Syed Alam Shah Bukhari
AI Engineer building RAG systems LLM Production Agents
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Building AI agents that solve real business problems.
I've been working on AI automation systems that combine LLMs, backend engineering, API integrations, and human-in-the-loop workflows.
One thing I've learned is that successful automation isn't just about getting an AI agent to...
Completed "Building and Evaluating Advanced RAG" by DeepLearning.AI (TruEra, LlamaIndex).
The most useful part wasn't building another RAG pipeline, it was learning how to actually evaluate one. The RAG Triad (answer relevance, context relevance, groundedness) gives you a way to...
Building AI agents is easy. Building one you can trust with a real business workflow is harder.
I built a Freelance Admin Agent to explore that problem using Strands Agents SDK and Claude Sonnet 4.5 on Amazon Bedrock.
The working MVP takes manually provided client emails and turns...
Why I stopped using pure semantic search for RAG
When I built a hybrid retrieval system, I learned semantic search alone misses exact matches, things like IDs, codes, or specific terms that don't need "understanding," just exact lookup.
Combining vector search with keyword...
A few months ago I shipped my first production RAG pipeline. Simple idea: upload a document, ask questions, get answers with citations.
The part nobody warns you about is everything after "it works on my laptop." ChromaDB breaking on cloud deployment. Secrets formatting silently...