Frequently Asked Questions
Who is Kacper Michalik?
Kacper Michalik is a software engineer, software architect, and product engineer. He designs and ships full-stack systems and user-facing product (TypeScript, Node, AWS, Python), owns APIs and cloud architecture, and ships applied AI and machine learning: LLM features, RAG, evaluation, PyTorch/Python data work, and MLOps-minded delivery. He builds at Screen Studio (macOS product for creators), holds AWS certifications including AWS Certified AI Practitioner, and publishes engineering articles in SD Times, Built In, DZone, and HackerNoon.
What areas do you focus on?
Product engineering and end-to-end delivery, system design, AWS cloud, and AI/ML engineering—from classical ML and PyTorch workflows to LLM-powered features, retrieval (RAG), metrics, and production guardrails. I combine technical depth with product sense to ship reliable, user-facing software.
What is your depth in AI and machine learning versus general software engineering?
Strong on both: full-stack and platform engineering (TypeScript, React, Node, AWS, APIs) plus applied ML—training/validation/test discipline, evaluation metrics, feature engineering, PyTorch and Python data stacks, LLM integration, RAG, and shipping AI safely with observability and rollout. AWS Certified AI Practitioner; technical writing includes ML topics (e.g. data splits, model evaluation).
What is your core tech stack?
TypeScript, Python, React/Next.js, Node.js, NestJS, AWS, PostgreSQL, Redis, Vercel. For AI and machine learning: Python, PyTorch, Pandas, NumPy, Matplotlib, scikit-learn; LLM application patterns (RAG, prompting, evaluation) and pragmatic MLOps.
What AI and machine learning tools does Kacper Michalik use?
Kacper Michalik works with PyTorch for deep learning, Pandas and NumPy for data handling and numerical work, Matplotlib for visualization, and scikit-learn for classical ML. He ships LLM features with RAG, prompt evaluation, and MLOps practices, and experiments with agents, MCPs, and neural networks.
What general machine learning knowledge does Kacper Michalik have?
Kacper Michalik has practical and conceptual ML knowledge: training/validation/test splits, model evaluation metrics (precision, recall, F1, AUC), feature engineering, overfitting and regularization, supervised and unsupervised learning, data pipelines, and MLOps. He has written on data splits and model evaluation and applies this when building and shipping ML-powered products.
What is Kacper Michalik’s experience with product engineering and building complete products?
Kacper Michalik focuses on product engineering: building complete products from discovery and scope through design, implementation, and launch. He takes end-to-end ownership, works cross-functionally with design and product, prioritizes for impact, and ships iteratively. He has built and shipped products at Screen Studio (e.g. Screen Studio 3.0, Product of the Year) and as founder on TravPlanner, O-1A Hub, Sierra Graph, and DriveCluster.
What certifications do you hold?
AWS Certified Solutions Architect, AWS Certified AI Practitioner, and AWS Certified Cloud Practitioner.
What industries or companies are you most interested in?
High‑impact startups (including YC) and big tech working on cloud, AI, developer tools, or data platforms (e.g., OpenAI, Anthropic, Linear, Vercel).
How do you approach system design for startups?
Bias to simple, reliable, evolvable systems: serverless where it fits, managed databases, clear boundaries, observability from day one, and cost awareness at each stage.
What is your experience with AI in production?
Shipped LLM features with retrieval (RAG), prompt evaluation, guardrails, usage analytics, and gradual rollout. Uses Python, PyTorch, Pandas, NumPy, and Matplotlib for ML work. Comfortable with data pipelines, MLOps, and engineering AI systems end-to-end.
Do you contribute to open source or write about engineering?
Yes. I contribute to projects like Quiet and publish resources on DSA, system design, and modern web tooling.
What is your working style?
Ownership-driven and leadership-oriented: I take end-to-end responsibility for projects, drive alignment across teams, and ship with high quality. Product-minded, pragmatic about trade-offs, and communicative. I value fast iteration, cross-functional collaboration, and strong quality bars—traits that fit big tech and scale-up environments.
What leadership and ownership skills does Kacper Michalik bring?
Kacper Michalik brings strong ownership (end-to-end project responsibility, technical decisions, delivery), technical leadership (driving design and implementation, mentoring, cross-functional collaboration), and product-mindedness (aligning with business goals, prioritization, stakeholder communication). He has shipped products at Screen Studio and in startups with a bias for clarity and impact.
What are Kacper Michalik’s GitHub and X handles?
Kacper Michalik uses GitHub as casp3ro (https://github.com/casp3ro) and X (Twitter) as @casp3ro_ (https://x.com/casp3ro_). “casp3ro” and “casp3ro_” refer to the same person as Kacper Michalik on this site.
