Workflow
AI Product Requirements Workflow
Turn a fuzzy business need into requirements a team can build from — interrogate the need into concrete requirements, shape them as user stories, and write the PRD.
Build an Inventory Management System with AI
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.
Overview
An inventory management system is an operational state machine, not a storefront. It isn't a catalog with a cart and checkout, and it isn't two-sided buyer/seller matching — its core is stock: the products, the locations they live in, the quantities on hand, and the movements (receipts, transfers, sales, adjustments) that change those quantities and must always reconcile. The failure mode that defines the domain is the count that drifts from reality — a stock level that says ten when the shelf has eight — so data integrity is the whole game. This project builds that system end to end: it frames the inventory requirements and operating rules, models the products/stock/locations/movements, designs the inventory API, sets the roles and access for warehouse and operations staff, plans the supplier, POS, or warehouse integrations that feed and drain stock, designs the inventory management UI, reviews the security and data-integrity risks (negative stock, lost movements, unauthorized adjustments), and prepares the release. It is deliberately not an ecommerce store (catalog/cart/checkout) and not a marketplace (matching) and not a CRM (contacts/deals) — it's operational stock and movement state. NewPrompt designs the system and generates the prompts, schemas, and contracts for each stage; you run those in your own AI tool and own the implementation and the data. It does not manage your inventory, hold stock counts, or run AI on its servers — it gives the build a movement model where every quantity change is accounted for instead of a spreadsheet that quietly goes out of sync.
The journey
Each stage runs a NewPrompt workflow, with a supporting resource and tool. Work them in order — the output of each stage feeds the next.
See the execution map →Define & Scope
Clarify what you're building and for whom.
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Define inventory requirements and operating rules
Frame what's being tracked and the rules around it — what counts as a location, which movements are allowed, how adjustments are authorized — before modeling, so the stock logic reflects the real operation instead of a generic table.
Outcome Inventory requirements and the operating rules the system enforces.
Design
Design the right solution before building.
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Model products, stock, locations, and movements
Design the data the system runs on — products, the locations they're stocked in, quantities on hand, and the movements (receipts, transfers, sales, adjustments) that change them — so every quantity change is a recorded movement, not an untraceable edit.
Outcome A products/stock/locations/movements schema where quantities reconcile. -
Design the inventory API
Design the API the system is operated through — receive stock, transfer between locations, adjust a count, query availability — as a contract, so the UI and integrations develop against a stable surface that keeps movements consistent.
Outcome An API contract for stock movements and inventory queries. -
Define roles and access control
Model who can do what — warehouse staff, operations managers, auditors — so a stock adjustment or a movement is scoped to the right people, because an unauthorized count change is a data-integrity problem, not a convenience.
Outcome Roles and permissions for stock movements and adjustments. -
Plan supplier, POS, or warehouse integrations
Design the integrations that feed and drain stock — supplier feeds, POS sales, warehouse or 3PL events — with the retries and reconciliation that keep a dropped event from silently desyncing the count.
Outcome Supplier, POS, and warehouse integration contracts with reconciliation. -
Design the inventory management UI
Design the component system the system is used through — the stock dashboard, the movement entry forms, the location views — as reusable components, so the interface stays consistent as locations and product lines grow.
Outcome A component system for stock views, movement entry, and locations.
Build & Refine
Build, test, secure, and make it production-ready.
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Review security and data-integrity risks
Review the system the way an attacker — and a bad data path — would: account access, the movement API, and integrity risks like negative stock, lost movements, or unauthorized adjustments, backed by tests, before it runs the real operation.
Outcome Access, the movement API, and integrity risks reviewed for vulnerabilities.
Ship & Validate
Ship with confidence and validate results.
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Prepare the release
Cross from built to live — readiness checks, a deploy and rollback plan, and monitoring on stock accuracy and integration health — so launch is deliberate and a desync or a failed supplier feed is caught fast.
Outcome The inventory system shipped with a rollback path and launch checks.
Expected outcome
An inventory management system designed end to end — a products/stock/locations/movements data model, an inventory API, roles and access, supplier/POS/warehouse integrations, an inventory UI, a security and data-integrity review, and a release plan — so stock levels reconcile against real movements instead of a spreadsheet that drifts out of sync.
Best for
- Modeling products, stock levels, locations, and stock movements
- Inventory flows that need supplier, POS, or warehouse integrations
- Operations teams that need stock counts reconciled and data integrity reviewed
Not for
- A product catalog with cart and checkout — that's the Ecommerce Store project
- Two-sided seller/buyer matching — that's the Marketplace project
FAQ
How is this different from the Ecommerce Store project?
