LLMs Resources

Related resources for LLMs

From Custom ML Pipelines to Foundry: Modernizing Enterprise AI
Neel Shah
5d
The AI Gold Rush Is Here, and Most People Are Playing the Wrong Game
John Godel
1w
Winning with Generative AI and Prompt Engineering
John Godel
1w
Why AI Can Threaten Capitalism More Than the Working Class
John Godel
1w
What are AI hallucinations
Mahesh Chand
1w
How LLMs Generate Responses
Mahesh Chand
1w
LLMs And GSCP-15: Turning Raw Models Into Governed Reasoning Systems
John Godel
1w
CathAI Assistant: An Integrated .NET and NVIDIA MONAI Platform for Coronary Angiography Analysis
John Godel
2w
🤖 Ethical AI: Challenges in Bias, Transparency & Regulations
Vijay Kumari
2w
🔮 Micro-LLMs vs Large LLMs: The Future of Lightweight AI Models
Vijay Kumari
2w
From Prompts To Pipelines: How Real AI Products Are Actually Built
John Godel
2w
Large Language Models: What They Really Change In Work And Software
John Godel
2w
Major Challenges LLMs Face When Working With Healthcare Data
Mahesh Chand
3w
NanoChat Deep Dive: How Lightweight AI Chats Work Using Transformer Models
Rohit Gupta
3w
How Large Language Models (LLMs) Work
Baibhav Kumar
3w
Beyond Chatbots: Auto-Regressive LLMs as Real-Time Enterprise Forecasting Engines
Tuhin Paul
3w
LLMs: Generative AI: When Your Learning Architecture Is Not Smart Enough, Your Model Gets Worse
John Godel
4w
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 for LLMs: A Cleaner and More Efficient JSON Alternative
Sarthak Varshney
Nov 17
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
FastAPI + LLMs: Building a Scalable AI Backend
Rohit Gupta
Nov 07
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
Automating Bank Statement Analysis with LLMs & RAG Techniques
Rohit Gupta
Nov 04
Generative AI: Data Quality Is Destiny - Unifying Data Governance and AI Governance for Trustworthy AI
John Godel
Oct 28
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
LLMs: GSCP-12, Memory, and Machine Consciousness — An AI Perspective
John Godel
Oct 19
Building a Legal Assistant That Understands Case Law Relationships Using Graph-Augmented LLMs Using Python
Tuhin Paul
Oct 15
How Do LLMs Use Context to Generate Better Responses
Mahesh Chand
Oct 14
Context Engineering: Why Prompt Engineering Is Engineering—but Context Engineering Is Not Really
John Godel
Oct 14
What Are the Core Components of LangChain?
Kautilya Utkarsh
Oct 13
Prompt Engineering Is the Must-Have; Context Engineering Is Its Power Assist
John Godel
Oct 13
LLMs: Build an AI Core Banking App with FastAPI and GPT-5 (In-Depth)
John Godel
Oct 12
LLMs: Build an AI Healthcare App with Streamlit and GPT-5 (In-Depth)
John Godel
Oct 12
LLMs: Private Tailored SLMs (John Gödel’s PT-SLMs) — Narrow, Cheap, Sovereign Models with Shockingly Good On-Domain Performance
John Godel
Oct 12
GraphQA: Building Graph-Aware Question Answering Systems with LLMs
Rohit Gupta
Oct 12
LLMs, Tokens, Weights, Vectors, Embeddings — A Practical Article
John Godel
Oct 12
LLMs: From Tokens to Dollars: Cost Engineering for LLM Apps
John Godel
Oct 12
LLMs Feature Flags: Canary, Rollback, and Contract SemVer
John Godel
Oct 12
Can You Do Context Engineering Without Prompt Engineering?
John Godel
Oct 12
LLMs: How to Combine NoSQL Data with LLMs Effectively
John Godel
Oct 10
How Do Agents Differ from Chains? When to Use Agents vs Chains?
Kautilya Utkarsh
Oct 07
Difference Between a Prompt and a Prompt Template
Mahesh Chand
Oct 06
The Top 10 Large Language Models (LLMs) of 2025: The Age of Cognitive Giants
John Godel
Oct 06
Large Language Models (LLMs): The Top 10 Models of 2025 - The Age of Cognitive Giants
John Godel
Oct 05
Everything About Large Language Models—and How They Differ From GPT
John Godel
Oct 03
How to Combine Tabular Data with LLMs Effectively
Riya Patel
Oct 03
Granite 4.0 vs LLaMA 3 vs Mistral: Enterprise AI Models Compared
