# Dezycro Dezycro is an operations layer for AI coding agents that provides product context, steers work, verifies behavior against requirements, and records decisions. It is designed for developers, product teams, and organizations that want to use agents without giving Dezycro access to source code. - Findings24: - Website: - Pricing: Freemium - Categories: AI Agent Infrastructure, AI Developer Tools, AI Testing Assistant ## What is Dezycro? Dezycro is an operations layer for AI coding agents. It does not write the application code itself; instead, it supplies agents with product context, accepts steering instructions while work is in progress, verifies the resulting behavior against requirements, and records the decisions and evidence for later work. The product is built for workflows using agents such as Claude Code and Cursor. Teams can organize PRDs, technical specifications, flow maps, OpenAPI information, tasks, decisions, and reference documents into a shared context. Dezycro then generates checks from the intended behavior and runs them against the product’s running API, helping identify missing endpoints, skipped flow steps, and requirements that drifted during implementation. Dezycro says it does not access repository source code: repositories are not cloned, uploaded, or indexed. Its verifier runs in the user’s environment, while specifications, journeys, results, and project history are kept in a workbook that can be exported. ## What can Dezycro do? ### Provisioned agent context Give agents product and technical specifications, flow maps, notebooks, OpenAPI information, tasks, decisions, and reference documents before they begin work. ### In-run direction Use a per-feature command inbox to send new instructions or invalidate stale work while an agent is running, without having to manage every terminal step. ### Requirement-based verification Generate checks from PRDs and API specifications independently of the coding agent, then run them against the product’s running API to expose differences between intended and observed behavior. ### Flow and requirement modeling Represent user journeys as steps and decision points, including alternate or abandoned paths, and flag conflicts when a new requirement contradicts an existing one. ### Shared workbook and history Keep decisions, assumptions, tasks, blockers, specifications, and verification evidence in one workspace, with version history for PRDs and technical requirements. ### Agent and documentation connections Use the CLI, Claude Code plugin, MCP server, or API, and bring in context from Linear, Atlassian Confluence, and document ingestion. ## Use Cases ### Prepare an agent for a new feature A product or engineering team can assemble the feature’s PRD, technical requirements, journeys, decisions, and existing documentation before handing the task to an AI coding agent. ### Catch behavior that agent-authored tests miss Teams can generate independent checks from the requirements and run them against a running API to find missing routes, skipped stages, or incorrect responses that the agent’s own tests did not identify. ### Correct work during an active run A developer or product owner can issue a correction or invalidate outdated work through the feature command inbox instead of waiting for implementation to reach review. ### Carry project knowledge into later work Teams can retain reusable notebooks, skills, decisions, and verification history in the workbook so subsequent agent sessions start with documented context rather than reconstructing it. ## Frequently Asked Questions ### Does Dezycro need access to my repository? No. Dezycro says that it does not clone, upload, index, or read repository source code. Its verifier runs in the user’s environment against a running API. ### Is Dezycro itself a coding agent? No. Claude Code and Cursor write the code; Dezycro provides the surrounding context, in-run direction, verification, and recorded project knowledge. ### Which coding agents and services does it support? The site lists Claude Code and Cursor through the Dezycro plugin, CLI, and MCP server. It also lists Linear and Atlassian Confluence connectors for bringing issues and existing documentation into context. ### How does its verification differ from ordinary CI tests? Dezycro generates checks from the API specification and PRD independently of the coding agent. The checks are intended to compare the built product with the specified behavior rather than only confirm tests written by the same agent pass. ### Can Dezycro fit into an existing workflow? The product says teams can keep their existing agent and repository while Dezycro runs alongside them. Generated checks can also plug into a CI/CD pipeline as ongoing sanity tests. ## Quick Facts - **Product type**: AI coding-agent operations layer - **Coding agents listed**: Claude Code and Cursor - **Verification target**: Running API in the user’s environment - **Source-code access**: Repository source is not cloned, uploaded, or indexed - **Interfaces**: CLI, Claude Code plugin, MCP server, and API - **AI key providers**: OpenAI, Anthropic, and Bedrock