Coding Workflows Workflow Advanced

AI Auth & Identity Workflow

Design access control before you build it, not after a breach — choose the authentication approach, model the roles and permissions, review the design for gaps, then document the identity model.

The problem

Access control is the part of a system you cannot retrofit safely — bolt authorization on after the fact and you get the leaked record, the privilege escalation, the role that can do more than anyone intended. The decisions are upfront and they compound: how users prove who they are, what each role may do, where the identity boundaries sit, how sessions behave. 'Ask AI to add auth' produces a login form and stops, skipping the authorization model that actually keeps data safe. This workflow designs the whole access-control strategy — authentication, roles, permissions, sessions — and reviews it for gaps before a single check ships.

Recommended workflow

Each step uses an existing NewPrompt tool, pre-filled by a matching resource. Open the resource to read it, or jump straight into the tool with the inputs ready.

  1. Choose the authentication approach

    Anchor the model as a security engineer and decide how users prove who they are — sessions versus tokens, password versus passwordless, SSO, MFA — on the trade-offs your system actually faces, not the default.

    Goal An authentication approach chosen on its trade-offs.

    Resource Authentication Strategy Prompt
    Tool Role Prompt Generator
    Open this step in Role Prompt Generator

  2. Model the roles and permissions

    Design the authorization model one decision at a time: the roles, what each may do, how permissions compose (RBAC and beyond), and how sessions carry identity. This is the layer that actually controls access.

    Goal Roles, permissions, and session strategy modeled.

    Resource RBAC Design Prompt
    Tool Multi-Step Prompt Builder
    Open this step in Multi-Step Prompt Builder

  3. Review the access-control design for gaps

    Turn a security lens on the design before it's code: missing checks, privilege escalation, roles that can do too much, identity boundaries that leak. Find the holes while they're still cheap to close.

    Goal The access-control design reviewed for escalation and missing checks.

    Resource Authorization Review Prompt
    Tool Code Review Prompt Generator
    Open this step in Code Review Prompt Generator

  4. Document the identity model

    Capture the decisions — auth method, role-and-permission matrix, session rules, identity boundaries — in a document the build follows and the next security review starts from.

    Goal The auth and identity model documented for the build.

    Resource Permission Matrix Prompt
    Tool Markdown Output Builder
    Open this step in Markdown Output Builder

Expected outcome

An access-control strategy designed before implementation — authentication chosen on trade-offs, roles and permissions modeled, the design reviewed for escalation and gaps, and the identity model documented — so security is built into the structure instead of patched in after the first leak.

Best for

  • Designing authentication and authorization before building it
  • Modeling roles, RBAC, and permissions deliberately
  • Reviewing an access-control design for gaps before it ships

Not for

  • Reviewing existing code for vulnerabilities — use the AI Security Review Workflow
  • Designing the API surface — use the AI API Design Workflow
  • Designing the data model — use the AI Database Design Workflow

FAQ

How is this different from the AI Security Review Workflow?

Security review inspects existing code for vulnerabilities — it's a review pass. This designs the access-control model up front: authentication, roles, permissions, sessions. One designs the security; the other reviews what's built. You'd design auth here, then run a security review on the implementation.

How is this different from the AI API Design Workflow?

API design shapes the endpoints and contracts; this shapes who's allowed to call them and what they can do. Auth is the access layer over the API surface — related but distinct artifacts. They inform each other, but the role-and-permission model is its own design.

Does the AI decide my security model?

No. It structures the auth and authorization decisions, surfaces the trade-offs, and pressure-tests the design for gaps — but the access-control calls, and owning their consequences, stay with you. High-stakes systems still warrant a real security audit.

Part of these blueprints

Complete build journeys that include this workflow as a stage.

Blueprint Build an API Backend with AI The full path to a backend you can put clients on — define the requirements, design the architecture, API contract, data model, and access control, then build it reviewed, tested, secured, and shipped. View Blueprint → Blueprint Build a Marketplace with AI The full path to a two-sided platform — define the buyer-and-seller requirements, model the data, design the API, build roles and permissions, wire integrations, design the UI, then test, secure, and ship it. View Blueprint → Blueprint Build a CRM with AI The full path to a CRM that fits your sales process — define the contacts, deals, and pipeline, model the data that ties them together, then build the roles, integrations, and pipeline UI, and ship. View Blueprint → Blueprint Build an E-commerce Store with AI The full path to a store you own end to end — model the catalog and orders, design the storefront and checkout, add customer accounts and payments, then secure it, test it, and ship. View Blueprint →

Where to go next

Recommended next workflow AI Security Review Workflow Review code for what an attacker would do, not just what tests catch — anchor the model as a security engineer, run a threat-focused review, then back the findings with auth and input tests. Use when You're reviewing code where a vulnerability would actually hurt — auth, input handling, anything exposed. Start this workflow

Related workflows

Coding Workflows AI API Design Workflow Design an API on its contract instead of discovering it endpoint by endpoint — model the resources, design the endpoints and payloads, pin the contract, then review it before code locks it in. Use when You're about to build or extend an API and want the resources, endpoints, and contracts designed before implementation locks them in. View Playbook → Coding Workflows AI Database Design Workflow Design a schema on its data, not a hunch — model the entities and relationships, set the constraints that protect integrity, plan indexes around real queries, then document the schema and migration. Use when You're about to create or reshape a database and want the entities, constraints, and indexes designed before the migration is written. View Playbook →

Tip: Each step's resource opens its tool pre-filled — start at step one and carry the output forward.

All playbooks