Rohit Gupta
Oct 03
Large Language Models (LLMs) Under the Hood: A Technical Deep Dive
John Godel
Oct 01
Large Language Models (LLMs) With Guardrails: How GSCP Turns Raw Capability Into Reliable Systems
John Godel
Oct 01
Large Language Models (LLMs), Explained: Foundations, Capabilities, Limits, and What Comes Next
John Godel
Oct 01
How to Evaluate LLMs?
Riya Patel
Sep 30
Best Practices for Prompt Engineering in Data Science
Riya Patel
Sep 30
How can AI models be used for summarization?
Vijay Kumari
Sep 26
Artificial Intelligence: The GitHub Effect on LLMs - Why Noisy Code Corrupts Training—and How to Build Reliable Autonomous Coders
John Godel
Sep 25
🌡️ Understanding Temperature in Large Language Models (LLMs)
Vijay Kumari
Sep 25
What are few-shot, zero-shot, and one-shot learning in LLMs?
Avnii Thakur
Sep 25
Large Language Models (LLMs) on Tabular Data
Riya Patel
Sep 22
Extending Existing LLMs with Ollama’s Modelfile: A Practical Guide
Jayant Kumar
Sep 15
How to Evaluate LLMs?
Riya Patel
Sep 15
Artificial Intelligence: How Hidden Triggers and Backdoors Compromise Transformer-Driven LLMs
John Godel
Sep 11
LLMs: Why Modern LLMs Like GPT Are Decoder-Only
John Godel
Sep 02
Artificial Intelligence: Why Modern LLMs Like GPT Are Decoder-Only
John Godel
Sep 02
LLMs: How You Can Keep Your Job Next 5 Years by Mastering Them
John Godel
Sep 01
AI in Practice: LLMs, Transformers, Weights, and Embeddings/Vectors — An In-Depth Builder’s Guide
John Godel
Aug 28
Prompt LLMs to Extract Data from Documents
Mahesh Chand
Aug 27
Contract-Driven Prompt Engineering: Spec-Verified LLM Pipelines That Actually Ship
John Godel
Aug 27
A Deep Dive into LLMs Using GSCP (Gödel’s Scaffolded Cognitive Prompting)
John Godel
Aug 20
How Do Large Language Models Work? A Deep Dive into LLM AI
Baibhav Kumar
Aug 19
How do you guide LLMs to follow instructions more reliably?
Mahesh Chand
Aug 19
Learn Prompt Engineering for LLMs: The Ultimate Beginner’s Guide (ChatGPT, Claude, Gemini)
Mahesh Chand
Aug 12
How to Setup Ollama gpt-oss with Open WebUI
Anoop Kumar Sharma
Aug 11
What are Large Language Models (LLMs) Used for?
Vijay Kumari
Aug 08
Why Prompt Engineering Is Critical for LLMs Like ChatGPT and Claude
Mahesh Chand
Aug 07
How Prompt Engineering Changed the Way I Write Code
Jake Creasy
Aug 05
What is Generative AI?
Mahesh Chand
Jul 28
Empowering Financial Advisors with GSCP & LLMs for Advanced Client Insights
John Godel
Jul 14
How Do You Protect Your Data from LLMs?
Mahesh Chand
Jul 14
Understanding Transformers in Large Language Models (LLMs): Internal Components and Their Roles
John Godel
Jul 13
Top Generative AI Models in 2025: Best LLMs for Text, Image, Video, and Music
Mahesh Chand
Jun 19
Top Open-Source LLMs You Should Experiment With in 2025
Sharp Economy
Jun 17
Should We Train Our Own LLMs or Use Existing Ones via APIs?
Mahesh Chand
Jun 13
Top 5 LLMs for Enterprises
Mahesh Chand
Jun 13
What are Good Use Cases for Integrating LLMs into Our Own Products?
Mahesh Chand
May 24
How to Ensure Data Privacy and Intellectual Property Protection When Using LLMs
Mahesh Chand
May 23
Docker Introducing the New CLI Model Runner
Sarthak Varshney
May 20
What is a key concern when sending data to AI systems?
Mahesh Chand
May 19
How Would You Architect a Chatbot Using a Large Language Model
Madhu Patel
May 15
How Can GenAI Drive Real Business Value in Engineering?
Mahesh Chand
May 14
Vibe Coding / Programming Is Not a Synonym for All AI-Assisted Programming
John Godel
Apr 30
Implementing Agents In LangChain
Madhu Patel
Apr 24
Architectural Design Patterns for Applications Leveraging LLMs
CSharp TV
Jan 10
Introduction to Semantic Kernel SDK and Azure OpenAI
Kuljot Bakshi
1y
Harnessing the Power of Function Calling with Local LLMs using Ollama
Jeeva Subburaj
1y
An Insightful Perspective on Artificial Intelligence
John Godel
1y

