Use cases
What operators actually build.
Real apps, in production at our design partners, built by the person closest to the problem – not an engineer pulled off product. Everything is anonymized: the work is real, the screens below are mocks.
Who’s building
The examples
Six apps. Six different stories.
Pipeline updates used to be spreadsheets and decks passed around. Now it’s one view, owned by RevOps, that the whole company works in. The pattern keeps repeating – roadmap updates, status reports: the artifact people used to send each other becomes the app everyone opens.
One view, owned by the team closest to the data, used by everyone.
One person built a Slack bot that answers from the team’s playbooks, citing every answer – and saying “I don’t know” when the docs don’t cover it. Apps aren’t just web apps: a bot, an internal service, whatever fits. One operator’s onboarding guide even drafts its own updates from Slack questions, nothing live without her approval.
If the answer isn’t in the docs, it says so. Refusal is deterministic.
A chain of spreadsheets became the single tool the paid-media team runs on: pacing, partner economics, a queue of today’s changes. It reads production data directly – read-only, scoped by Stoda – so nothing gets duplicated into one more sheet that drifts.
Built on production data, made safe: read-only where it should be.
Product managers shape in the coding tools now, not slide decks: ship the working version internally, behind SSO, and put the team on the real thing. One PM’s onboarding pilot became the most-used internal app at the company – and the blueprint the production build was scoped from.
Working software is the new spec.
The VP of creative built a suite, not an app: a generation tool and a review tool that talk to each other, with dozens of configurations of a review agent his team deploys. When the process changes, he doesn’t update a playbook – he updates the tools and agents his team runs on.
His process lives in the tools his team uses, not in a playbook.
Not every app needs AI – this one is deterministic on purpose: fixed checks that flag exactly what needs a human, identically on every run. Building with AI and putting AI in an app are separate decisions, and deterministic buys predictability, auditability, and flat costs.
The app flags. A person decides. Every run identical.
The other half
A portfolio, not shadow IT.
Because every app deploys through Stoda, you can see the whole portfolio: who built what, who uses it, what to keep, and what to quietly retire. That visibility is the difference between an asset and a liability.
It’s all usage, so decisions get made with data instead of perception. And apps outlive their builders: everything is versioned and deployed the same way, so when someone leaves, handing their app to a new owner – or retiring it – is a decision, not an archaeology project. Lessons from every deploy fold back into the shared template, so the next app begins where the last one finished.
The portfolio report surfaces what to keep and what to retire, on its own.
Your operators have a list like this already.
Let them build it safely. We’re picking our next design partners now.