LLM Resources

Related resources for LLM

RAG vs LLM Explained: Why Modern AI Apps Need More Than ChatGPT
Gautam Singh
2d
Few Shot Prompting Explained: How to Get High Quality and Consistent AI Output
Mahesh Chand
4d
✨ Prompt Engineering Never Dies ✨
John Godel
5d
Context Window in Large Language Models (LLMs)
Jayant Kumar
5d
From LLMs to PT-SLMs: How GSCP-15 Turns Generic Models into Governed, Enterprise-Grade Delivery
John Godel
6d
Agent Memory and Long-Running Workflows: Designing AI Agents That Don’t Forget, Drift, or Hallucinate
John Godel
1w
How Do Developers Reduce Hallucinations When Using LLMs in Production Apps?
Aarav Patel
1w
Building Production AI Agents with LLMs Using GSCP-15: A Technical Reference Architecture
John Godel
1w
Enterprise-Grade Private LLM Deployment Architecture: Secure, Autoscaling, Multi-Region, and Internet-Isolated
Nagaraj M
1w
Basic RAG Demo With LLM and Vector Database
Ng Cheehou
1w
Understanding LLM Generation (Decoder) Parameters (Sample/Inference Parameter): Control, Creativity, and Output
Jayant Kumar
2w
The Enterprise AI Stack, All Together: LLMs, PT-SLMs, GSCP-15, Prompt Engineering, and Context Engineering
John Godel
2w
Context Engineering Powered by GSCP-15: The Discipline That Makes AI Reliable in Production
John Godel
2w
The New Wave: LLMs, PT-SLMs, and GSCP-15 as the Enterprise Stack for Trustworthy AI
John Godel
2w
The LLM Era Gets Serious: What Changes Next and Why It Matters
John Godel
2w
Large Language Models in 2026: GPT-5 vs Claude vs Llama and the Future of AI Models
Praveen Kumar
2w
Why There Is No "Tokenization-Only Model" in Modern NLP
Jayant Kumar
2w
When a Prompt Is Not Enough: Building Smarter AI with Microsoft Agent Framework
Varun Setia
2w
Dev Guide: What and How to Build AI Agents with LangChain, n8n, and AutoGen for Business Automation
Rohit Gupta
3w
Engineering Autonomous AI: The Technical Stack Behind Systems That Act
John Godel
3w
Token-Efficient RAG: Using Query Intent to Reduce Cost Without Losing Accuracy
Varun Setia
3w
Agentic AI vs. Generative AI in 2025: What They Are and How to Choose
Rohit Gupta
3w
Agentic RAG Explained in Simple Words
Prathap Reddy
Dec 23
AI Hallucinations Explained: Inside the Museum of AI Hallucinations | AI Agents Conference 2025
Baibhav Kumar
Dec 19
From Custom ML Pipelines to Foundry: Modernizing Enterprise AI
Neel Shah
Dec 19
The AI Gold Rush Is Here, and Most People Are Playing the Wrong Game
John Godel
Dec 18
Winning with Generative AI and Prompt Engineering
John Godel
Dec 17
C# Corner Daily Tech Updates | AWS Agentic AI, NVIDIA LLM Fine-Tuning, Slurm Acquisition – Dec 15, 2025
Baibhav Kumar
Dec 16
Why AI Can Threaten Capitalism More Than the Working Class
John Godel
Dec 15
From Single Agents to Governed Ecosystems: GSCP-15 Orchestration with Layered Memory
John Godel
Dec 15
What are AI hallucinations
Mahesh Chand
Dec 15
Different Types of AI Hallucinations
Mahesh Chand
Dec 15
How LLMs Generate Responses
Mahesh Chand
Dec 15
What is Agent Engineering: How Modern AI Agents Are Built
Rohit Gupta
Dec 12
AI Agents: Architected Memory Systems For GSCP-15 Agents
John Godel
Dec 11
LLMs And GSCP-15: Turning Raw Models Into Governed Reasoning Systems
John Godel
Dec 11
What LangSmith Fetch Is and How It Automates Dataset Retrieval for Evaluations
Rohit Gupta
Dec 11
What LangChain Polly Is and How It Automates AI Agent Engineering
Rohit Gupta
Dec 11
CathAI Assistant: An Integrated .NET and NVIDIA MONAI Platform for Coronary Angiography Analysis
John Godel
Dec 10
🤖 Ethical AI: Challenges in Bias, Transparency & Regulations
Vijay Kumari
Dec 10
🔮 Micro-LLMs vs Large LLMs: The Future of Lightweight AI Models
Vijay Kumari
Dec 10
From Prompts To Pipelines: How Real AI Products Are Actually Built
John Godel
Dec 10
What Is Tokenization? The Most Comprehensive Guide for NLP and AI
Mahesh Chand
Dec 10
LangSmith Cost Tracking: Full Guide to Logging, Monitoring, and Optimizing LLM Costs
Rohit Gupta
Dec 08
What are the different types of AI agents
Mahesh Chand
Dec 08
The Complete Breakdown of How AI Agents Work
Mahesh Chand
Dec 07
Large Language Models: What They Really Change In Work And Software
John Godel
Dec 05
Major Challenges LLMs Face When Working With Healthcare Data
Mahesh Chand
Dec 03
Docker Model Runner Adds vLLM for Fast AI Inference
Sarthak Varshney
Dec 01
NanoChat Deep Dive: How Lightweight AI Chats Work Using Transformer Models
Rohit Gupta
Nov 30
How Large Language Models (LLMs) Work
