The Executive Imperative AI isn't Just Tech, It's

Let us cut to the chase. When Microsoft poured $10 billion into OpenAI and wove its capabilities into their products, their value skyrocketed by over**$1 trillion**in about a year (Source: Reuters on Microsoft’s market cap surge). On the flip side? Companies sleeping on Artificial Intelligence (AI) are watching their market share shrink and valuations dip.

The message could not be clearer: AI is no longer a niche tech project; it is a fundamental driver of business success or failure. It directly impacts your performance, your competitive standing, and ultimately, your shareholder value.

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Adopting GenAI for the Busy Executive

Slash Costs and Boost Loyalty with AI-Powered Documentation

Remember the early internet, when websites were mostly static “brochureware”? This evolved into e-commerce. The brochureware approach proved surprisingly effective for customer support. It allowed companies to put product documentation, HR manuals, and engineering notes online where people could reference them. Later, search capabilities were added, making this content more accessible. A fundamental challenge remained: search alone couldn’t bridge the gap between complex documentation and user needs.

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Anthropic’s MCP Set up Git MCP Agentic Tooling wit

Anthropic’s MCP: Set up Git MCP Agentic Tooling with Claude Desktop

In this guide, I’ll walk you through setting up and using Model Context Protocol (MCP) Git integration with Claude Desktop. This powerful tooling enables Claude to analyze and interact with your Git repositories directly. It provides advanced code analysis and version control capabilities. We’ll cover everything from basic setup to advanced use cases, troubleshooting, and best practices. Let’s start by understanding what MCP is and why it’s important.

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Anthropic’s new MCP Integration Streamlining AI As

MCP Integration: How Brave Search and Claude Desktop Enhance AI Agentic Assistant Capabilities

Introduction to MCP Agentic AI

The Model Context Protocol (MCP) has revolutionized how AI assistants interact with external data sources, offering smooth integration with tools, repositories, and local or cloud-based datasets. Introduced by Anthropic in late 2024, MCP enables AI to go beyond its traditional constraints, making it more proactive, contextual, and integrated into our workflows. This article focuses on setting up the Brave Search MCP plugin for Claude Desktop to strengthen your AI assistant with advanced web search capabilities. Whether you are a developer or a casual user, this guide will help you integrate this tool to use AI’s full potential. This is a continuation of the article that Rick recently wrote on Setting up Claude Filesystem MCP, but it is a standalone article. First, we’ll explore an in-depth discussion of MCP, followed by practical hands-on use case that show the Brave search connector with the Claude client. This hands-on approach will help you understand the power of the MCP architecture.

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Setting up Claude Filesystem MCP

Setting up Claude Filesystem MCP

The Model Context Protocol (MCP) is a big deal in artificial intelligence. It was introduced on November 25th, 2024, and it’s like a universal connector for AI systems. Before MCP, AI assistants were like chefs with only one ingredient - their own capabilities. But now, with MCP, AI assistants have a “fully stocked pantry” of information to work with. This means they can do more and better things for us.

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Rick and Chris Review Machine Learning

Trail Talk: Rick and Chris Review Machine Learning

On a crisp Saturday morning, Rick and Chris were hiking up a favorite mountain trail, the sun casting a golden glow through the trees. Backpacks strapped on and water bottles filled, they set a steady pace up the incline.

Rick: adjusting his backpack straps

“Chris, you’ve been diving deep into machine learning lately. I keep hearing terms like supervised and unsupervised learning, but I’m a bit fuzzy on what they actually mean.”

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Streamlit Adventures Part 5

Streamlit Adventures Part 5

**Building a Real-Time File Monitor with Streamlit*A Tale of Synchronization, Queues, and Friendly BanterOn a sunny afternoon in Austin, Texas, Rick and Chris were lounging at their favorite coffee shop, laptops open, cups of coffee steaming. Their latest project, Meeting Buddy, was giving them a bit of a headache.***Rick:**Sipping his coffee “You know, Chris, the file drop synchronization just is not working as expected. The UI is not updating when new files are added.”Chris:“Yeah, I noticed that. It is like the UI is oblivious to the new markdown files we generate during meetings.”Rick:“Exactly! We need a way to have the UI respond in real-time as files are added or removed from the directory.”**Chris:**Grinning “Sounds like a job for the watchdog library and a bit of Streamlit magic!”Rick:“Agreed. Let us break it down and build a simple prototype that listens to a directory and updates the UI accordingly.”

They clinked their coffee mugs together, ready to embark on another coding adventure.

