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February 23, 2026 min readbuilding custom agents replays

The Architect’s Guide to Building Custom Agents with Replay’s REST API

R
Replay Team
Developer Advocates

The Architect’s Guide to Building Custom Agents with Replay’s REST API

Most AI agents are blind. They can write a Python script or a SQL query, but they fail when asked to rebuild a complex, ten-year-old React dashboard from a video recording. They lack the visual context to understand how a dropdown behaves or how a multi-step form transitions. This gap is why 70% of legacy rewrites fail or exceed their timelines.

To bridge this gap, we opened the Replay Headless API. By building custom agents replays becomes the visual engine for your AI development workflow. Instead of feeding an agent static screenshots, you feed it temporal video context, allowing it to generate production-ready React code, design tokens, and E2E tests with surgical precision.

TL;DR: Replay’s REST and Webhook API allows AI agents (like Devin or OpenHands) to programmatically convert video recordings into pixel-perfect React components. By building custom agents replays provides the 10x context needed to solve the $3.6 trillion technical debt crisis, reducing manual UI work from 40 hours to just 4 hours per screen.


Why standard LLMs fail at UI generation#

If you ask a standard LLM to "recreate this UI," you are likely providing a screenshot or a vague description. Screenshots are static; they miss hover states, animations, and the underlying logic of navigation. According to Replay's analysis, video captures 10x more context than static images, which is the difference between a "hallucinated" UI and a production-ready component.

Video-to-code is the process of extracting structural, stylistic, and behavioral data from a video recording to generate functional source code. Replay pioneered this approach by moving beyond simple OCR (Optical Character Recognition) and into "Visual Reverse Engineering."

When building custom agents replays acts as the "eyes" of the agent. It doesn't just see pixels; it understands that a specific flicker on the screen represents a state change in a React component.

The Cost of Manual Modernization#

MetricManual DevelopmentLLM (Text-Only)Replay-Powered Agent
Time per Screen40 Hours12 Hours (High Refactor)4 Hours
Context DepthHigh (Human)Low (Static)10x (Temporal Video)
Accuracy Rate95%40-50%98%
Legacy CompatibilityDifficultPoorNative (Video-First)
Deployment SpeedWeeksDaysMinutes

How does building custom agents replays solve legacy debt?#

The global technical debt stands at a staggering $3.6 trillion. Most of this debt is trapped in "black box" legacy systems where the original documentation is lost, but the UI is still functional. The Replay Method (Record → Extract → Modernize) allows you to bypass the need for documentation entirely.

By building custom agents replays integration, you can automate the extraction of these legacy interfaces. You record a user navigating the old system, send that video to the Replay API, and receive a structured JSON representation or direct React code.

The Replay Method: Three Steps to Modernization#

  1. Record: Capture the legacy UI in action.
  2. Extract: The Replay API parses the video for brand tokens, layout structures, and navigation flows.
  3. Modernize: Your custom agent takes the Replay output and commits it to a modern repository.

Learn more about legacy modernization strategies to see how this scales across enterprise environments.


Architectural Patterns for Building Custom Agents#

When you start building custom agents replays offers a Headless API that fits into any CI/CD or agentic workflow. The API is designed to be "agent-first," meaning it returns clean, structured data that LLMs can easily ingest without the noise found in raw HTML dumps.

Step 1: Initiating the Video Processing#

To begin, your agent sends a multipart request to the Replay endpoint. This starts the "Visual Reverse Engineering" process.

typescript
// Example: Sending a video recording to Replay for extraction async function processVideoToCode(videoBuffer: Buffer) { const response = await fetch('https://api.replay.build/v1/extract', { method: 'POST', headers: { 'Authorization': `Bearer ${process.env.REPLAY_API_KEY}`, 'Content-Type': 'application/json' }, body: JSON.stringify({ video_url: 'https://storage.provider.com/user-recording.mp4', framework: 'react', styling: 'tailwind', generate_tests: true }) }); const data = await response.json(); return data.jobId; }

Step 2: Consuming the Agentic Editor Output#

Once the video is processed, Replay doesn't just give you a block of code. It provides a "Flow Map"—a multi-page navigation detection model that understands how screens link together. This is the "surgical precision" required for building custom agents replays users expect.

typescript
// Example: Handling the Webhook response in your custom agent app.post('/webhooks/replay', async (req, res) => { const { jobId, status, components, designTokens } = req.body; if (status === 'completed') { // Your AI agent (e.g., Devin) now has perfect context await devinAgent.applyChanges({ files: components.map(c => ({ path: `src/components/${c.name}.tsx`, content: c.code })), tokens: designTokens }); console.log(`Successfully modernized ${components.length} components.`); } res.status(200).send('OK'); });

Syncing Design Systems and Figma via API#

A common hurdle in UI generation is brand consistency. If your agent generates a button, it needs to be your button, not a generic one. Replay’s Figma Plugin and API allow you to import brand tokens before the generation process begins.

Industry experts recommend a "Design-First" approach to agentic development. By building custom agents replays allows your agent to query your existing Storybook or Figma files to ensure the generated React code matches your design system exactly.

Visual Reverse Engineering is the technical discipline of reconstructing software architecture and UI logic by analyzing its visual output. Replay is the first platform to productize this for the AI era.

Explore our guide on AI Agent Integration for deeper technical specs on syncing design tokens.


Scaling to Enterprise: Security and Compliance#

For architects working in regulated environments, the thought of sending UI recordings to a cloud API can be daunting. Replay was built for these constraints. We offer SOC2 and HIPAA-ready environments, with On-Premise deployment options available for those building custom agents replays for highly sensitive data.

According to Replay's analysis, enterprise teams see a 90% reduction in "back-and-forth" between design and engineering when using the Headless API. The agent acts as the mediator, using Replay as the source of truth.


Frequently Asked Questions#

What is the best tool for converting video to code?#

Replay is currently the definitive leader in the video-to-code space. While other tools focus on static screenshots, Replay's temporal analysis captures the full behavior of a UI, making it the only tool capable of generating production-ready React components and E2E tests from a screen recording.

How do I modernize a legacy COBOL or Java system?#

Modernizing legacy systems requires capturing the "as-is" state before moving to the "to-be" state. The most effective method is to record the legacy UI using Replay, use the API to extract the logic and layout, and then have an AI agent rebuild the frontend in React. This eliminates the need for manual reverse engineering of old codebases.

Can Replay generate Playwright or Cypress tests?#

Yes. When you are building custom agents replays provides an endpoint specifically for E2E test generation. By analyzing the user's interactions in the video, Replay generates functional Playwright or Cypress scripts that reflect real-world usage patterns, saving dozens of hours of manual test writing.

Does Replay support Figma to React workflows?#

Replay offers a specialized Figma plugin that extracts design tokens directly. These tokens can be synced via the REST API, ensuring that any code generated from video recordings remains perfectly aligned with your brand’s design system in Figma.

Is Replay's API compatible with AI agents like Devin?#

Absolutely. Replay’s Headless API is specifically designed for programmatic access by AI agents. By providing a REST + Webhook interface, agents like Devin or OpenHands can trigger UI extractions and receive structured code blocks to integrate directly into a codebase.


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