How to Use Multi-Step Prompts
Big tasks fail in single prompts. Multi-step prompting breaks a goal into focused, sequential prompts — each output validated, then fed into the next.
Design a role model that scales — roles derived from real permissions, the role-permission mapping, and the inheritance and edge cases before you hardcode 'isAdmin'.
RBAC done wrong becomes a tangle of special-case checks and a role nobody dares change. This prompt designs the model properly: it starts from the actual permissions the system needs, groups them into roles that map to real jobs, defines inheritance and the deny rules, and pressure-tests the edge cases (the admin who shouldn't see billing, the cross-team access) before any of it is code.
Define the permissions and actors
Note what the system does, the kinds of users, and the sensitive operations. The model is derived from real permissions, not from role names.
Open this resource in Multi-Step Prompt Builder
Load the prompt into Multi-Step Prompt Builder and fill in your context. Building it in stages keeps the permissions, roles, mapping, and edge cases each fully worked out.
Review the role model
Read the permission list, the roles, the role-permission mapping, and how the edge cases - temporary access, cross-team, service accounts - resolve within the model.
Tighten the model and re-run
Adjust any role that became an arbitrary bucket or any missing deny, then regenerate before you hardcode the checks.
The prompt puts PERMISSIONS FIRST — it lists discrete permissions as verb + resource independent of roles, then groups them into roles under a hard rule: 'Derive roles from permissions, never the reverse.' Doing it in this order stops roles from becoming arbitrary admin/user buckets, because every role has to justify itself against real permissions in the role-permission matrix.
Its EDGE CASES step names the awkward actors directly — elevated temporary access, cross-team, service accounts, the super-admin — and asks how the model handles each 'without special-casing.' Instead of an if-branch, each resolves through the permission list and explicit denies, so the OUTPUT shows how those edge cases sit inside the same role-permission matrix.
Reach for this when you're designing a role model from scratch — deriving permissions, roles, inheritance, and deny rules before any code. Its notFor points elsewhere: reviewing existing authorization code belongs to the Authorization Review Prompt, and building just the matrix artifact belongs to the Permission Matrix Prompt. This one produces the whole model, edge cases included.
It doesn't — running it through Multi-Step Prompt Builder produces a design (permission list, roles, matrix, edge-case resolution) that you run in your own assistant and must review. Workflow step 4 exists for exactly this: tighten any role that became an arbitrary bucket or any missing deny, then regenerate. It's a design aid, not a substitute for a security audit or production validation.
Big tasks fail in single prompts. Multi-step prompting breaks a goal into focused, sequential prompts — each output validated, then fed into the next.
Prompt chaining runs prompts in sequence where each output becomes the next prompt's input — the technique that turns a chat into a pipeline.
An AI workflow prompt set turns one goal into an executable sequence — objective, prompt, and expected output per step, ready to run top to bottom.
Convert scattered bug notes, Slack messages, or user complaints into structured engineering tasks with reproduction steps, severity, and root cause hypothesis.
A reusable AI agent task template with variables for objective, context, available tools, constraints, success criteria, failure handling, and output format.
'Make it good', 'be detailed', 'keep it interesting' — vague prompts get vague output. The fix is mechanical: replace every fuzzy word with a checkable instruction.
Break a big goal into a sequential prompt workflow — each step with an objective, prompt, and expected output.
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.
The full path to an applicant tracking system — model jobs, candidates, and hiring stages, generate job descriptions and screening prompts, parse résumés into structured data, design the hiring API, set roles, review security, then ship.
The full path to an inventory management system — model products, stock, locations, and movements, design the inventory API, set roles, plan supplier and POS integrations, design the UI, review data-integrity risks, then ship.
The full path to an internal admin panel — model the operational data it manages, design the management API, define RBAC and admin permissions, design the tables and forms, review risky admin actions, then ship to trusted internal users.
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.
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.
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.
Both of them logged in successfully. One of them is looking at a ticket from another company's workspace. Here's how to turn your real actors, resources and actions into a reviewable RBAC model and a permission matrix where every cell says allow, deny, or on what condition.