For over many years, I've been the silent guardian of software excellence. My journey began in the trenches of software quality assurance, where I mastered the art of turning "it works" into "it works flawlessly." From stress-testing code for agile Silicon Valley startups, I've honed a meticulous eye for detail and a passion for bridging technical robustness with real-world user needs.
In the early days, I lived by the mantra: "A bug unresolved today becomes a crisis tomorrow." This mindset drove me to architect testing frameworks for applications across industries like education, healthcare, transportation and logistics—ensuring not just functionality, but scalability, stability, and compliance. But technology never sleeps, and neither do I.
When Agile disrupted traditional QA, I immersed myself in CI/CD pipelines and automation tools like Selenium and Cypress and Playwright. Earned certifications in cloud technologies and data analytics to stay ahead of shifting industry demands.
My focus today is on AI's transformative potential - learning about models, exploring AI agents, and stress-testing conversational AI chatbots, including penetration testing AI tools to detect vulnerabilities. My QA roots now fuel a new mission: ensuring AI systems are ethical, reliable, and human-centric.
Because Quality Matters More Than Ever. Testing a chatbot isn't just about debugging code—it's about anticipating how a nurse might phrase an urgent query, or how cultural nuances could derail a financial advice bot. My decade of breaking (and fixing) systems gives me a unique lens to: validate AI model accuracy and bias mitigation; design test scenarios for autonomous AI agents; build guardrails for generative AI outputs.
I'm laser-focused on becoming a bridge between QA's rigorous legacy and AI's uncharted future. Because in a world racing to adopt AI, someone needs to ask: "But what if it fails?"—and have the technical grit to ensure it doesn't.
Let's build systems that aren't just smart, but wisely trustworthy.
I build AI apps that mix technologies end-to-end—from weather-aware styling to voice assistants that actually hold a conversation. Right now I'm experimenting with AI Bento Box (www.aibentobox.com), where kids get a coach-like homework buddy instead of quick answers. Every release teaches me where AI excels and where human intuition still leads the way.
Built Fashion Weather (www.fashionweather.ai)—an AI stylist that checks the forecast, recommends what to wear, and renders photorealistic outfits with OpenAI GPT-3.5 and Ai Image generation. The app runs on a Python backend and JavaScript frontend connected through Model Context Protocol (MCP), keeping Google Weather API, OpenAI, and image models in sync via JSON-RPC 2.0 messaging. Deployed on AWS Elastic Beanstalk, it curates weather-ready looks from boardroom to date night, suggesting brands that span diffusion to luxury—rain or shine.
I built an AI voice agent for calls that sounds convincingly human—it handles inbound and outbound conversations, schedules tasks, and stays on script. Who said robots can’t be charming? Happy to demo it if you're curious!
Browse my latest notebooks for reproducible walkthroughs that combine Python, requests, pandas, numpy, and plotly for analysis and data story visualization. Explore the repo here: ApiDataVisualization
Phone: (650) 675-2252
Email: tatiana@yeremenko.org
Gmail: tatiana.v.yeremenko@gmail.com
Location: San Francisco Bay Area, CA