Topics

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

Why AI Can Threaten Capitalism More Than the Working Class

What are AI hallucinations

How LLMs Generate Responses

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

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

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

Major Challenges LLMs Face When Working With Healthcare Data

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

How Large Language Models (LLMs) Work

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

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 for LLMs: A Cleaner and More Efficient JSON Alternative

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

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

FastAPI + LLMs: Building a Scalable AI Backend

LLMs + SQL: From Natural Language to Safe, Auditable Queries

LLMs That Fix Things: Field Service Assistants from Triage to Wrench Time

Automating Bank Statement Analysis with LLMs & RAG Techniques

Generative AI: Data Quality Is Destiny - Unifying Data Governance and AI Governance for Trustworthy AI

RAG vs. Fine-Tuning in 2025: A Practical Playbook for Teams

OpenMemory – Self-Hosted Long-Term AI Memory Engine for LLMs

LLMs: GSCP-12 (Gödel’s Scaffolded Cognitive Prompting) for Rigorous Deductive and Inductive Reasoning in LLMs

LLMs: GSCP-12, Memory, and Machine Consciousness — An AI Perspective

Building a Legal Assistant That Understands Case Law Relationships Using Graph-Augmented LLMs Using Python

How Do LLMs Use Context to Generate Better Responses

Context Engineering: Why Prompt Engineering Is Engineering—but Context Engineering Is Not Really

What Are the Core Components of LangChain?

Prompt Engineering Is the Must-Have; Context Engineering Is Its Power Assist

LLMs: Build an AI Core Banking App with FastAPI and GPT-5 (In-Depth)

LLMs: Build an AI Healthcare App with Streamlit and GPT-5 (In-Depth)

LLMs: Private Tailored SLMs (John Gödel’s PT-SLMs) — Narrow, Cheap, Sovereign Models with Shockingly Good On-Domain Performance

GraphQA: Building Graph-Aware Question Answering Systems with LLMs

LLMs, Tokens, Weights, Vectors, Embeddings — A Practical Article

LLMs: From Tokens to Dollars: Cost Engineering for LLM Apps

LLMs Feature Flags: Canary, Rollback, and Contract SemVer

Can You Do Context Engineering Without Prompt Engineering?

LLMs: How to Combine NoSQL Data with LLMs Effectively

How Do Agents Differ from Chains? When to Use Agents vs Chains?

Difference Between a Prompt and a Prompt Template

The Top 10 Large Language Models (LLMs) of 2025: The Age of Cognitive Giants

Large Language Models (LLMs): The Top 10 Models of 2025 - The Age of Cognitive Giants

Everything About Large Language Models—and How They Differ From GPT

How to Combine Tabular Data with LLMs Effectively

Granite 4.0 vs LLaMA 3 vs Mistral: Enterprise AI Models Compared

Large Language Models (LLMs) Under the Hood: A Technical Deep Dive

Large Language Models (LLMs) With Guardrails: How GSCP Turns Raw Capability Into Reliable Systems

Large Language Models (LLMs), Explained: Foundations, Capabilities, Limits, and What Comes Next

How to Evaluate LLMs?

Best Practices for Prompt Engineering in Data Science

How can AI models be used for summarization?

Artificial Intelligence: The GitHub Effect on LLMs - Why Noisy Code Corrupts Training—and How to Build Reliable Autonomous Coders

🌡️ Understanding Temperature in Large Language Models (LLMs)

What are few-shot, zero-shot, and one-shot learning in LLMs?

Large Language Models (LLMs) on Tabular Data

Extending Existing LLMs with Ollama’s Modelfile: A Practical Guide

How to Evaluate LLMs?

Artificial Intelligence: How Hidden Triggers and Backdoors Compromise Transformer-Driven LLMs

LLMs: Why Modern LLMs Like GPT Are Decoder-Only

Artificial Intelligence: Why Modern LLMs Like GPT Are Decoder-Only

LLMs: How You Can Keep Your Job Next 5 Years by Mastering Them

AI in Practice: LLMs, Transformers, Weights, and Embeddings/Vectors — An In-Depth Builder’s Guide

Prompt LLMs to Extract Data from Documents

Contract-Driven Prompt Engineering: Spec-Verified LLM Pipelines That Actually Ship

A Deep Dive into LLMs Using GSCP (Gödel’s Scaffolded Cognitive Prompting)

How Do Large Language Models Work? A Deep Dive into LLM AI

How do you guide LLMs to follow instructions more reliably?

Learn Prompt Engineering for LLMs: The Ultimate Beginner’s Guide (ChatGPT, Claude, Gemini)

How to Setup Ollama gpt-oss with Open WebUI

What are Large Language Models (LLMs) Used for?

Why Prompt Engineering Is Critical for LLMs Like ChatGPT and Claude