Backend & AI Engineering Notes
Practical notes from systems I've built and maintained: backend architecture, AI systems, debugging, and the AI-native development workflows I use to ship them.
I keep this intentionally selective. If a problem did not teach me something reusable, it does not need a blog post.
How a Countdown Timer Became a State-Synchronization Problem
What Office Escape taught me about timestamps, browser throttling, offline state, and multiple UI surfaces
By Anuka MitharaHow a React Effect Turned Cloud Sync Into an API Request Loop
A production debugging lesson from Office Escape
By Anuka MitharaHow I Use AI Coding Agents Without Outsourcing the Engineering
How vibe coding fits into my workflow without giving up architecture, judgment, testing, or ownership
By Anuka MitharaHow Small Backend Changes Quietly Break Other Services
What maintaining connected APIs taught me about contracts, defaults, tenant context, and compatibility
By Anuka MitharaThe Agent Navigated to the Right Page and Highlighted the Wrong Thing
A small Next.js race condition that changed how I design UI-driving agents
By Anuka MitharaThe Hard Part of an AI Shopping Agent Wasn't the LLM
What Kapuru taught me about memory, tool calls, streaming, and checkout safety
By Anuka MitharaWhat Actually Gets Hard When You Maintain Many Backend Services
The difficult part is not writing another FastAPI endpoint — it is keeping the whole system understandable
By Anuka MitharaWhen Security Scanning Breaks CI: Fix the Risk, Not Just the Pipeline
What a Trivy failure taught me about vulnerability triage, base images, dependency ownership, and useful security gates
By Anuka MitharaWhy I Put a Middleware Layer Between Applications and LLM Providers
What changed when multiple AI features, models, providers, and usage constraints started sharing the same backend
By Anuka Mithara