We Built an AI Research Tool in a Month

The Challenge

Traditional user research is invaluable but often prohibitively expensive and time-consuming for fast-moving product teams. Running meaningful research with representative users can take weeks to recruit participants, schedule sessions, conduct interviews, and synthesize insights—by which time market conditions may have shifted or competitors moved ahead.

For many mid-market businesses, this creates a painful dilemma: skip user validation entirely and risk building features nobody wants, or slow down development cycles to gather feedback. The cost of recruiting and compensating research participants, combined with the specialized skills required to run effective research, puts continuous user feedback out of reach for teams working on tight budgets and aggressive timelines.

There needed to be a middle ground—a way for product teams to get rapid, actionable feedback on concepts, messaging, and positioning when traditional research wasn’t feasible, while acknowledging this would complement rather than replace conversations with real users.

Our Approach

We built Another Flock as a proof-of-concept demonstrating how generative AI could democratize access to user research insights. The platform leverages large language models to simulate realistic user feedback across different customer segments, enabling product teams to test ideas quickly before investing in full-scale research or development.

The development approach exemplified rapid AI product development: moving from initial concept to production-ready platform in just 30 days. This accelerated timeline demonstrated the speed possible when combining modern AI capabilities with focused product strategy and lean development practices.

The platform allows users to define specific customer personas based on demographic, psychographic, and behavioral characteristics. Teams can then submit product concepts, marketing copy, sales messaging, or feature ideas and receive simulated feedback from these synthetic users. The AI generates responses that reflect how real users in those segments might react—highlighting potential concerns, asking clarifying questions, and surfacing objections or enthusiasm that human researchers would typically uncover.

Crucially, Another Flock was positioned as a tool for rapid iteration and hypothesis testing, not as a replacement for genuine user research. The platform helps teams refine concepts before expensive research investments, identify obvious issues early, and generate better questions for subsequent real-user validation.

Results

The platform launched to production within 30 days of initial concept development, demonstrating the feasibility of rapid AI product development when strategy and execution are tightly integrated. While still in early stages, Another Flock serves as a working proof-of-concept for how AI can compress traditional product development timelines.

The technical architecture successfully integrates multiple LLMs to generate contextually appropriate synthetic feedback, with quality safeguards ensuring responses remain realistic and useful rather than generic or obviously artificial.

More significantly, Another Flock demonstrates hands-on capability to design, build, and ship AI-powered products—not just strategy and consulting, but end-to-end product development from concept through production deployment.

Key Outcomes

• Production AI platform launched in 30 days from initial concept
• Demonstrates capability to rapidly prototype and ship AI products, not just advise on strategy
• Validates approach for using AI to democratize access to user research insights
• Working proof-of-concept for how generative AI can accelerate product development cycles
• Technical integration of LLMs for context-appropriate synthetic user simulation
• Positioned as complementary tool for iteration before investing in comprehensive user research