Baibhav Kumar
Nov 30
How to Build AI Prompts in C# 14
Ziggy Rafiq
Nov 27
Understanding Agent Frameworks, Runtimes, and Harnesses in Modern AI Systems
Rohit Gupta
Nov 27
Beyond Chatbots: Auto-Regressive LLMs as Real-Time Enterprise Forecasting Engines
Tuhin Paul
Nov 27
LLMs: Generative AI: When Your Learning Architecture Is Not Smart Enough, Your Model Gets Worse
John Godel
Nov 27
What is Retrieval-Augmented Generation (RAG)?
Baibhav Kumar
Nov 25
Telecom Tower Assistant: Multi-Modal LLM's for Field Service Repairs
Tuhin Paul
Nov 25
Transforming AI with .NET and C#
Abhishek Yadav
Nov 24
20 Essential Terms to Understand When Building RAG (Retrieval-Augmented Generation) Applications
Nitin Pandit
Nov 21
Artificial Intelligence: Understanding PII, PHI, PCI and Why They Matter in the Age of AI, GenAI, LLMs and PT-SLMs
John Godel
Nov 18
GenAI: Understanding PII, PHI, PCI and Why They Matter in the Age of AI, GenAI, LLMs and PT-SLMs
John Godel
Nov 18
Understanding PII, PHI, PCI and Why They Matter in the Age of AI, GenAI, LLMs and PT-SLMs
John Godel
Nov 18
TOON vs JSON: Can Token-Oriented Object Notation Replace JSON?
Nitin Pandit
Nov 18
AI-Powered File Summarizer: Deep-Dive Architecture, Algorithms, Workflows, and Enterprise Integration
Rohit Gupta
Nov 18
Build a Bash terminal agent with NVIDIA Nemotron in one hour
Rohit Gupta
Nov 17
TOON for LLMs: A Cleaner and More Efficient JSON Alternative
Sarthak Varshney
Nov 17
Microsoft Agent Framework - Declarative Tools Explained
Shweta Lodha
Nov 17
Qwen3-Next: The AI Model That's Actually Affordable to Run
Sarthak Varshney
Nov 17
How LLM Memory Works: Architecture, Techniques, and Developer Patterns
Rohit Gupta
Nov 14
LLMs: We Should Stop Calling Them “Large Language Models”
John Godel
Nov 11
LLMs: Gödel’s Autonomous Self-Supervised Learning for LLMs - An Introduction
John Godel
Nov 11
Agentic World Wide Web Is Knocking at the Door
John Godel
Nov 11
Agentic AI: Beyond the Hype Curve - A Realistic 2030 Outlook for AI-Led Software Development—and the Future of the Web
John Godel
Nov 11
Build and Run Local AI Models Using Ollama and LangChain
Rohit Gupta
Nov 11
Building AI-Enhanced Applications: Integrating LangChain and Semantic Kernel with ASP.NET Core
Rajesh Gami
Nov 11
Tokencrush, LangGraph, and the Real Economics of LLM Efficiency
Rohit Gupta
Nov 09
Top 50 Prompt Engineering Techniques for Python Developers
Rohit Gupta
Nov 07
FastAPI + LLMs: Building a Scalable AI Backend
Rohit Gupta
Nov 07
Using LangChain Tools in Python for AI Workflow Automation
Rohit Gupta
Nov 07
Connect Python to GPT-5 API: Step-by-Step Developer Guide
Rohit Gupta
Nov 07
AI for Python Developers: OpenAI API Setup and Best Practices in 15 Minutes
Rohit Gupta
Nov 06
Is JSON Dead? Meet TOON – The Token-Efficient Alternative for LLM Prompts
Deepak Tewatia
Nov 06
LLMs + SQL: From Natural Language to Safe, Auditable Queries
John Godel
Nov 05
LLMs That Fix Things: Field Service Assistants from Triage to Wrench Time
John Godel
Nov 05
AI LLM Reaches 1M TPS: The Next Leap in Inference Speed
Mahesh Chand
Nov 04
MaxKB Open-Source Platform | Enterprise AI Agents & RAG Pipeline
Rohit Gupta
Nov 04
Automating Bank Statement Analysis with LLMs & RAG Techniques
Rohit Gupta
Nov 04
OpenAgent: The Ultimate Framework for Modular AI Agent Orchestration
Rohit Gupta
Nov 03
Prompt Engineering: Prompt Observability - Traces, Metrics, and Incident Response
John Godel
Oct 30
MiniMax M2 on Ollama Cloud – Benchmark Leader for Coding and Agentic Workflows
Rohit Gupta
Oct 30
Generative AI: Data Quality Is Destiny - Unifying Data Governance and AI Governance for Trustworthy AI
John Godel
Oct 28
Build a Custom LangChain Chat Model from Scratch
Rohit Gupta
Oct 27
Building Responsible Intelligence: How to Use Large Language Models Ethically and Carefully
Rinki
Oct 26
RAG vs. Fine-Tuning in 2025: A Practical Playbook for Teams
John Godel
Oct 26
OpenMemory – Self-Hosted Long-Term AI Memory Engine for LLMs
Rohit Gupta
Oct 26
LLMs: GSCP-12 (Gödel’s Scaffolded Cognitive Prompting) for Rigorous Deductive and Inductive Reasoning in LLMs
John Godel
Oct 25
Operational Prompt Engineering: Turning Prompts into Products
John Godel
Oct 23
AI Agents in Practice: Data Privacy & DSAR Fulfillment Agent (Prompts + Code)
John Godel
Oct 22
Agents 2.0 and Deep Agents: The Future of Autonomous AI Systems
Rohit Gupta
Oct 20
LLMs: GSCP-12, Memory, and Machine Consciousness — An AI Perspective
John Godel
Oct 19

