From insight to fix, in one conversation
Designing how security analysts investigate and fix risky AI agents in Rubrik Agent Cloud, with Rubrik AI bringing the context to them instead of making them search for it.
Context
Rethinking how Rubrik is used in an AI-first world.
Rubrik AI is the chat built into Rubrik’s products. It started as a Q&A chatbot that answered how-to questions. This project rethought how people will use Rubrik in an AI-first world: instead of clicking through the product to piece things together, they work with an agent that brings the context to them and takes action for them, while they approve anything that changes something.
I set out to define what that agentic experience looks like, starting with Agent Cloud. Agent Cloud gives companies visibility and control over their AI agents, and flags when one does something risky. Security analysts and IT admins investigate what happened and fix it, which means pulling together many parts of the product, then acting, like undoing what the agent did or adding a new policy, a security guardrail for what agents are allowed to do. That made it the right place to prove the idea.
Opening Rubrik AI from the Agent Cloud dashboard.
The opportunity
The context was all there. Connecting it was still up to the analyst.
Agent Cloud already had everything an investigation needs: insights, alerts, every agent and what it can access, what it did, and the policies around it. But working through an investigation meant the analyst had to plan every next step: what to look at, where to find it, and what to do about it.
Rubrik AI lays those steps out for them. It ties the pieces together, explains what they mean and suggests what to do next, so analysts only have to focus on making the right decision.
- What am I looking at?
- Who or what is involved?
- Where’s the related data?
- Is this actually risky?
- What should I do?
- Where do I do it?
- Pulls in the related context
- Explains what it means
- Shows the evidence in the canvas
- Suggests the next step
- You make the call
Instead of planning each step, analysts follow the path Rubrik AI lays out and focus on the decision.
What I designed
The building blocks of an agentic experience.
- A framework for the whole investigation
I designed how an investigation starts, how Rubrik AI responds at each step, from the context it pulls in to the next steps it suggests, and how the analyst gets from understanding an issue to fixing and preventing it, all in one conversation.
- Real product views, beside the chat
I created the canvas: when an answer is easier to see than to read, it opens next to the chat and shows Agent Cloud’s existing UI, the same access maps, session timelines and policy views analysts already use.
When an answer is easier to see than to read, the canvas opens beside the chat.
In practice
One conversation, from question to fix.
Here’s the workflow end to end, through one investigation that starts from an insight: Claude Code, a coding agent, deleted a repository on GitHub, something it had never done before.
Start from what matters
As soon as the analyst logs in, Rubrik AI opens on its own and flags what needs attention first: here, a critical insight that Claude Code deleted a repository on GitHub. One click starts the investigation, with that insight already loaded as context.
The agent explains, the canvas shows
Rubrik AI explains what happened: Claude Code deleted the acme-platform repository, even though it had only ever read and written code before. At the same time, the canvas opens the agent’s access map, where the new shell tool it used stands out.
From there, the analyst opens the affected session and walks through its timeline: a policy stopped the agent from committing a credentials file, then it moved on and ran the command that deleted the repository and its full history.
Rewind, right from the conversation
Rubrik AI stages a rewind to just before the deletion and lays out what will be restored. The analyst confirms, and the canvas shows the rewind completing: the repository is back on GitHub with all of its history.
Turn the fix into a policy
With the repository restored, Rubrik AI points out that Claude Code can still run shell commands, so the same thing could happen again. It recommends a policy to block coding agents from running destructive shell commands on GitHub and drafts it in the canvas.
The analyst can review its scope, examples and definitions or ask follow-up questions, then create it, all in the same conversation.
The policy at work
The next time a coding agent tries something similar, Agent Cloud stops it as it happens. Here, a developer asks Claude Code to clean up old repositories, and it tries to delete one. The new policy blocks the command, and Claude Code suggests safer options instead, like archiving the repository.
Key decisions
Four decisions shaped the design.
- Show the real product, not a chat version of it
A map, a timeline or a table is easier to scan and compare than paragraphs of chat, and these are views analysts already know and use. So instead of rebuilding them as chat responses, the canvas reuses Agent Cloud’s existing UI, and any view in the product can show up in the conversation.
- Start where the analyst already is
Rubrik AI opens on its own after login, with the most important insight already flagged and loaded as context, so the conversation starts at the right place instead of at a blank prompt.
- Suggest, then ask
Rubrik AI recommends the next step, but the analyst confirms every action that changes something, like a rewind or a new policy.
- Fix and prevent in one flow
Suggesting the policy right after the rewind keeps prevention in the same conversation as the fix, while the full story of what happened is still on screen.
Outcome
From my designs to Rubrik’s main stage.
Rubrik’s leadership demoed this experience live at Rubrik Forward 2026, Rubrik’s annual conference. On the main stage, they showed Rubrik customers and sales teams how Agent Cloud and Rubrik AI take an analyst from insight to fix in one conversation.
The design on the main stage at Rubrik Forward 2026.
Beyond the demo, it became the blueprint for agentic experiences across Rubrik: other product teams are now building their own, following the standards set here.
What’s next
From demo to product.
This integrated experience is now being built, and is planned to be generally available in early 2027.