Hi, I’m Azeemuddin Mohammed
CTO | Head of Engineering | SaaS Product Engineering & Applied AI
With 20+ years in technology and engineering leadership, I build and scale SaaS products, AI systems, and high-performing engineering teams.
I don’t just advise. I build and lead. From MVPs and AI-powered products to production-grade platforms, my focus is turning product ideas into reliable systems and shipping real products.
What I Share at CodedByAzm
- AI products & automation
- Engineering leadership & product execution
- SaaS architecture & modern workflows
- Lessons from building real-world products
You’ll also find Launch Radar, product breakdowns, startup analysis, and practical insights from the rapidly evolving AI era.
If you’re interested in SaaS, AI, engineering leadership, or modern product development, you’re in the right place.
Read the Blog · Explore Launch Radar · Follow the Journey
What is CodedByAzm?
CodedByAzm is a tech blog for startups and developers, focused on AI products, SaaS systems, engineering leadership, and modern software development.
With 20+ years in technology and engineering leadership, I share practical insights from building, scaling, and shipping software in fast-moving environments.
Alongside in-depth articles and product breakdowns, CodedByAzm documents real-world experiences in SaaS product development, AI systems, engineering leadership, and technical execution.
What You’ll Find Here
CodedByAzm is built around practical execution, not generic startup advice or recycled AI hype.
Here’s what you’ll find:
👉 Practical insights on SaaS, AI systems, and modern engineering
👉 Engineering leadership and product execution lessons
👉 Product breakdowns, architecture thinking, and market insights
👉 Real-world perspectives on building software in the AI era
Practical insights on AI, SaaS, engineering leadership, product development, and modern software engineering, based on real-world experience.
Each article focuses on lessons, technical decisions, and ideas that can help you build better products and engineering systems.
- RAG Grounding: How to Keep AI Answers Grounded | VoyageIQ
How VoyageIQ Uses RAG Grounding to Keep AI Answers Grounded When you ask a large language model a question about a niche topic or your own private documents, it doesn’t automatically have access to that information. If the required context isn’t available, the model may generate a plausible-sounding answer based on patterns learned during training… Read more: RAG Grounding: How to Keep AI Answers Grounded | VoyageIQ - Building a RAG Application with Next.js, FastAPI & pgvector: A Practical Guide
Building a RAG Application with Next.js, FastAPI and pgvector Many AI applications start with a simple chatbot: build a UI, connect an LLM API, and let users ask questions. That works well for experimentation. But when an application needs to answer questions based on a specific set of documents, simply calling an LLM isn’t enough.… Read more: Building a RAG Application with Next.js, FastAPI & pgvector: A Practical Guide - Distribution. Distribution. Distribution.
Distribution. Distribution. Distribution. There was a decade where my entire worth as a CTO was tied to how clean my architecture was, whether the database could handle a spike, and how fast we could ship a feature. Writing the product was the job. It took years of scars to get good at it. That world… Read more: Distribution. Distribution. Distribution.