Topics

RAG vs LLM Explained: Why Modern AI Apps Need More Than ChatGPT

Few Shot Prompting Explained: How to Get High Quality and Consistent AI Output

✨ Prompt Engineering Never Dies ✨

Context Window in Large Language Models (LLMs)

From LLMs to PT-SLMs: How GSCP-15 Turns Generic Models into Governed, Enterprise-Grade Delivery

Agent Memory and Long-Running Workflows: Designing AI Agents That Don’t Forget, Drift, or Hallucinate

How Do Developers Reduce Hallucinations When Using LLMs in Production Apps?

Building Production AI Agents with LLMs Using GSCP-15: A Technical Reference Architecture

Enterprise-Grade Private LLM Deployment Architecture: Secure, Autoscaling, Multi-Region, and Internet-Isolated

Basic RAG Demo With LLM and Vector Database

Understanding LLM Generation (Decoder) Parameters (Sample/Inference Parameter): Control, Creativity, and Output

The Enterprise AI Stack, All Together: LLMs, PT-SLMs, GSCP-15, Prompt Engineering, and Context Engineering

Context Engineering Powered by GSCP-15: The Discipline That Makes AI Reliable in Production

The New Wave: LLMs, PT-SLMs, and GSCP-15 as the Enterprise Stack for Trustworthy AI

The LLM Era Gets Serious: What Changes Next and Why It Matters

Large Language Models in 2026: GPT-5 vs Claude vs Llama and the Future of AI Models

Why There Is No "Tokenization-Only Model" in Modern NLP

When a Prompt Is Not Enough: Building Smarter AI with Microsoft Agent Framework

Dev Guide: What and How to Build AI Agents with LangChain, n8n, and AutoGen for Business Automation

