MirahLabs Engineering Blog
Technical insights, architectural deep-dives, and system designs authored by our product engineers and AI research leads.
Python Performance Profiling: Finding and Fixing Bottlenecks
Before optimizing Python code, measure first. Learn how to use cProfile, py-spy, memory_profiler, and line_profiler to identify real bottlenecks—not the ones you assume.
Python Type Hints and Pydantic: Building Safer, Self-Documenting APIs
Type hints transform Python from a dynamic free-for-all into a structured, IDE-friendly language. Pydantic adds runtime validation. Together they make your APIs safer and self-documenting.
Understanding LLM Hallucinations: Causes, Detection, and Prevention
LLM hallucinations—confidently wrong answers—are the most critical reliability challenge in production AI. Learn why they happen, how to detect them, and architectural strategies to minimize them.
Writing Clean Code: SOLID Principles with Python Examples
SOLID principles are the foundation of maintainable object-oriented code. This guide explains each principle with practical Python examples and shows how they prevent the most common design problems.
Prompt Engineering: Advanced Techniques for Production LLM Applications
Prompt engineering is the art of communicating with LLMs effectively. Learn chain-of-thought prompting, few-shot examples, structured output, and prompt injection prevention for production systems.
Designing RESTful APIs: Best Practices for Consistency and Usability
A poorly designed API is a liability—developers avoid it, bugs multiply, and breaking changes cause outages. This guide covers REST naming conventions, versioning, error formats, and documentation with OpenAPI.