Build a SaaS MVP with AI Execution Map — Roadmap, Workflows & Tools

Step 1 of 11

Define what you're actually building

A requirements document the build can start from.

Phase Define & Scope

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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. Resource Product Requirements Assistant Turn a rough feature idea into a structured requirement: problem statement, acceptance criteria, and what's explicitly out of scope. Tool System Prompt Generator Build structured system prompts from role, tone, constraints, and model target.

Step 2 of 11

Cut it to an MVP

A first-release scope small enough to actually ship, with a success signal.

Phase Define & Scope

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Workflow AI MVP Planning Workflow Cut a product idea down to the smallest first release that proves the core value — separate the real must-haves from everything that can wait, then define the MVP and its success signal. Resource Startup Advisor Role Prompt An expert startup advisor role prompt — stage-aware, capital-efficiency-minded, and built to name the riskiest assumption in any plan instead of cheering it on. Tool Role Prompt Generator Generate expert role prompts — perspective, responsibilities, and decision criteria, not just "act as".

Step 3 of 11

Design the architecture

An architecture decided on its trade-offs and documented.

Phase Design

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Workflow AI Project Architecture Workflow Design a system's architecture on its real trade-offs instead of a confident diagram — put the model in an architect's seat, work the decisions one at a time, and write down the why. Resource Software Architect Role Prompt Make AI act as a software architect — system design, scalability, service boundaries, and trade-offs — instead of jumping straight to code. Tool Role Prompt Generator Generate expert role prompts — perspective, responsibilities, and decision criteria, not just "act as".

Step 4 of 11

Design the API contract

An API contract the build develops against.

Phase Design

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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. 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. Tool JSON Output Prompt Builder Build prompts that return structured data — JSON first, with YAML, XML, and CSV modes — parseable every time.

Step 5 of 11

Design the data model

A schema designed on its entities, constraints, and queries.

Phase Design

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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. 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. Tool SQL Optimization Prompt Build evidence-based SQL optimization prompts — goal, platform, and the evidence you have turn into a query tuning contract.

Step 6 of 11

Review the code as you build

Changes reviewed for correctness and design before they merge.

Phase Build & Refine

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Workflow AI Code Review Workflow A complete AI-assisted review pass — not one prompt — that ends with ranked findings, tests guarding behavior, and a refactor plan when one is warranted. Resource Code Review Prompt — the Review Contract "Review this code" gets shallow comments. The review contract gets findings with severities, a checklist, and a verdict. Tool Code Review Prompt Generator Generate code review prompts for any scope — snippet, file, diff, or full pull request — with focused review rules.

Step 7 of 11

Lock behavior down with tests

Tests that catch real regressions, not green decoration.

Phase Build & Refine

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Workflow AI Test Generation Workflow Build a test suite that fails for real reasons, not green decoration — coverage across unit, integration, and edge cases, then a review for the gaps. Resource Unit Test Prompt — Isolation Done Right Mock the dependencies, test the business logic, one behavior per test — the unit testing contract that bans plumbing tests. Tool Test Case Prompt Generator Build test generation prompts — unit, integration, or E2E — with framework modes and edge-case coverage rules.

Step 8 of 11

Run a security pass before launch

The exposed paths reviewed for vulnerabilities and guarded by tests.

Phase Build & Refine

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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. Resource Security Code Review Prompt Twelve security checks — injection, auth, secrets, SSRF, privilege escalation — reviewed the way an attacker would read the code. Tool Code Review Prompt Generator Generate code review prompts for any scope — snippet, file, diff, or full pull request — with focused review rules.

Step 9 of 11

Keep the AI feature costs in check

AI feature costs measured and trimmed before they hit production volume.

Phase Build & Refine

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Workflow AI Cost Optimization Workflow Cut what an AI feature costs without dumbing it down — price the prompt as it runs today, see where the tokens go, trim the waste, and re-measure to prove the saving holds at scale. Resource Estimate Cost per 1,000 Calls A classification call costs a fraction of a cent — until you run a million of them. This prices a small repeated prompt at the scale that actually bills. Tool Token Counter Estimate how many tokens a prompt is and what it costs — honest ranges across GPT, Claude, and Gemini, with per-call and per-1,000-call pricing.

Step 10 of 11

Ship the first release

The MVP deployed with a rollback path and monitoring.

Phase Ship & Validate

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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. 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. Tool Markdown Output Builder Build prompts that produce documents in a fixed structure — headings, sections, and tables.

Step 11 of 11

Validate it against its success signal

A validation verdict on the shipped MVP and an iterate / pivot / scale decision.

Phase Ship & Validate

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Workflow AI Product Validation Workflow Find out whether the thing you shipped actually worked — define the success metric, plan the measurement, classify the real evidence, then render a verdict and an iterate / pivot / scale decision. Resource Product Validation Report Prompt Consolidate the whole validation into one shareable report — the success metric, the evidence, the hit / partial / miss verdict, and the iterate / pivot / scale decision, in a form the team and stakeholders can act on. Tool Markdown Output Builder Build prompts that produce documents in a fixed structure — headings, sections, and tables.