Engineering Autonomous AI: The Technical Stack Behind Systems That Act

Token-Efficient RAG: Using Query Intent to Reduce Cost Without Losing Accuracy

Agentic AI vs. Generative AI in 2025: What They Are and How to Choose

Agentic RAG Explained in Simple Words

AI Hallucinations Explained: Inside the Museum of AI Hallucinations | AI Agents Conference 2025

From Custom ML Pipelines to Foundry: Modernizing Enterprise AI

The AI Gold Rush Is Here, and Most People Are Playing the Wrong Game

Winning with Generative AI and Prompt Engineering

C# Corner Daily Tech Updates | AWS Agentic AI, NVIDIA LLM Fine-Tuning, Slurm Acquisition – Dec 15, 2025

Why AI Can Threaten Capitalism More Than the Working Class

From Single Agents to Governed Ecosystems: GSCP-15 Orchestration with Layered Memory

What are AI hallucinations

Different Types of AI Hallucinations

How LLMs Generate Responses

What is Agent Engineering: How Modern AI Agents Are Built

AI Agents: Architected Memory Systems For GSCP-15 Agents

LLMs And GSCP-15: Turning Raw Models Into Governed Reasoning Systems

What LangSmith Fetch Is and How It Automates Dataset Retrieval for Evaluations

What LangChain Polly Is and How It Automates AI Agent Engineering

CathAI Assistant: An Integrated .NET and NVIDIA MONAI Platform for Coronary Angiography Analysis

🤖 Ethical AI: Challenges in Bias, Transparency & Regulations

🔮 Micro-LLMs vs Large LLMs: The Future of Lightweight AI Models

From Prompts To Pipelines: How Real AI Products Are Actually Built

What Is Tokenization? The Most Comprehensive Guide for NLP and AI

LangSmith Cost Tracking: Full Guide to Logging, Monitoring, and Optimizing LLM Costs

What are the different types of AI agents

The Complete Breakdown of How AI Agents Work

Large Language Models: What They Really Change In Work And Software

Major Challenges LLMs Face When Working With Healthcare Data

Docker Model Runner Adds vLLM for Fast AI Inference

NanoChat Deep Dive: How Lightweight AI Chats Work Using Transformer Models

How Large Language Models (LLMs) Work

How to Build AI Prompts in C# 14

Understanding Agent Frameworks, Runtimes, and Harnesses in Modern AI Systems

Beyond Chatbots: Auto-Regressive LLMs as Real-Time Enterprise Forecasting Engines

LLMs: Generative AI: When Your Learning Architecture Is Not Smart Enough, Your Model Gets Worse

What is Retrieval-Augmented Generation (RAG)?

Telecom Tower Assistant: Multi-Modal LLM's for Field Service Repairs

Transforming AI with .NET and C#

20 Essential Terms to Understand When Building RAG (Retrieval-Augmented Generation) Applications

Artificial Intelligence: Understanding PII, PHI, PCI and Why They Matter in the Age of AI, GenAI, LLMs and PT-SLMs

GenAI: Understanding PII, PHI, PCI and Why They Matter in the Age of AI, GenAI, LLMs and PT-SLMs

Understanding PII, PHI, PCI and Why They Matter in the Age of AI, GenAI, LLMs and PT-SLMs

TOON vs JSON: Can Token-Oriented Object Notation Replace JSON?

AI-Powered File Summarizer: Deep-Dive Architecture, Algorithms, Workflows, and Enterprise Integration

Build a Bash terminal agent with NVIDIA Nemotron in one hour

TOON for LLMs: A Cleaner and More Efficient JSON Alternative

Microsoft Agent Framework - Declarative Tools Explained

Qwen3-Next: The AI Model That's Actually Affordable to Run

How LLM Memory Works: Architecture, Techniques, and Developer Patterns

LLMs: We Should Stop Calling Them “Large Language Models”

LLMs: Gödel’s Autonomous Self-Supervised Learning for LLMs - An Introduction

Agentic World Wide Web Is Knocking at the Door

Agentic AI: Beyond the Hype Curve - A Realistic 2030 Outlook for AI-Led Software Development—and the Future of the Web

Build and Run Local AI Models Using Ollama and LangChain

Building AI-Enhanced Applications: Integrating LangChain and Semantic Kernel with ASP.NET Core

Tokencrush, LangGraph, and the Real Economics of LLM Efficiency

Top 50 Prompt Engineering Techniques for Python Developers

FastAPI + LLMs: Building a Scalable AI Backend

Using LangChain Tools in Python for AI Workflow Automation