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Notes on fullstack engineering, AI in production, and shipping reliable software.
Featured
Learn to architect and implement full-stack web applications with LLM agents, covering backend orchestration, tool usage, and frontend interaction patterns for intelligent, production-ready systems.
· 1 min read
llm · docker
Learn to set up a self-contained local environment for LLM app development using Docker Compose. Deploy vector stores, open-source models, and FastAPI for a streamlined build process.
· 1 min
mlops · ci/cd
Learn practical strategies and tooling to build automated CI/CD pipelines for managing, versioning, and deploying machine learning models reliably from training to production.
python · ai
Learn how to efficiently deploy your PyCaret machine learning classification models as robust and scalable APIs using FastAPI, making your predictions easily accessible.
Aug 2026 · 1 min
Explore the critical security and privacy challenges of developing screen-aware AI assistants like omi, and learn how Python, LLM best practices, and FastAPI can help build them responsibly.
ai · llm
Learn to build a flexible, privacy-aware LLM application backend using FastAPI and Eden AI, a European unified API gateway for managing diverse AI models and addressing regional compliance.
python · fastapi
Master strategies for building high-performance AI inference APIs with FastAPI, addressing concurrency challenges and scaling ML model predictions for multiple users without performance bottlenecks.
posthog · python
Unlock user behavior and performance insights for your Python/FastAPI LLM application. Discover how to integrate PostHog for robust analytics, user tracking, and advanced data privacy controls.
Jul 2026 · 1 min
llm · ai
Discover how developers can strategically leverage LLMs for intelligent code review and security analysis in Python and FastAPI, boosting productivity while preserving core coding skills.
Encountered `AttributeError: 'OneHotEncoder' object has no attribute '_infrequent_enabled'`? Learn to diagnose and fix this common scikit-learn versioning issue, ensuring robust data preprocessing for your ML projects.
Jun 2026 · 1 min
Learn to leverage Hugging Face's open-source speech-to-speech models to create performant and privacy-focused local voice agents with practical Python implementation steps.
Explore how Python and LLMs provide technical solutions for detecting AI-generated content and maintaining academic integrity, offering an alternative to traditional methods like typewriters in education.