Evaluation: Multi-turn Conversations, Tool Use, Tracing, and Red Teaming
LLMOps Part 11: Understanding evaluation of conversational LLM systems, tool evaluations, tracing with Langfuse, and automated red teaming.
· Avi Chawla
Evaluation: Model Benchmarks and LLM Application Assessment
LLMOps Part 10: Understanding model benchmarks, LLM application evaluation, and tooling.
· Avi Chawla
Evaluation: Fundamentals
LLMOps Part 9: A foundational guide to the evaluation of LLM applications, covering challenges and a practical taxonomy of evaluation methods.
· Avi Chawla
Context Engineering: Memory and Temporal Context
LLMOps Part 8: A concise overview of memory, dynamic and temporal context in LLM systems, covering short and long-term memory, dynamic context injection, and some of the common context failure modes in agentic applications.
· Avi Chawla
Context Engineering: An Introduction to the Information Environment for LLMs
LLMOps Part 7: A conceptual overview of context engineering, covering context types, context construction principles, and retrieval-centric techniques for building high-signal inputs.
· Avi Chawla
Context Engineering: Prompt Management, Defense, and Control
LLMOps Part 6: Exploring prompt versioning, defensive prompting, and techniques such as verbalized sampling, role prompting and more.
· Avi Chawla
Context Engineering: Foundations, Categories, and Techniques of Prompt Engineering
LLMOps Part 5: An introduction to prompt engineering (a subset of context engineering), covering prompt types, the prompt development workflow, and key techniques in the field.
· Avi Chawla
Building Blocks of LLMs: Decoding, Generation Parameters, and the LLM Application Lifecycle
LLMOps Part 4: An exploration of key decoding strategies, sampling parameters, and the general lifecycle of LLM-based applications.
· Avi Chawla
Building Blocks of LLMs: Attention, Architectural Designs and Training
LLMOps Part 3: A focused look at the core ideas behind attention mechanism, transformer and mixture-of-experts architectures, and model pretraining and fine-tuning.
· Avi Chawla
Tools, Resources and Prompts
· Avi Chawla
MCP Architecture Overview
· Avi Chawla
Why was MCP created?
· Avi Chawla
What is MCP?
· Avi Chawla
Building Blocks of LLMs: Tokenization and Embeddings
LLMOps Part 2: A detailed walkthrough of tokenization, embeddings, and positional representations, building the foundational translation layer that enables LLMs to process and reason over text.
· Avi Chawla
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part C)
AI Agents Crash Course—Part 17 (with implementation).
· Avi Chawla
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part B)
AI Agents Crash Course—Part 16 (with implementation).
· Avi Chawla
Foundations of AI Engineering and LLMs
LLMOps Part 1: An overview of AI engineering and LLMOps, and the core dimensions that define modern AI systems.
· Avi Chawla
A Practical Guide to Integrate Evaluation and Observability into LLM Apps
A comprehensive guide to Opik, an open-source LLM evaluation and observability framework.
· Avi Chawla
CI/CD Workflows
MLOps Part 18: A hands-on guide to CI/CD in MLOps with DVC, Docker, GitHub Actions, and GitOps-based Kubernetes delivery on Amazon EKS.
· Avi Chawla
Monitoring and Observability: Practical Tooling with Evidently, Prometheus, and Grafana
MLOps Part 17: ML monitoring in practice with Evidently, Prometheus and Grafana, stitched into a FastAPI inference service with drift reports, metrics scraping, and dashboards.
· Avi Chawla
A Practical Deep Dive Into Memory Optimization for Agentic Systems (Part A)
AI Agents Crash Course—Part 15 (with implementation).
· Avi Chawla
Monitoring and Observability: Core Fundamentals
MLOps Part 16: A comprehensive overview of drift detection using statistical techniques, and how logging and observability keep ML systems healthy.
· Avi Chawla
Model Deployment: EKS Lifecycle and Model Serving
MLOps Part 15: Understanding the EKS lifecycle, getting hands-on with AWS setup, and deploying a simple ML inference service on Amazon EKS.
· Avi Chawla
Model Deployment: Introduction to AWS
MLOps Part 14: Understanding AWS cloud platform, and zooming into EKS.
· Avi Chawla
Build an MCP-powered Audio Analysis Toolkit
...explained step-by-step with code.
· Avi Chawla
Build an MCP-powered RAG over Videos
Chat with videos and get precise timestamps.
· Avi Chawla
Model Deployment: Cloud Fundamentals
MLOps Part 13: An overview of cloud concepts that matter, from virtualization and storage choices to VPC, load balancing, identity, and observability.
· Avi Chawla
Model Deployment: Kubernetes
MLOps Part 12: An introduction to Kubernetes, plus a practical walkthrough of deploying a simple FastAPI inference service using Kubernetes.
· Avi Chawla
MCP-powered Deep Researcher
Multi-agent (100% local).
· Avi Chawla
MCP-powered Synthetic Data Generator
Generate realistic data using existing data (100% local).
· Avi Chawla