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Notes on fullstack engineering, AI in production, and shipping reliable software.
Featured
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 read
python · ai
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.
Aug 2026 · 1 min
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.
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.
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.
Jun 2026 · 1 min
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.
Explore the practical implications of token usage differences between Claude Opus 4.6 and 4.7. Learn to measure and optimize LLM token consumption in Python for cost-effective AI applications.
May 2026 · 1 min
ai · workflow
Discover practical strategies for integrating AI tools and LLMs into your Python/TypeScript development workflow. Automate tasks, enhance code quality, and accelerate project delivery with smart AI assistance.
Apr 2026 · 1 min
Discover how Claude Code Routines streamline the orchestration of LLM-powered coding tasks, enabling Python developers to build robust, predictable, and AI-driven applications.
python · fastapi
Learn to apply the Miller Principle (7 ± 2) to simplify Python applications, FastAPI APIs, and LLM prompt design, effectively reducing cognitive load and improving maintainability.
Uncover the vulnerabilities and biases in current AI agent benchmarks and learn practical Python strategies to build more robust, secure, and trustworthy LLM evaluation frameworks.