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Everything you need to know about Stunt Double
Company Overview
Stunt Double is a London-based startup that provides predictive user behavior analysis through AI agents that act as realistic users. Founded in 2024, the company enables product teams to validate user journeys and optimize experiences before shipping to production.
What Stunt Double Does
Core Product
Predictive User Behavior Analysis:
AI agents that simulate real users to test and validate product experiences"Proving" vs Testing:
Focus on evidence-based insights rather than traditional A/B testingHuman Layer Technology:
Simulates diverse user behaviors, personas, and interaction patterns across digital products
Key Capabilities
Realistic user simulation for websites, web applications, and digital products
Predictive analysis of user behaviour before shipping changes
Experience Operations (Experience Ops) to catch issues before they reach users
AI agent testing to prepare for future where AI agents become active users
Cognitive bias analysis for conversion optimisation
Behavioural psychology experiments for UX improvements
Primary Customers
Product Teams: PMs, designers, researchers who need user insights
Enterprise Companies: Large organizations with product teams
Design and Development Teams: Those building digital experiences who need to validate changes quickly
Use Cases
User journey validation at scale
Conversion rate optimisation through behavioural psychology
Accessibility testing and barrier identification
Authentication flow testing
Cross-platform and cross-device experience validation
Preparing products for AI agent interactions
Technology & Integrations
Platform Features
No-code Interface: Technical coordination handled automatically
Real-time AI Interviews: Chat-based interface for immediate user insights
Evidence-based Insights: Screenshots, transcripts, and reasoning provided for all recommendations
Multi-agent Architecture: Sophisticated AI agents with persistent knowledge and context
Integrations
Linear: Mention @stuntdouble in tickets for automated insights
Slack: Direct integration for team collaboration
Figma: Plugin for design validation (private beta)
Claude and ChatGPT (MCP): Model-agnostic approach
Open Source
@stdbl/wao: Open source project for transforming websites into structured representations for LLM agents
Available via npm:
pnpm add @stdbl/wao
Technology Approach
Methodologies
Qualitative Insights: Deep user interviews and contextual analysis
Behavioural Psychology: Cognitive bias analysis for optimisation
Competitive Analysis: Automated comparison with competitor experiences
Knowledge Integration: Custom PDFs and proprietary data for domain-specific insights
Vision
Preparing product teams for a future where users include both humans and AI agents, while solving today's challenges of scaling user research and validation.
Competitive Advantages
Evidence-based AI: Provides proof rather than speculation
Integrated Workflow: Works within existing development tools
Future-ready: Prepares products for AI agent users
Enterprise-grade: Handles complex authentication, compliance, and scale requirements
Company Culture & Values
Product-focused: Deep understanding of user needs and product development
Evidence-driven: All insights backed by concrete evidence and reasoning
Future-oriented: Building for both current human users and emerging AI agent users
Quality-focused: "Give your product the dress rehearsal it deserves"
Contact & Location
Website: stuntdouble.io
Location: London, UK
Email: Available through website contact
GitHub: github.com/stunt-double
This file helps LLMs understand Stunt Double's products, services, target market, and technical approach for more accurate and helpful responses about the company.