Opinion insight on the new announcements on the Databricks Data + AI Summit 2026, written as we attend the event in San Francisco, with an honest and open view as experienced and reflected by our element61 consultants present.
Learnings during the Databricks Data + AI Summit in San Francisco
"A lot is being announced at the Databricks Data + AI Summit 2026, and like everyone else, we are still getting to know these new platforms, products, and capabilities in practice. Below a honest first-impression perspective on what I’m genuinely into, and one I’m not convinced about."
✅ 1. Databricks has a sharp vision on apps
Databricks is making app development on top of enterprise data feel radically easier, while still keeping governance at the center.
First, they gave you an easy way to build apps backed by a real database: Lakebase, their serverless Postgres offering. Now they’ve shipped Genie App Builder, basically their own Lovable / v0.dev, except it intimately understands the platform it runs on and integrates with all your data and ontology layer.
What I love is that they’re actively defusing the biggest footgun of letting business users code:
- With Unity Catalog, platform admins can centrally pre-configure row- and object-level security. The app connects to your data on behalf of the user, so people can’t leak data by mistake. Another reason to really step up your Unity Catalog game.
- Auth is built in. The folks who never think about SSO get it for free, by default.
Honestly, from my own experience, this is massive. The platform makes it easy to protect users from themselves.
Pair that with Serverless Micro Apps that scale to zero, spin up in a couple of seconds, and shut off when idle, and “app sprawl” no longer means going broke.
I like that Databricks has a bold, opinionated vision on the future of software and apps, and that it’s actually backed by their platform.
🤖 2. Sandboxed compute in Agent Bricks
I’m an agent nerd, so this one got me.
Governed compute. Python interpreters. A place to run bash and Python scripts. All inside your own cloud environment.
These past months, I landed on the view that the last real problem for running autonomous agents everywhere, and not just in your terminal or chat UI 😬, is giving them secure serverless compute.
Options like Daytona existed, but for a lot of enterprises, moving data and code off-platform was a non-starter.
Now that Databricks has built this in, I think it makes them a credible end-to-end agent provider.
🤔 One thing I’m not sold on: Omnigent
As a heavy opencode user, I already have a single harness with access to all models, so I don’t really feel the need to orchestrate multiple harnesses.
The supervisor pattern and routing are already doable from the CLI, and there’s a desktop and web app too.
I do like the Unity AI Gateway integration. And to be fair, it governs and routes external, non-Databricks models too, not just models hosted on Databricks.
But here’s my take on cost: the surefire way to cut enterprise AI spend isn’t paying per token by consuming models through the platform.
For power users, it’s enterprise subscriptions straight from the providers. For example, a €200/month plan at OpenAI or Anthropic can deliver thousands of euros of equivalent API usage.
Final thought
All in all, very exciting stuff from Databricks.
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FAQ
Databricks used the Data + AI Summit 2026 in San Francisco to position itself as an enterprise app and agent platform. Key announcements include Lakebase (serverless Postgres), Genie App Builder for building data-backed apps, Serverless Micro Apps that scale to zero, and sandboxed compute in Agent Bricks. element61 consultants attended the event and shared honest first impressions.
Lakebase is Databricks' serverless Postgres offering that gives developers an easy way to build apps backed by a real database. It lets teams create enterprise applications on top of their data while keeping governance central. Lakebase is one of the building blocks behind Databricks' push to make app development on enterprise data radically easier.
Genie App Builder is Databricks' app-building tool comparable to Lovable or v0.dev, but one that intimately understands the platform it runs on and integrates with all your data and ontology layer. It lets business users build apps on enterprise data, while Unity Catalog keeps row- and object-level security centrally configured so users can't leak data by mistake.
Governance stays at the center. With Unity Catalog, platform admins pre-configure row- and object-level security, and apps connect to data on behalf of the user so people can't leak data by accident. Authentication and SSO are built in by default. In element61's view, making it easy to protect users from themselves is a major step forward.
Serverless Micro Apps are Databricks applications that scale to zero: they spin up in a couple of seconds and shut off when idle. Because idle apps don't consume compute, "app sprawl" no longer means runaway costs. Paired with built-in governance and authentication, they let organizations deploy many small apps affordably.
Sandboxed compute in Agent Bricks gives autonomous agents governed, secure serverless compute - Python interpreters and a place to run bash and Python scripts - all inside your own cloud environment. We see this as significant: securing off-platform data and code was previously a non-starter for many enterprises, and building it in makes Databricks a credible end-to-end agent provider.
For autonomous agents to run beyond a terminal or chat UI, they need secure, governed compute. Earlier options such as Daytona existed, but moving data and code off-platform was unacceptable for many enterprises. By building sandboxed compute into the platform, Databricks removes that blocker, a development element61's agent specialists view as a genuine step toward end-to-end enterprise agents.
At element61, we're not fully sold on Omnigent. As heavy users of a single AI harness with access to all leading models, we already have the flexibility to orchestrate model routing and supervisor patterns through existing CLI, desktop, and web interfaces. However, we do see clear value in the Unity AI Gateway, particularly because it enables governance and routing not only for Databricks models but also for external AI models, supporting a more unified enterprise AI architecture.
The surefire way to cut enterprise AI spend isn't paying per token by consuming models through the platform. For power users, enterprise subscriptions straight from the providers go further; for example, a €200/month plan at OpenAI or Anthropic can deliver thousands of euros of equivalent API usage.
The Unity AI Gateway is a Databricks integration that governs and routes AI models, including external, non-Databricks models, not just those hosted on Databricks. It gives enterprises a single, governed control point for model access. We note this as one of the more appealing pieces of the Omnigent announcement.
Enterprises building applications and autonomous agents on top of governed data should take note, especially those already invested in Databricks and Unity Catalog. element61's consultants attend events like the Data + AI Summit to assess these platforms in practice. Reach out to element61 to translate these announcements into a practical roadmap.
element61 can help you evaluate Databricks' new app and agent capabilities Lakebase, Genie App Builder, Serverless Micro Apps, and Agent Bricks and strengthen the Unity Catalog governance they depend on. Whether you're exploring enterprise apps or autonomous agents, get in touch for a tailored assessment.