Operative - Web application code generation for internal APIs
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Operative: The AI Tool That Builds Internal Web Apps for You

In the world of internal tooling, frontend development for in-house APIs is often a bottleneck. Many organizations maintain powerful backends to serve operations, analytics, or internal workflows—but spinning up functional frontends for these systems is tedious, repetitive, and expensive. Developers frequently find themselves copying boilerplate, wrestling with API documentation, debugging asynchronous requests, and juggling user interface frameworks—all for apps that often won’t see public exposure.

While platforms like Retool have made strides in simplifying internal tool development, they rely primarily on connecting to external integrations and still require a lot of manual setup and UI customization. And while new AI coding tools like Cursor or Copilot help with individual tasks, they often keep developers stuck in the feedback loop: write a prompt, review the code, test it, revise the prompt, and repeat.

Operative was born to cut through this cycle. By generating and testing complete frontend applications for internal APIs—automatically—Operative removes the grunt work, letting organizations create production-grade interfaces in a fraction of the time.

How Does Operative Work?

Operative is a browser-based AI tool that automates the creation of functional web applications connected to an organization’s internal backend. Think of it as Retool meets Copilot, but for codebases you actually control—and with testing built in.

Here’s how it works:

  • Input: The user provides access to internal APIs and describes the application’s desired functionality.
  • Generation: Operative uses Claude Sonnet 4 to generate fully functional frontend code, tailored to the provided API endpoints.
  • Testing: Operative runs the generated app in a full browser environment. Its AI agent clicks buttons, scrolls through the page, captures screenshots, and checks the browser console for errors.
  • Debugging: If something doesn’t work, the AI iteratively corrects the issue. This debugging loop continues autonomously until the app functions as expected.
  • Delivery: The result is a fully operational frontend, ready to be deployed or extended by human developers.

In short, Operative combines the intelligence of modern LLMs with a powerful browser agent that verifies usability in real time, before the user even touches the code.

What Makes Operative Different from Other AI Coding Tools?

Most AI development tools—like Cursor, GitHub Copilot, or even newer IDE-integrated assistants—are helpers. They assist in specific tasks, generate snippets, and respond to prompts. But they leave the orchestration, testing, and integration up to the human.

Operative is an agent, not a helper. It takes ownership of the entire flow, from understanding the user’s intent to shipping a usable product. Its key differentiators include:

  • Real-Time Testing: Operative doesn’t just write code; it verifies it. It runs the generated applications in a browser and fixes issues before handing them off.
  • Internal Focus: Instead of working with popular external APIs like Stripe or Slack, Operative connects directly to private, internal endpoints—where the real complexity lies.
  • Live UI Feedback: Through browser-based simulation, Operative shows users how the app behaves, including screenshots of test interactions.
  • End-to-End Flow: It merges generation and debugging into a continuous loop, creating a polished product without the typical back-and-forth between AI and developer.

This "6-star experience," as the founders put it, aims to make internal tool development feel magical—almost like watching a fully staffed engineering team build your prototype overnight.

Who Are the Founders Behind Operative?

Operative was co-founded by Christopher Settles and Erik Quintanilla, long-time collaborators with a shared passion for automation, AI, and clean engineering.

  • Christopher Settles (CEO) brings deep machine learning experience from his time at Uber, where he led fraud detection and AI platform initiatives. With a background in computer science from UIUC, Chris has always gravitated toward large-scale, intelligent systems.
  • Erik Quintanilla (CTO) is a published vision researcher and seasoned software engineer with stints at CapitalOne, Amazon, and multiple startups. His work bridges AI, UI, and real-world interactivity—a perfect fit for building browser-native agents that "see" and "understand" how apps work.

Their friendship began over a decade ago in high school coding competitions and evolved into building serious tools for developers. Operative is the culmination of that shared journey—an expression of their belief that internal development shouldn't be tedious.

How Did Operative Evolve from an Open Source Experiment?

Operative didn’t emerge out of thin air. The project began as an open-source tool called Operative Web Eval Agent, designed to verify AI-generated frontend code by launching a browser agent. It ran inside tools like Cursor and gave developers a way to test and inspect their AI-generated UIs without leaving the IDE.

The open-source project quickly gained traction, accumulating over 900 GitHub stars and attracting thousands of developers experimenting with AI-assisted workflows. It was a developer’s dream—one-click validation for generated UI code, tightly integrated with the local dev loop.

That early success planted the seed: why not bring the entire workflow—code generation, visual verification, error resolution—under one roof? That question led to Operative.sh, a hosted product with significantly more power, polish, and business application.

Who Is Operative Built For?

Operative is ideal for engineering teams at mid-sized to large enterprises that maintain complex internal systems. These companies often have:

  • Dozens of microservices and APIs that are under-documented
  • Internal stakeholders requesting dashboards, tools, and CRUD apps
  • A backlog of frontend tasks that engineers deprioritize in favor of core product work
  • A desire to use AI, but with caution around correctness and integration

For these teams, Operative provides both speed and safety. The AI doesn’t just spit out unverified snippets—it tests its own work and delivers usable, correct output. That’s a critical distinction in enterprise environments where trust and functionality matter.

What Are Some Early Use Cases of Operative?

Operative is already powering a range of applications across industries. Example use cases include:

  • Internal dashboards for sales and operations teams, built by engineers in minutes instead of weeks.
  • Custom admin panels for customer support workflows, tightly coupled with internal APIs.
  • Prototyping tools for product managers to visualize new features before investing engineering hours.
  • Lightweight analytics UIs that query backend data directly and update live in the browser.

Perhaps the most viral example is a Minecraft clone—generated, debugged, and rendered by Operative entirely within the browser. While not enterprise-focused, it showcases the platform’s ability to create complex UIs and logic-heavy applications with minimal input.

What Is the Vision for Operative’s Future?

The long-term vision for Operative is to become the default way internal tools are built. As LLMs become more capable and organizations adopt AI-assisted development pipelines, Operative offers a glimpse of what’s possible: tools that think, test, and ship—not just assist.

Future directions include:

  • Expanded integrations with major code hosts, CI/CD pipelines, and permissioning tools
  • Collaboration features for teams to co-build, review, and approve AI-generated apps
  • AI agents that learn from your codebase over time to improve output quality and reduce hallucinations
  • Mobile web support and React Native compatibility for internal mobile apps

Operative is also positioned to lead the way in agentic software, where AI doesn’t just follow commands—it owns tasks end to end, autonomously producing useful results.

Why Is Operative a Startup to Watch?

In an era where AI is often more promise than product, Operative delivers something tangible. It builds real software that works, not just prototypes, not just snippets. It bridges the messy world of internal APIs and the growing capabilities of generative AI to solve an unsexy but critical problem: making internal development faster, cheaper, and more reliable.

With strong technical leadership, early traction from developers, and a clear product-market fit in the enterprise AI tooling space, Operative is one of the most exciting startups of the Spring 2025 Y Combinator batch—and a signal that the future of development may very well happen inside the browser.