Building AI Products That Actually Work — Lessons from GyanBeej
A practical 2026 guide to building AI products that are reliable, cost-efficient, and safe. Learn smart AI workflows, risk controls, and how to avoid over-relying on LLMs.
Engineering notes, architecture decisions, and lessons from building 80+ production applications.
RSS FeedA practical 2026 guide to building AI products that are reliable, cost-efficient, and safe. Learn smart AI workflows, risk controls, and how to avoid over-relying on LLMs.
155 fleet compliance SaaS Django FMCSA software development
My 2026 Django project structure after 6+ years in production: scalable architecture, folder strategy, service-layer patterns, and when to choose FastAPI, Node.js, or Go instead.
A comprehensive guide for CTOs and senior developers on production-ready LLM integration with a Django backend, focusing on architecture, security, and scalability for real-world applications.
Designing a robust AI voice agent SaaS architecture requires balancing sub-second latency, high concurrency, and cost efficiency. Lessons from real-world systems.
Longer-form articles published on Medium for a wider audience. Click to read on Medium.
A practical perspective on why AI-generated code still needs engineering discipline, architectural thinking, and security review before production.
A step-by-step SAML SSO integration guide for Django, including a thread-safe multi-tenant configuration strategy.
How to choose between transaction mode and session mode in Supabase, avoid connection bottlenecks, and keep FastAPI backends stable.
A practical walkthrough to integrate Ruff into Django projects, tune linting rules, and reduce noisy checks.
A clear breakdown of the classic Codewars kata, with Python and JavaScript solutions and the key logic behind each step.