Start with Reqode

From Requirements to Code. Verified.

Reqode helps AI build what you actually need. It produces clear specifications, guides implementation, and helps you catch mismatches before they turn into rework.

For teams building with AI coding agents like Codex, Cursor, or Claude Code.

Start with Reqode See how it works

Challenges

People and AI Lose Product Context

Product decisions get scattered across chats, documents, and code. Team members and AI agents repeatedly reconstruct the same context, missing connections between requirements, APIs, data, and UI behavior.

Architecture Drifts as the Codebase Grows

Local changes drift from architectural rules, component responsibilities, and subsystem boundaries that the agent cannot see.

Product Changes Need Too Many Handoffs

You break a product change into database, API, and UI tasks, repeat the context, and connect the results yourself. Each step needs another prompt, another handoff, and more of your attention.

How Reqode Solves It

Reqode gives teams a connected, branch-aware product and implementation model, exposes focused context to AI agents, and verifies work against that source of truth. Use the model to guide the next feature, then use verification and reviewed changes to keep it current.

  1. Product model Requirements, APIs, data, UI, architecture, linked code
  2. Feature specifications Reviewed changes with connected context
  3. Agent implementation A defined change guided by the model
  4. Verification & reviewed updates Check the result and resolve differences
  5. Product model Updated context for the next change
Ready for the next change

Capabilities

Specification Management
Manage connected requirements, data entities, APIs, interfaces, wireframes, and test cases in a versioned product model, with traceable relations and branch-aware revisions.
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Change Management
Define each product change through a Change Request that connects its goal, affected specification revisions, project branch, implementation impact, and linked issue.
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Architecture & Software Units Blueprints
Define subsystem architecture and software unit blueprints with implementation rules, responsibilities, dependencies, and file boundaries linked to product specifications.
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AI Assistants
Use AI assistants to refine specifications, design test cases, develop architecture, and review implementation. Inspect structured proposals before applying changes.
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MCP for AI Coding Agents
Give coding agents branch-aware specifications, architecture guidance, software units, file traces, and Change Request context through MCP. Record and resolve Findings as work progresses.
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MCP for AI QA Agents
Give QA agents prepared test runs, cases, steps, and expected outcomes through MCP. Record execution results and update statuses, comments, and step outcomes in Reqode.
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Built for products with more moving parts

Reqode is designed for projects where a single feature touches connected data, APIs, interfaces, and business rules across your system.

Growing project complexity

  1. Prototype

    One repository
    A few data entities
    One main user flow

  2. Focused product

    One app and its backend
    Dozens of data tables
    Several user roles

  3. Connected product

    Multiple apps or services
    Shared data and API contracts
    Roles and cross-app workflows

  4. Complex system

    Multiple repositories
    Hundreds of data tables
    Many roles and integrations

  • Prompt engineering: prototypes through focused products.
  • Open-source spec frameworks: focused products into complex systems, overlapping with prompts and Reqode.
  • ReqodeConnected context across the system: from focused products through complex systems.
Complexity comes from dependencies and business rules, not repository or table counts alone.
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Explore your product specifications
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Explore your product specifications

Start from FieldDesk’s dashboard and explore Requirements, Data Entities, User Interfaces, or API Operations.

Structured, Verified Memory for AI Agents

Reqode gives AI coding agents a structured, verified memory of your product: requirements, specifications, architecture rules, software units, and change history. Through MCP, agents retrieve focused, branch-aware context for each task, while Reqode's verifiers keep that source of truth aligned with the code.

Reqode connects product specifications, AI agents, implementation, and verification.

Start with one product area

Building a new product

Define the first feature before implementation. Its specifications become context for the next change.
Start a new product

Evolving an existing product

Connect the code and specifications for one product area, check for mismatches, and use the reviewed model to guide its next change.
Start with existing software

Frequently Asked Questions

Which coding agents can I use?

Use an MCP-compatible agent such as Codex, Cursor, or Claude Code. Reqode supplies product and implementation context while the agent works in your coding environment. See MCP for Coding Agents.

Can I start with existing code?

Yes. Start with one relevant area, connect its repository context, and review the specifications that describe it. You can expand the model as you make further changes.

Who prepares the specifications?

Your team can write them directly or use AI Analyst to clarify a feature and propose changes. Review the proposed diff and apply the accepted result.

What does my team still decide?

Your team chooses the intended behavior, accepts specification changes, reviews the implementation and evidence, and decides what to release.

How is the result checked?

AI verifiers inspect specifications, architecture guidance, and linked implementation within their defined scope. Test runs record execution results. Review both kinds of evidence; a completed check is not a guarantee that a feature is correct.

How does Reqode help prevent architecture drift?

Reqode connects implementation with subsystem architecture rules, unit guidelines, and component responsibilities. AI verifiers check the selected code against that guidance and record findings for your team to review. Explore architecture checks.

What if the specification needs to change?

Review the intended behavior before choosing a correction. If the product decision has changed, your team can use AI assistance to prepare a specification update, review and apply it, then check the implementation against the revised specification. Explore how to resolve a mismatch.