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What is Microservice Architecture

This article orginally appeared in several websites and Linked in November 2015.

What is Microservice Architecture?

Rick HightowerEngineering Consultant focused on AI

November 27, 2015

Microservice architecture is a method of developing software systems. Its focus is building small, reusable, scalable services. Applying Microservices becomes very important when you have to create services for polyglot devices: wearables, Internet of Things (IOT), mobile, desktop, and web. The trend towards providing services for rich, native mobile application and web applications started the trend towards Microservices adoption. This is one reason why microservices lean heavily on web technologies like HTTP/REST/WebSocket with JSON,Message Pack, and their ilk. The web technologies provide a low barrier to entry and least common denominator to communication.

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Article Streamlit Part 3 - Form Validation Part 1

Article: Streamlit Part 3

Form Validation Part 1

A Roundhouse Kick into Streamlit Form Validation

Amid the rhythmic thuds of gloves hitting pads, Rick and Chris were immersed in their kickboxing class. Between combos, they exchanged thoughts—not just on perfecting their strikes but also on coding challenges. As they caught their breath, the conversation shifted to Streamlit and the importance of form validation.

Rick: Panting “You know, Chris, it’s like the saying ‘garbage in, garbage out.’ If I don’t validate the data properly in my Streamlit app, I can’t expect good results. I need to guard the gate and make sure only clean data gets through.”

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Streamlit Part 2 Layouts, Components and Graphs

Streamlit Part 2: Layouts, Components and Graphs

Gym Geeks: When Iron Pumping Meets Data Crunching

On a crisp morning at the local gym, Rick and Chris were lifting weights and discussing the next steps in Rick’s Streamlit journey. Amidst the clanking of dumbbells and the hum of treadmills, their conversation delved deeper into the world of Streamlit’s UI components. Rick and Chris, our favorite tech-obsessed gym rats, were at it again, discussing Streamlit components between sets of bench presses.

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The Kafka Ecosystem

This article appeared on LinkedIn on Feb 24th, 2018.

The Kafka Ecosystem - Kafka Core, Kafka Streams, Kafka Connect, Kafka REST Proxy, and the Schema Registry

Rick HightowerEngineering Consultant focused on AI

February 24, 2018

The core of Kafka is the brokers, topics, logs, partitions, and cluster. The core also consists of related tools like MirrorMaker. The aforementioned is Kafka as it exists in Apache.

The Kafka ecosystem consists of Kafka Core, Kafka Streams, Kafka Connect, Kafka REST Proxy, and the Schema Registry. Most of the additional pieces of the Kafka ecosystem comes from Confluent and is not part of Apache.

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Is JParse Fast

This article originally appeared on LinkedIn on Feb 19th, 2024 by Rick Hightower

JParse: The most efficient JSON parser for the JVM yet!

Rick Hightower Engineering Consultant focused on AI

February 19, 2023

JParse

JParse, is the most efficient JSON parser for the JVM yet.

Why JParse?

JParse is the most efficient JSON parser for the JVM yet - it uses an index overlay to deliver lightning-fast parsing speeds.

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Using ChatGPT Chat Function Calls from Java

This article originally appeared on LinkedIn.

Title: Using ChatGPT Chat Function Calls from Java

Author: Rick Hightower

Original Publication Date: July 9, 2023

Using ChatGPT Chat Function Calls from Java

Introduction

As artificial intelligence and chatbots become more popular, it is increasingly important to integrate functions into chat conversations. Functions are small pieces of code that can be reused and embedded into larger programs to perform a specific task. In this blog post, we will discuss how to implement and integrate functions into ChatGPT conversations using JAI, a Java OpenAI API client. This guide will cover how to define a function, handle function callbacks, and mix function results with the content and context returned from the function. We will also provide an example of a weather-related function and its integration into a larger program using a function map.

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Using ChatGPT, Embeddings, and HyDE to Improve Search Results

This article originally appeared on LinkedIn on July 11th, 2023.

Using ChatGPT, Embeddings, and HyDE to Improve Search Results

Rick Hightower Engineering Consultant focused on AI

July 11, 2023

Using ChatGPT, Embeddings, and HyDE to Improve Search Results

Introduction

In today’s fast-paced business world, it is essential to stay ahead of the competition. An efficient search engine that can provide accurate information to your customers or employees can make a big difference. However, building and maintaining a robust search engine can be a challenge. In this dev notebook, we will explore how ChatGPT, Embeddings, and HyDE can help you improve your search results.

