Aravind Patel

AI Agents & Automation

When should you choose single-agent orchestration over multi-agent architecture?

Choose single-agent orchestration for simple, sequential tasks or multi-agent for complex, collaborative problems requiring specialized roles and dynamic reasoning.

RAG & Vector Databases

How do you measure and reduce hallucination rates in enterprise RAG pipelines?

Measure RAG hallucination using LLM-as-a-judge frameworks like Ragas for faithfulness and relevancy, and reduce it by improving retrieval with re-ranking, optimizing chunking, and

Prompt Engineering & LLMs

How does Chain-of-Thought (CoT) prompting impact token latency and accuracy in complex logic tasks?

Chain-of-Thought (CoT) prompting increases token latency due to more tokens but significantly improves accuracy for complex logic tasks by enabling better reasoning.

System Prompts & Guardrails

What is the best way to enforce brand tone and prevent PII leakage in customer support LLM bots?

Layered guardrails—system prompt, tone classifier, pre‑response PII filter, then LLM—enforce brand tone and stop data leaks.

Computer Vision & Multimodal AI

How to fine-tune Vision-Language Models (VLMs) for domain-specific document layout extraction?

Freeze the vision encoder, add a lightweight adapter to the language decoder, and train on OCR‑annotated layout tokens with a small learning rate.

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