Autogen: A Basic Understanding
Author(s): Rashmi Originally published on Towards AI. Subtitle AutoGen is Microsoft’s open-source framework for building multi-agent AI applications where multiple AI agents collaborate to solve complex tasks. It enables agents to have conversations with each other, share context, and work together autonomously …
Persistence in LangGraph — Deep, Practical Guide
Author(s): Rashmi Originally published on Towards AI. Persistence in LangGraph — Deep, Practical Guide Persistence in LangGraph means storing and restoring graph state so an agent/workflow can: Image description not provided in the HTMLThe article explores the importance of persistence in LangGraph, …
Why MCP Matters: A Deep Dive into Model Context Protocol
Author(s): Rashmi Originally published on Towards AI. Why MCP Matters: A Deep Dive into Model Context Protocol MCP = a standard protocol that lets AI apps/agents connect to external tools + data sources in a consistent way. Instead of building a custom …
Kafka vs Kinesis (2026): A Practical Guide to Streaming, Use Cases, Architecture, and Code
Author(s): Rashmi Originally published on Towards AI. Kafka vs Kinesis (2026): A Practical Guide to Streaming, Use Cases, Architecture, and Code Event streaming is the nervous system of modern data platforms: clickstreams, payments, logs, IoT telemetry, fraud signals, and ML features all …
MLflow vs Kubeflow vs Airflow: Choosing the Right MLOps Tool for Real-World Production Systems
Author(s): Rashmi Originally published on Towards AI. MLflow vs Kubeflow vs Airflow: Choosing the Right MLOps Tool for Real-World Production Systems Machine Learning models rarely fail because of algorithms. They fail because pipelines break, experiments are lost, deployments drift, and nobody knows …
Agent Lightning: From Agent Experiments to Self-Improving AI Systems
Author(s): Rashmi Originally published on Towards AI. Agent Lightning: From Agent Experiments to Self-Improving AI Systems Agent Lightning is a training and optimization runtime for agents. Agent Lightning is an innovative, research-driven, open-source initiative by Microsoft that focuses on transforming agent executions …
CNN vs RNN: Two Brains of Deep Learning
Author(s): Rashmi Originally published on Towards AI. CNN vs RNN: Two Brains of Deep Learning Convolutional Neural Network (CNN) is a specialized deep learning architecture designed to process grid-like topology data, primarily images, by automatically learning spatial hierarchies of features through backpropagation. …
Inside Latent Space: The Hidden Intelligence of AI Systems
Author(s): Rashmi Originally published on Towards AI. Inside Latent Space: The Hidden Intelligence of AI Systems Latent space is the compressed “meaning space” where AI models transform messy real-world inputs (text, images, audio, sensor signals) into dense vectors (embeddings) that capture patterns, …
Adversarial NLP in 2026: When Text Attacks Text
Author(s): Rashmi Originally published on Towards AI. Adversarial NLP in 2026: When Text Attacks Text Adversarial NLP is the study and practice of crafting text inputs that cause NLP systems to behave incorrectly — misclassify, leak secrets, follow malicious instructions, or take …
LSTM vs GRU: Architecture, Performance, and Use Cases
Author(s): Rashmi Originally published on Towards AI. LSTM vs GRU: Architecture, Performance, and Use Cases Imagine you’re reading a long book and trying to remember key plot points: The Reading AnalogyThe article delves into the comparison between Long Short-Term Memory (LSTM) and …
Inference Is the New Training
Author(s): Rashmi Originally published on Towards AI. Inference Is the New Training Inference Is the New Training refers to a paradigm shift where AI systems learn and adapt during inference time rather than just during pre-training. Instead of static models that only …
Critical Pointers for AI Developers in the Age of Agent IDEs
Author(s): Rashmi Originally published on Towards AI. Architecture Rot from Over-Reliance on AI Generation The Problem: AI generates working code but often creates architectural debt — poor separation of concerns, tight coupling, and no thought to scalability. Critical Pointers for AI Developers …
AI Engineers in 2026 Need Less Math and More Architecture
Author(s): Rashmi Originally published on Towards AI. AI Engineers in 2026 Need Less Math and More Architecture The AI engineering landscape is fundamentally transforming. Modern AI engineers increasingly focus on system design, orchestration, and integration rather than implementing algorithms from scratch. The …
The Complete Guide to RAG Systems
Author(s): Rashmi Originally published on Towards AI. The Complete Guide to RAG Systems Retrieval-Augmented Generation (RAG) has revolutionized how we build intelligent systems by combining the power of large language models with external knowledge retrieval. As organizations struggle with hallucinations, outdated information, …
Sentiment Cluster Analysis for Movie Reviews Project
Author(s): Rashmi Originally published on Towards AI. Sentiment Cluster Analysis for Movie Reviews Project Sentiment cluster analysis combines sentiment analysis with unsupervised clustering to discover natural groupings in movie review data beyond simple positive/negative classifications. This approach reveals nuanced patterns like “enthusiastically …
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