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Meta's Llama 2 Threatens Dominance of Other AI Mod

Published originally on LinkedIn on July 20, 2023 Meta’s Llama 2 Threatens Dominance of Other AI Models By Rick Hightower.

Introduction

The world of artificial intelligence (AI) is constantly evolving, and the latest development is the release of Llama 2 by tech giant Meta. This open-source large language model has been trained on a massive 2 trillion tokens, making it a top contender to dominate the industry. In this blog post, we will delve into the implications of Llama 2’s release, its partnership with Microsoft, and the development of other generative AI technologies by Meta.

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Understanding LLMs and Using Chain of Thought

***This article was originally published on Understanding LLM and using Chain of Thoughts on July 24, 2023 by Rick Hightower.***

Understanding LLMs and Using Chain of Thought

Author: Rick Hightower

We will look at a real-world use case that most developers and tech managers should understand. We will give ChatGPT a Java method and ask it to create a Mermaid sequence diagram.

Chain of Thought (CoT) prompting is a technique that improves the performance of Large Language Models (LLMs) on reasoning tasks. It uses few-shot learning. According to Toward Data Science, CoT helps LLMs handle complex tasks like common sense reasoning and arithmetic. It does this by breaking down multi-step requests into smaller steps. This creates a way to see and understand the process. It makes both the input and output easier to manage and tweak.

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Prompt Engineering Getting What You Want From Chat

Original Article: Prompt Engineering: Getting What You Want From ChatGPT Using CoT and Synthetic Prompts July 26, 2023 By Rick Hightower

LLM Prompt Engineering with Chain of Thought and Synthetic Prompts: Getting what you want from ChatGPT using CoT Part 2

Introduction

Large Language Models (LLMs) have become increasingly popular in recent years due to their ability to understand and generate human-like text across various domains (V7 Labs) (Scale AI). These models, such as OpenAI’s GPT-4 and Google’s PaLM 2, are trained on massive amounts of text data, allowing them to excel at tasks like text generation, summarization, translation, and sentiment analysis (Scale AI) (Moveworks). However, despite their impressive capabilities, LLMs must improve their reasoning and problem-solving tasks (Moveworks) to solve complex problems.

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Advanced SQL Techniques for ETL

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  root((Advanced SQL Techniques for ETL))
    CASE Statements
      Conditional Logic
      Data Standardization
      Conditional Aggregation
      FILTER Alternative
    GROUP BY Operations
      Data Aggregation
      Monthly Metrics
      Handling Nulls
      COALESCE Function
    Window Functions
      Partitioning
      RANK
      Rolling Aggregates
      Duplicate Detection
    SQL Functions
      LEAD & LAG
      ROW_NUMBER
      DENSE_RANK
      Cumulative Metrics
    Table Partitioning
      Performance Optimization
      Date-Based Partitioning
      Query Efficiency
      Scalability

Advanced SQL Techniques for ETL

• CASE Statements with conditional logic, standardization, and FILTER alternatives
• GROUP BY Operations including aggregation, metrics, and null handling
• Window Functions with partitioning, ranking, and duplicate detection
• SQL Functions like LEAD(), LAG(), and ROW_NUMBER()
• Table Partitioning for performance and scalability

Ever wrestled with massive datasets using procedural scripts? You know that feeling—like moving a mountain with a teaspoon. Transform that struggle into power with advanced SQL techniques that turn hours into minutes.

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AI-Powered Knowledge Base for Product Managers

AI-Powered Knowledge Base for Product Managers

Author: Rick Hightower

This article originally appeared on August 7, 2023 on LinkedIn.

Building an AI-powered Knowledge Base for Product Managers

An IBM study shows product managers are early adopters of generative AI. They rank in the top-ten professions that use AI. The report states that 21% of product managers use AI daily. Product Managers are leading the AI charge.

As AI’s role in product management increases, product managers must learn how to use AI to stay competitive. Product managers using AI differ from their traditional counterparts by applying their technical expertise to harness AI’s potential in enhancing product management processes.

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ChatGPT at scale Azure Cloud Provides Access to Ch

ChatGPT at scale: Azure Cloud Provides Access to ChatGPT

Author: Rick HightowerThis article was originally published on LinkedIn on July 30, 2023.

Azure Supports ChatGPT 4

Introducing GPT-4 in Azure OpenAI Service: A New Era of AI-Powered Conversations

The Azure OpenAI Service has taken a major leap forward with the introduction of GPT-4, OpenAI’s most advanced language model to date. As of April 3, 2023, GPT-4 is available in preview, allowing customers and partners to experience the power of this cutting-edge AI model. Read more on Azure Blog

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