Practical guides and real-world lessons from building with Python, AI, AWS, and beyond.
How we designed and delivered a production-grade async REST API using Django 6.0 and DRF — including MCP server integration for AI agents, PyTest migration, and CI/CD optimisation that cut test time from 8 minutes to under 3.
A practical guide to building cost-effective AI pipelines: OpenAI Batch API to cut costs by half, word embeddings for semantic search, Gemini for PDF OCR, and JSON schema-based data extraction for financial and carbon data.
From a Dockerised monolith to a resilient AWS architecture with Lambda, SQS, CloudWatch, and Terraform. Real decisions, real trade-offs — not a tutorial dressed up as experience.
Lessons from building a scalable CRM integration framework that connects five major platforms. Common patterns, authentication strategies, data sync pitfalls, and how to build a backend that doesn't break when CRM APIs change.