🧠 Case Study: AI Role-Play Simulations for Soft Skills Training
To help users build real-world soft skills like job interviews and conflict resolution, over 80 AI-powered role-play simulations were created with lifelike, adaptive training. Discover how prompt engineering, voice models, LLM evaluation, and real-time analytics brought these experiences to life.
As the demand for human-centered skills grows across industries, innovative training methods are becoming essential. Let's explore how generative AI can transform soft skills development by combining advanced language models with immersive voice-based simulations.
As an AI engineer, I was involved in building an AI conversation simulator designed to help users develop essential soft skills, such as conflict resolution, giving feedback, and interview preparation through lifelike, voice-based interactions with digital avatars.
The work focused on prompt engineering and LLM system design, resulting in over 80 customized training simulations powered by the latest advancements in AI. Each simulation was crafted to provide an immersive and highly practical learning experience.
🎯 What We Set Out to Do
Soft skills are critical in today's workplace but challenging to teach at scale. The goal was to build a platform where anyone could:
- Practice realistic workplace conversations in a safe environment
- Receive immediate, structured feedback on their performance
- Learn through applying proven conversation methodologies
The main technical challenge was creating AI avatars that could follow structured conversation flows (based on established methodologies) while maintaining natural dialogue. This required careful balancing of deterministic behaviors with enough flexibility to handle diverse user inputs.
💡 Deliverables and Milestones
80+ Realistic Role-Play Scenarios
I developed a flexible, large language model-based conversation system to help users practice and improve soft skills through immersive, voice-driven simulations. Key features include:
- 80+ custom simulations organized into modules (e.g., feedback, conflict resolution, interviews)
- Multi-language support, with full implementations in English and Spanish
- Progressive difficulty levels to guide users through increasingly complex scenarios
- Context-aware avatars with distinct personalities and adaptive behaviors
Powered by OpenAI and Anthropic models integrated via LangChain, the simulator was tested across 350+ sessions. User feedback showed that 81% found the simulations realistic and valuable, highlighting the effectiveness of this AI-driven learning approach.
The core innovation was a carefully designed prompting system, including:
- System prompts that define avatar identity, context, and methodology
- Variable substitution system for flexible scenario configuration
- Conversation history management for context-aware responses
- Length and style constraints to ensure consistent avatar behavior
Effective Real-Time Feedback
After each simulation, users received automated performance feedback from an LLM-based scoring engine. It assessed tone, clarity, empathy, and alignment with the role-play goal. This gives learners actionable tips to improve as well as a gamified learning experience with metrics to measure their progress.
System Observability
To better understand user behavior and improve content, I built a secure Cloud Function that anonymized and exported user conversations to Google Sheets. This allowed the team to analyze language patterns, training gaps, and track improvement over time.
To make the system easier to debug, improve, and scale, I integrated LangSmith for real-time LLM observability and tracing. This helped us pinpoint where conversations went off-track or became unclear, and fix them fast.
✅ Impact at a Glance
- 350+ simulations tested, 80+ deployed
- 81% of users found the conversations valuable
- Used in public employment services in Spain
- Enhanced quality and debugging with LangSmith and Google Sheets
🔧 Technologies Used
- LLMs: OpenAI GPT family, Anthropic Claude
- Frameworks: LangChain, LangSmith, Firebase
- Data Tools: Google Cloud Functions, Google Sheets
- Frontend: Avatar-based voice interface, Angular JS
- Speech pipeline: STT (DeepGram) & TTS (Google TTS)
🚀 Ready to Innovate with AI?
If you're building a virtual coach, an AI training tool, or any LLM-powered experience — I can help with:
- Designing smart, human-like prompts
- Building reliable feedback systems
- Scaling with observability and data analytics
Let's talk about how AI can elevate learning, training, or engagement in your business. Don't hesitate to start a (not AI generated) conversation by sending an email to contact@cirov.com.