Google AI for Developers’ Post

This update is truly game-changing! This new 'Max' version of the Gemini Deep Research Agent and 'MCP Support' clearly demonstrate that the focus is no longer just on completing tasks, but on building an autonomous ecosystem. When we talk about revenue and automation, people often get caught up in tools, but true scalability comes from 'Systems over Hustle.' Long-horizon research agents like these will now strengthen the backend of systems so much that founders will have to focus solely on the vision instead of worrying about day-to-day operations. I believe in the saying 'I Don't Do Tasks, I Build Systems That Run Your Business'—and these AI updates are a major leap in that direction. Do you think the introduction of deep research agents like these will further reduce the need for human intervention in business operations, or will they simply accelerate our research? What are your thoughts?

This update is truly game-changing! This new 'Max' version of the Gemini Deep Research Agent and 'MCP Support' clearly demonstrate that the focus is no longer just on completing tasks, but on building an autonomous ecosystem. When we talk about revenue and automation, people often get caught up in tools, but true scalability comes from 'Systems over Hustle.' Long-horizon research agents like these will now strengthen the backend of systems so much that founders will have to focus solely on the vision instead of worrying about day-to-day operations. I believe in the saying 'I Don't Do Tasks, I Build Systems That Run Your Business'—and these AI updates are a major leap in that direction. Do you think the introduction of deep research agents like these will further reduce the need for human intervention in business operations, or will they simply accelerate our research? What are your thoughts?

A cleaner interface is a cosmetic fix for a structural problem. Most companies celebrate these updates as a boost to productivity, but they ignore that the friction isn't in the button placement—it's in the data architecture sitting behind the screen. And in my experience with enterprise HubSpot deployments, the "big update" often masks the fact that the underlying governance layer is still fragmented. You can streamline the UI all you want, but if the decision rights and field mappings are broken, you're just accelerating the rate at which users create bad data. It's a bit of a distraction from the real work of CRM hygiene. Whether this actually translates to revenue efficiency in every vertical is a different conversation. Three of the last four migrations I’ve audited showed that users didn't need fewer clicks; they needed a system that actually reflected their GTM strategy. The tool evolved. The process didn't.

The ability to plan before execution combined with long-horizon reasoning is a big step forward—this feels closer to true research automation than anything we’ve seen so far.

This is the shift from AI as a tool → AI as an operator. Excited to see how teams leverage Deep Research vs Deep Research Max depending on complexity, cost, and outcome precision.

This is awesome. Now we're back in the game

Powerful upgrade from Google—deep research workflows just became far more capable.

Research was always gated by how many hours one person could stay focused. Moving that gate to a configuration flag changes who gets to do research at all

You’re getting there! Come share what you build and learn with 13,400+ of us in the AI Agents group on linkedin: https://www.linkedin.com/groups/6672014

Exciting update! Deep Research Max sounds particularly promising for complex academic and enterprise research use cases. Looking forward to testing it.