaaS vendors try to create a data silo in their customer’s business. By making it hard for you to extract your data, they create high switching costs. This also allows them to steer you to buy their AI agent services — sometimes at high expense and/or of low quality — rather than build your own or buy from a different vendor. Unfortunately, some SaaS vendors are seeing AI agents coming for this data and working to make it harder for you (and your AI agents) to efficiently access it.
One of my teams just told me that a SaaS vendor we have been using to store our customer data wants to charge over $20,000 for an API key to get at our data. This high cost — no doubt intentionally designed to make it hard for customers to get their data out — is adding a barrier to implementing agentic workflows that take advantage of that data.
Through AI Aspire (an AI advisory firm), I advise a number of businesses on their AI strategies. When it comes to buying SaaS, I often advise them to try to control their own data (which, sadly, some vendors mightily resist). This way, you can hire a SaaS vendor to record and operate on your data, but ultimately you decide how to route it to the appropriate human or AI system for processing.
Over the past decade, a lot of work has gone into organizing businesses’ structured data. Because AI can now process unstructured data much better than before, the value of organizing your unstructured data (including PDF files, which LandingAI’s Agentic Document Extraction specializes in!) is higher than ever before.
In the era of generative AI, businesses and individuals have important work ahead to organize their data to be AI-ready.
P.S. As an individual, my favorite note-taking app is Obsidian. I am happy to “hire” Obsidian to operate on my notes files. And, all my notes are saved as Markdown files in my file system, and I have built AI agents that read from or write to my Obsidian files. This is a small example of how controlling my own notes data lets me do more with AI agents!
[Original text: https://t.co/1bwB2lBowg ]
Anyone who says college alum networks don’t work, really hasn’t experienced the power of what alumni does.
You’re way more likely to get people go out of the way for you just because you went to the same college, irrespective of the age gap.