GitHub bio: I'm a self-taught developer and ethical-hacker passionate about next-gen AI solutions, data science, and building systems that scale. My journey began in childhood, tinkering with MS-DOS and experimenting with (white-hat) flood-ping attacks. I was lucky to have an uncle who worked as a Senior Dev at Microsoft — he introduced me to C#, Visual Basic, and fundamental programming concepts. This intro set the course for a lifelong love of breaking and re-building Tech.

TechEd and the future of AI + Robotics. Nano-bots injected into our bloodstream to regulate health... World domination.

TechNYC.io and iOS apps

Two time healthcare founder with two exits. Currently vibe coding D2C and Micro SaaS products and advising companies.

Healthcare, vibe coding tools,

Vibe coding D2C and Micro SaaS products. I've built 3: a nervous system reset app, a Bhagavad Gita AI in your pocket, and a patient collection tool for an MIT non profit. Two are revenue generating.

Firat Selcuk is a Senior Software Development Engineer in Test (SDET) at Early Warning®, based in Brooklyn, New York. With seven years of experience, Firat's background includes education in Mechanical Engineering from İskenderun Teknik Üniversitesi (İSTE) and a Bachelor's degree from Istanbul University. Firat is currently focused on building automated API and UI test frameworks using Java (Rest Assured, Selenium), integrating them into CI/CD pipelines (Gitlab, Harness), and deploying cloud-based test infrastructure on cloud. Firat is looking for design partners, co-founders (Technical and Business), investors, and speaking opportunities, preferring warm introductions via email.

Machine Learning & Data Engineering – Deepening knowledge in machine learning fundamentals, model lifecycle management, feature engineering, and scalable data pipelines. Blockchain & Web3 Technologies – Exploring blockchain architectures, smart contracts, DeFi systems, and decentralized application design.

Building an intelligent test automation platform that generates, executes, and optimizes API and UI test scenarios using LLM-driven analysis and modern automation frameworks. This work includes integrating the platform into CI/CD pipelines (GitLab/Harness), leveraging cloud infrastructure on AWS (EC2, Lambda, S3) and Docker for scalable test execution, and implementing automated failure analysis, test prioritization, and self-healing capabilities to improve test reliability and efficiency.