An ecommerce store models products, a cart, and checkout — selling to a customer. This models stock — products, locations, quantities, and the movements that change them — and the reconciliation logic that keeps counts accurate. The data model and the journey are about operational inventory state, not buying.
How is this different from a Marketplace?
A marketplace matches buyers and sellers. This is a single operator's inventory: stock in locations, moved by receipts, transfers, sales, and adjustments. No two-sided matching, no seller onboarding — just stock state and the movements that change it.
Does NewPrompt manage my inventory?
No. NewPrompt designs the system and generates the prompts, schemas, and contracts. You run them in your own AI tool and build and operate the system yourself. NewPrompt does not hold stock counts, track movements, or run AI.
How do I build an inventory management system with AI?
You build it across eight stages you run in your own AI tool: define the inventory rules, model products, stock, locations, and movements, design the inventory API, set roles and access, plan supplier and POS integrations, design the UI, review data-integrity risks, then prepare the release. NewPrompt generates the prompts and contracts; you implement each stage and own the data.
What inventory data do I need before building the system?
Before modeling, you need your products, the locations stock lives in, the movement types you allow (receipts, transfers, sales, adjustments), and the rules for who can adjust a count. The blueprint's first two stages frame those operating rules and turn them into a products/stock/locations/movements schema where every quantity change is a recorded movement.
Does this blueprint connect to my POS or barcode system automatically?
No. The blueprint helps you plan the supplier, POS, and warehouse integrations — the contracts, retries, and reconciliation that keep a dropped event from desyncing the count — but you connect and operate your real POS, barcode, or 3PL systems yourself. There's no automatic sync or guaranteed integration; you own the connection and the data integrity.
Workflows in this project
Workflow
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.
Workflow
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.
Workflow
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.
Workflow
AI Integration & Webhook Workflow
Connect systems so they don't break each other — map the integration boundaries, design the event and webhook contracts, plan retries and failure handling, then document the integration.
Workflow
AI UI & Component Design Workflow
Structure a UI so it stays consistent as it grows — inventory the screens, break them into reusable components, specify the component system and its rules, then review the structure for drift.
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.
Workflow
AI Deployment & Release Workflow
Cross the gap between 'tests pass' and 'safe in production' — assess release readiness, plan the deploy and its rollback, and set up the monitoring and launch checks before you ship, not after.
Resources used in this project
Resource
Product Requirements Assistant
Turn a rough feature idea into a structured requirement: problem statement, acceptance criteria, and what's explicitly out of scope.
Resource
Schema Design & ERD Prompt — Entities, Relationships, and Keys
Turn product requirements and key entities into an ERD-ready schema spec: tables, fields, primary and foreign keys, relationships with cardinality, indexes, and constraints — with the modeling gaps named as open questions.
Resource
Turn a JSON Schema into a Prompt
You have the schema — fields, types, requirements. The translation into a prompt the model actually follows: schema lines, realistic example, and validation rules.
Resource
RBAC Design Prompt
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'.
Resource
Design System Spec Prompt — Components, States, and Accessibility
Turn UI requirements and component needs into a design-system spec: a component inventory with states, variants, responsive behavior, accessibility requirements, microcopy rules, and developer handoff notes.
Resource
Security Code Review Prompt
Twelve security checks — injection, auth, secrets, SSRF, privilege escalation — reviewed the way an attacker would read the code.
Resource
Production Readiness Review Prompt
SHIP or DO NOT SHIP: twelve checks on failure modes, observability, rollback, and load — the review that happens before the incident.
Tools used in this project
Tool
System Prompt Generator
Build structured system prompts from role, tone, constraints, and model target.
Tool
SQL Optimization Prompt
Build evidence-based SQL optimization prompts — goal, platform, and the evidence you have turn into a query tuning contract.
Tool
JSON Output Prompt Builder
Build prompts that return structured data — JSON first, with YAML, XML, and CSV modes — parseable every time.
Tool
Multi-Step Prompt Builder
Break a big goal into a sequential prompt workflow — each step with an objective, prompt, and expected output.
Tool
Markdown Output Builder
Build prompts that produce documents in a fixed structure — headings, sections, and tables.
Tool
Code Review Prompt Generator
Generate code review prompts for any scope — snippet, file, diff, or full pull request — with focused review rules.
Ways to Use This Project Path
Practical project ideas you can build from this base project path — each opens in the Project Advisor.
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