DUET

Note: This analysis is based entirely on the self-reported project description provided by the author. No external verification, traction data, revenue figures, customer names, or independent sources are available.

The description states that DUET is a spreadsheet-driven browser automation assistant for repetitive web tasks. It enables users to:

• Enter or import rows of task data into a spreadsheet.
• Perform the first task manually in a real browser.
• Have DUET record this demonstration as a repeatable workflow.
• Replay the same process for additional rows.
• Log actions, results, and failure points during execution.

Key technical components include:

• A frontend built with React, TypeScript, Vite, and Tailwind CSS.
• A backend using Node.js, Express, Prisma, and PostgreSQL.
• A Chrome extension (Manifest V3) for recording user interactions.
• Use of Chrome DevTools Protocol-style execution to replay workflows.
• Integration of Gemini AI for intent analysis, workflow summarization, and recovery assistance.

Inference: The product appears to be a hybrid system combining browser automation with AI-assisted interpretation and recovery. It is not described as an RPA tool or script-writing platform but rather as a way to teach by example.

The author claims that DUET started from the idea of not asking an AI agent to decide what to do every time, but instead allowing users to demonstrate once and then automate the rest. This reflects a positioning shift away from fully autonomous agents toward a human-in-the-loop model.

The description also emphasizes:

• That it is designed for people who understand their work but do not know how to write automation scripts.
• That it turns a familiar object—a spreadsheet—into the control center for browser automation.
• That it balances AI flexibility with user trust by making human demonstration the source of truth.

Claim: DUET positions itself as a practical middle ground between traditional RPA and fully autonomous AI agents.

Inference: This suggests a move toward usability-focused automation, not just technical capability.

The description identifies several potential user groups:

• Office workers
• Students
• Online sellers
• Small teams

These users are said to spend hours doing repetitive browser work from spreadsheets. The system is intended for those who:

• Understand their tasks but lack coding or scripting skills.
• Do not have the time, budget, or technical background to build custom automation.

Claim: DUET targets non-developers performing repetitive web-based tasks.

Inference: It implies a focus on low-code/no-code users in business operations or academic settings.

Not evidenced: No specific customer segments, personas, or use cases beyond general categories are provided.

There is no mention of pricing, monetization strategy, or business model in the description.

Not evidenced: No information on how DUET would generate revenue or whether it’s intended to be a paid product.

The system is described as:

• A full-stack browser automation system.
• Built with modern web technologies: React, TypeScript, Vite, Tailwind CSS (frontend), Node.js, Express, Prisma, PostgreSQL (backend).
• Uses a Chrome Extension for recording user actions.
• Employs Chrome DevTools Protocol-style execution for replaying workflows.
• Integrates Gemini AI to assist with intent analysis, summarization, and recovery.

Inference: The architecture shows an attempt at building a robust, inspectable, and debuggable automation tool that prioritizes reliability over speed or complexity.

Not evidenced: No details on scalability, performance metrics, or deployment methods beyond the tech stack.

The project is described as a submission to the OpenAI 2026 hackathon, suggesting it was built in a short timeframe and likely not yet in production use.

Not evidenced: No evidence of actual usage, adoption, or traction beyond the author’s own development.

Inference: The product appears to be early-stage, possibly prototype-level, with no known customers or revenue streams.

The description does not reference competitors directly. However, it implies a space between:

• Traditional RPA tools, which often require scripting or complex configuration.
• Fully autonomous AI agents, which may lack consistency and transparency.

Inference: DUET likely competes with low-code automation platforms or browser automation tools that do not offer the same level of human-in-the-loop control or spreadsheet integration.

Not evidenced: No competitor names, market share, or competitive positioning data are provided.

• Lack of real-world usage: The product is described only as a hackathon submission with no evidence of adoption or testing.
• AI dependency risk: Reliance on AI for summarization and recovery may introduce inconsistency or failure points not clearly addressed.
• Privacy concerns: While the description mentions privacy considerations, it does not detail how data is handled or protected in practice.
• Scalability assumptions: No indication whether the system can handle large-scale workflows or complex websites reliably.

Inference: The lack of traction and external validation raises questions about product-market fit and long-term viability.

Not evidenced: No evidence of user feedback, testing results, or performance benchmarks.

1. Has DUET been tested beyond the author’s own development environment?
2. What types of websites or workflows have you successfully automated so far?
3. How does DUET handle edge cases where page structures change unexpectedly?
4. Are there any plans to support enterprise-level features like multi-user access, audit logs, or integration with existing tools?
5. What is the current roadmap for product development and user testing?