Problem Solver

Theory

A cloud product sandbox for builders. A complete product, simulated end to end. Every feature specced, the architecture built, and a runnable codebase handed off ready to ship.

0+Lines of code
0UI components
0Product pages
~0Weeks to deliver

The Vision

Product work still happens outside the product.

Teams describe what a product should become with documents, screenshots, static designs, and tickets, all of it disconnected from the real thing. Every handoff loses something in translation between product, design, and engineering.

Theory is the missing middle: a safe cloud sandbox branch of the real product where builders model changes in context, then export clean, review-ready work to engineering.

The entire thing is governed by one principle, stated everywhere in the product: production-aware, never production-authorized.

What Was Built

A working product cockpit, simulated end to end.

Start from the real product

No blank mockups. Theory spins up a cloud sandbox branch from a real baseline (main, staging, a release tag, or a commit) and opens the exact work area you choose: login flow, checkout, navigation, dashboard, or any custom route.

Real baseline, every time

Production-aware safety model

The whole product is built around one promise: it can read approved product context and stage changes, but it can never push, merge, deploy, or write to production. A visible "Sandbox Only" badge makes the boundary obvious at all times.

Never production-authorized

AI product modeling

A plain-English command layer for modeling changes in context. "Improve the login flow for a first-time user." "Show the empty dashboard state." Every response is scoped to the sandbox branch and reminds you the change never leaves it.

Conversational, in-context

Design Intelligence

The product's behavioral design context (visual rules, interaction patterns, density, accessibility, and responsive behavior) applied to every sandbox change. Ships with presets for internal tools, SaaS dashboards, marketplaces, marketing sites, and more.

6 template presets

Data safety modes

Test against realistic, product-shaped data without ever touching production. Choose mock data, censored replicated data with sensitive fields masked, staging data, or a read-only production reference. No write path exists.

Mock · Censored · Staging

Engineering handoff packages

The missing bridge between product intent and shipped code. Each handoff bundles a summary, affected routes and files, before/after screenshots, acceptance criteria, engineering notes, and a PR-ready developer review checklist.

PR-ready export

Deep Dive

Start from the real product every time.

A guided wizard turns intent into a running sandbox: pick a connected app, choose a read-only baseline, select the work area, and set a data mode. Theory creates an isolated branch and opens it in a live product canvas.

Left panel is the command cockpit: AI, brief, work area, Design Intelligence, components, state manager, comments, versions, handoff. Right panel is the running product, switchable between preview, code, split, compare, and responsive.

theory/login-flow-v1Sandbox Only
Connected appTheory Demo SaaS
Baselinemain · read-only
Work areaLogin flow
Data modeCensored replica
Safety modeExport-only
PreviewCodeCompareResponsive
Sandbox OnlyNo production writes
Read approved product context
Create sandbox branches
Render sandbox previews
Push to production
Merge branches
Deploy production builds
Write production data

Deep Dive

Production-aware. Never production-authorized.

Safety isn't a setting. It's the architecture. Theory can read approved context and stage changes on an isolated branch, but every dangerous capability is designed out: no pushes, no merges, no deploys, no production data writes.

The only ways out of the sandbox are an export or a PR-ready handoff. Engineering always controls merge and release. That trust boundary is what makes builders and their dev teams comfortable using it.

Under The Hood

A real architecture your team can build on.

The stack

React + ViteTypeScriptTailwind CSSshadcn · Radix UISupabase-ready modelGitHub-first (mocked)Row-Level Security (modeled)Vercel-ready

The front end is modeled against a future Supabase backend: typed objects for connected apps, baselines, sandboxes, work areas, comments, design templates, and handoff packages, with a role-based access model and append-only audit logs.

0Data models
0User roles
0Design templates
0Export formats

The Value

What a foundation like this costs the traditional way.

The traditional path

A product manager, a designer, and two to three senior front-end engineers, running discovery, specs, architecture, and a working build of a platform this complex.

9–12 months
before a team is confidently building

Estimated cost saved

$0K+

versus staffing the same discovery, design, and foundational build in-house or via an agency.

Working with ProductScott

The complete simulation: documentation, working codebase, and a Supabase-ready data model, handed to your team ready to run.

~6 weeks
flat fee, scoped upfront

Basis: a product manager, a UX/UI designer, and two senior front-end engineers at market salary, over roughly five to seven months to produce comparable documentation, design, architecture, and a working foundational build. Actual figures vary by team, rates, and scope.

Now imagine it's your product.

A platform, an internal tool, a brand-new product line: whatever you've been trying to get off the ground. This is the head start your team could be building from in weeks.