Engineering Notes
Thoughts and Ideas on AI by Muthukrishnan
Tag: Ai
The Race: Why Flow Beats Local Efficiency
A practical reading of Eliyahu Goldratt's The Race, and why AI transformation should focus on bottlenecks, throughput, and flow instead of local productivity.The Doorman Fallacy and Why AI Keeps Failing at Replacing People
In 2023, AI was going to replace programmers. A year later, customer support was next. By 2025, some executives had mov...Optimize Units of Work, Not Growth Targets
Growth becomes more actionable when leaders stop treating it as a target and start removing friction from the individual units of work that create it.AI Will Not Kill Junior Engineers but It Will Change Them
There is a growing debate in software teams: If AI can generate most entry-level coding work, do we still need junior ...Cloudflare Email for Agents: Why Email May Become Agent Infrastructure
Cloudflare's Email for Agents is less about email and more about giving AI agents identity, memory, and a universal communication channel.Building a Multi-Agent Swarm with OpenAI Swarm Framework
Learn the basics of OpenAI's experimental Swarm framework for lightweight multi-agent orchestration with handoffs and routines.Adding Context to Chunks for Better Retrieval with Contextual RAG
Improve your RAG pipeline by prepending contextual information to each chunk before embedding, reducing retrieval failures by up to 67%.A Practical Guide to Evaluating Your AI Agents with DeepEval
Learn how to systematically test and evaluate AI agents using DeepEval's metrics for relevancy, faithfulness, and task completion.Building an Agentic RAG Pipeline with LangGraph
Move beyond naive RAG with an agentic approach that uses LLMs to decide what to retrieve, when to retry, and how to synthesize answers.CrewAI vs LangGraph Building the Same Multi-Agent System in Both
A side-by-side comparison of CrewAI and LangGraph by implementing the same research assistant workflow in both frameworks.Building an MCP Server with Python to Connect Claude to Your Database
A practical guide to building a Model Context Protocol (MCP) server that lets Claude query your SQLite database directly.The Architecture is the Prompt - Guiding AI with Hexagonal Design
As developers, we've all felt the frustration. You have a well-structured repository with clear patterns, but the new A...A Multi-Agent AI Ecosystem for Self-Improving Software
In the relentless pursuit of robust and secure software, developers have long relied on a combination of automated test...Building a Multi-Agent Debate System with LangGraph
## Introduction Multi-agent systems are a fascinating area of AI development, where multiple autonomous agents collabo...Systems That Search for New Algorithms Automatically
An introduction to AlphaEvolve, DeepMind's new AI agent that uses evolutionary search and LLM-driven code synthesis to autonomously discover and optimize algorithms, outperforming human-designed solutions in several domains.TDD with Coding Agents to Build a Rate Limiting Service
## Problem Overview We'll build a sophisticated rate limiting service that supports: - Multiple rate limiting algorith...The Complete Claude Code Best Practices Guide
*A Comprehensive Manual Compiled from Developer Experiences and Community Knowledge* ## Table of Contents 1. [Introduc...Why MMLU Matters and What Massive Multitask Language Understanding Really Tests
A personal dive into MMLU - the benchmark that's reshaping how we measure AI intelligence across dozens of academic subjects.Understanding Mixture of Experts from First Principles
One of the most exciting architectural innovations in recent years is the **Mixture of Experts (MoE)**. It's a key reas...My Thoughts on Andrew Ngs Building Faster and Smarter with AI
{{< youtube RNJCfif1dPY >}} I watched Andrew Ng's latest talk on AI startup strategy, and while I disagree with some o...AI Agent Communication Protocols MCP, ACP, A2A, and ANP
An overview of the most important communication protocols for multi-agent systems, and how they enable interoperability and scalability.Small Language Models are the Future of Agentic AI
I recently came across a paper titled *"Small Language Models are the Future of Agentic AI,"* and it got me thinking. T...Meet AlphaEvolve the AI That Discovers New Algorithms
An introduction to AlphaEvolve, DeepMind's new AI agent that uses evolutionary search and LLM-driven code synthesis to autonomously discover and optimize algorithms, outperforming human-designed solutions in several domains.Learning CrewAI in a Step-by-Step Guide with 10 Concepts
A beginner-friendly guide to mastering CrewAI, from basic agents and tasks to advanced multi-agent workflows with tools and custom LLMs.An Introduction to Context Engineering for AI Code Generation
How to prevent AI coding assistants from generating outdated or deprecated code by using real-time context engineering.A Developers Guide to Effective AI Coding Agents
Moving beyond basic code completion to a structured, developer-led workflow that harnesses the full potential of AI coding agents.Deep Research Applications of Modern LLMs Generated through Deep Research
Exploring how modern AI systems are evolving beyond conversational chatbots to become autonomous research agents capable of conducting comprehensive, PhD-level investigations.