AI Build & Ask
Describe the change. Review the diff. Ship the app.
Developers build ObjectStack apps by pointing a coding agent like Claude Code at the source project. ObjectOS adds a second path for teams: business users describe the change in conversation on Cloud or Enterprise. Both produce the same typed ObjectStack metadata and run on the same governed runtime; ObjectOS AI Ask answers and acts on live data inside the permissions of the person asking.
- 2 paths
- Build with a coding agent in source, or by conversation in the cloud
- Held whole
- Apps small enough for AI to hold whole — the bundled CRM loads end-to-end
- Business+
- AI action audit, guardrails, and permission scoping start on ObjectOS Business
The build loop
From one sentence to a governed application.
The loop is designed so speed never outruns control: the AI moves fast on the draft, and a person owns the decision.
- Describe: “Track vendor contracts with renewal reminders and an approval for anything over $50k.”
- Your AI — a coding agent in source, or the in-app builder — drafts the objects, fields, views, and renewal flow.
- Structural changes land in the approval queue as a compact, readable diff.
- You approve — the ObjectStack runtime derives and ships tables, APIs, screens, automations, and audit.
- AI Ask now answers contract questions for each user, scoped to what they may see.
AI Build
Two ways to build — one reviewable definition
Whether the AI works in your repository or in an ObjectOS chat panel, the output is the same typed ObjectStack metadata a human reviews and owns. The definition stays small enough for an agent to hold whole: the objectstack README’s bundled CRM — objects, views, a dashboard, a lead-conversion flow, permission sets, actions, translations — loads end-to-end and refactors in one change.
In source, with your coding agent
Developers point Claude Code, Cursor, or any coding agent at the project; it writes every metadata type as source files, previewed in the browser and reviewed as a git diff — a Salesforce DX-style workflow.
In the cloud, by conversation
On ObjectOS Cloud and Enterprise, business users describe the change in chat; the in-app builder drafts it as ObjectStack metadata with live preview — Airtable-style ease with runtime governance.
Visual designers to fine-tune
Objects, views, flows, and dashboards each have a designer — drag-to-reorder fields, a flow canvas, kanban column config — and review mode diffs the draft against the published version, so tuning what the AI drafted never touches a file.
Approval before structure changes
Anything that changes the shape of the system queues for human sign-off with the full diff — on either path.
AI Ask
Answers and actions over live business data
AI Ask works inside the product, over real records — not a stale export — and it never sees more than the person asking.
Question the business
“Which contracts renew this quarter?” “Which vendors slipped SLA twice?” — answered from live objects with permissions applied.
Run approved actions
Ask can trigger actions that metadata explicitly exposes — assign, escalate, generate a summary — within the user’s rights.
Everything on the record
On ObjectOS Business and Enterprise, Ask queries and actions land in the audit log alongside human activity, so review works the same for both.
Open-source ObjectStack
Bring your own AI, keep the same governance
Open-source ObjectStack has no built-in assistant — by design. Your coding agent writes the same metadata as source files, and any MCP client queries the same governed objects through its open runtime.
Agent writes source files
npm create objectstack@latest scaffolds a project and writes an AGENTS.md, so Claude Code, Cursor, or any coding agent starts with the protocol’s rules loaded; it edits ObjectStack definitions in your repo, npx os dev --ui renders them, and review happens as ordinary git diffs.
Any MCP client can ask
The MCP server exposes your objects, queries, and actions to whatever model you run — hosted or fully local.
Same runtime, governance by edition
On the open-source runtime, MCP tool calls run inside the caller’s permissions and land in the audit log. ObjectOS adds in-app AI by edition: a taste on Free, in-app AI Build and Ask on Team, and AI governance — action audit, guardrails, permission scoping — from Business.
Decision surface
What changes, who reviews it, what runs
| Edition | How AI builds | How AI answers |
|---|---|---|
| Open-source ObjectStack | Your coding agent edits metadata source files; review as git diffs | Any MCP client queries governed objects with your own model |
| ObjectOS Cloud Free | A taste of in-app AI Build | A taste of in-app AI Ask |
| ObjectOS Cloud Team | In-app AI Build drafts changes; approvals gate structure | In-app AI Ask answers and runs approved actions |
| ObjectOS Business (Cloud) | Same, plus AI governance: action audit, guardrails, permission scoping | Same, with Ask queries and actions audited and guardrailed |
| ObjectOS Enterprise (self-managed) | Same, on your own infrastructure, plus bring-your-own-model | Same, plus local models and internal identity |
FAQ
Frequently asked questions
What stops AI from breaking production?
The ObjectStack runtime enforces two guarantees for any agent working over MCP: structural changes require human approval, and every tool call runs inside the requesting user’s permissions and is audited. ObjectOS Business and Enterprise add AI governance for the in-app AI — action audit, guardrails, permission scoping — so AI can draft quickly but cannot ship silently.
Which models does it use?
Cloud editions run managed models behind AI Build and Ask. The open-source ObjectStack brings your own — any MCP-compatible client or a local model. Self-managed ObjectOS Enterprise, from its single-node Business Self-Managed entry up, brings your own model or key.
Next pages