Your coding agents ship fast and ship blind. Today that changes.
Claude Code knows your codebase. Cursor knows your file tree. Codex knows the syntax of every language you’ve touched. None of them know which customer asked for the thing you’re about to build, what it’s worth, or whether anyone needed it. That gap is where the wrong features get shipped. Faster than ever.
Today we’re launching Everything AI: three Bagel features that move a product decision from customer signal to shipped code. AI Product Opportunities finds the openings worth building. Discovery OS validates them against your real customer signal. The Bagel MCP serves the answer to whatever AI agent does the building.
Each one earns its place on its own. Run together, they close the loop from signal to ship. Always build the right thing, the right way, at the right time.
AI Product Opportunities: Bagel brings you the next move
Most product tools wait for you to ask. You open the dashboard, type a query, and dig. AI Product Opportunities runs the other direction. Bagel scans every signal you’re connected to, finds the gaps you haven’t noticed, and brings you the opportunity already worked out.
Each one arrives with the evidence consolidated, the revenue quantified, and the customers named. A $50K Salesforce request shows up as the customer evidence and the revenue case for the initiative you were already weighing. Soon it’ll come packaged as a PRD or a dev-ready artifact too.
These are not brainstormed ideas. They’re openings Bagel found in your own data, ranked against your existing roadmap, with the receipts attached. Your job shrinks to the part that always mattered: looking at a substantiated call and deciding yes or no.
Discovery OS: validation in minutes
You have a hypothesis. Old way, you’d schedule interviews, run a research sprint, wait two weeks, synthesize, present. Then move on until the next cycle.
Discovery OS collapses that into minutes. Prompt the hypothesis, and Bagel returns the evidence aggregated, themed, and quantified across every connected source. Sales calls, support tickets, surveys, in-product feedback. The validation that used to be a project becomes a standing capability that runs whether you’re looking or not.
This is where you find out if an opportunity is real before anyone writes a line of code. See how it fits the wider platform on the platform overview.
The Bagel MCP: every decision, piped to every agent
AI Product Opportunities answers what to build. Discovery OS answers whether it’s worth it. The Bagel MCP answers how that answer reaches the thing doing the building.
The Bagel MCP server exposes your decisions to any MCP client. Claude Code, Cursor, Codex, Glean, and the rest of your stack. A developer opens a Linear ticket for SSO support, the agent queries Bagel, and pulls who requested it, the deal value at stake, and the security requirements. It builds against real customer use cases instead of a vague spec. First-pass quality up. Reopened tickets down.
The distinction that matters: the Bagel MCP serves scoped decisions and evidence, not raw data rows. It won’t dump a thousand unsorted Salesforce records on your agent. It answers the question the agent is asking. Which customers requested this, ranked by revenue, with the current roadmap position. We wrote a full guide to MCP for product teams if you want the deeper version.
Claude is the engine. Bagel is the fuel.
Why these three, together
Shipping got cheap. AI writes the code, generates the artifact, fills the ticket. The bottleneck moved up the stack to the part AI can’t see: which thing deserves to get built, and for whom.
Everything AI sits in that gap. AI Product Opportunities finds the opening. Discovery OS proves it’s real. The Bagel MCP carries the verdict to the agents doing the work. The loop runs continuously, against live customer signal, so the next right thing to build is already waiting when your team walks in on Monday.
You still own the yes. That part isn’t going anywhere.
