LLM

“Building Apps with OpenAI” my 29th Pluralsight Course!

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I am excited to share that my 29th Pluralsight course is now live titled Building Applications with OpenAI. This course guides developers through creating modern AI powered applications using OpenAI APIs. Whether you are just getting started with generative AI or looking to integrate it into real projects, you will walk away with practical skills you can use right away.

This was a fun course to build. In this course you will learn how to integrate OpenAI into real world applications from end to end. We begin by setting up the OpenAI API, handling authentication, and designing effective prompts. Then we build a full stack web app that uses AI to analyze and classify data while exploring best practices for deployment, performance monitoring, and error handling. By the end you will have the confidence to build, deploy, and scale your own AI driven solutions.

🧠 Why This Course Matters

Generative AI is reshaping how software gets built and developers are expected to know how to integrate these capabilities into applications. This course gives you the foundational and practical knowledge to do that. You will see how to handle prompt refinement, token limits, deployment tradeoffs, and optimization strategies.

📘 Official Course Description

“Generative AI is changing how software is developed, and developers are now expected to integrate AI features into modern applications. In this course, Building Applications with OpenAI, you’ll gain the skills to build, deploy, and maintain AI-powered web applications. First, you’ll explore how to configure the OpenAI API, manage authentication, and craft effective prompts. Next, you’ll build a full-stack expense tracking app that uses OpenAI to analyze and categorize expenses. Finally, you’ll learn how to deploy your app using platforms like Render or Google Cloud, monitor performance, and handle challenges such as token limits, error handling, and prompt optimization. When you’re finished with this course, you’ll have the knowledge and tools to confidently integrate OpenAI into your own applications and bring AI capabilities to your development projects.“

This course is a part of the “OpenAI for Developers Path” on Pluralsight. The path can be found here: https://app.pluralsight.com/paths/skills/openai-for-developers and has many courses that will teach you various aspects of bringing OpenAI into your applications.


If you’re building applications and need to add AI, this course will help you. Check out the course here:

https://www.pluralsight.com/courses/building-applications-openai

I hope this course serves as a valuable resource in your AI journey. Thank you for your continued support, and Be sure to follow my profile on Pluralsight so you will be notified as I release new courses! 

Here is the link to my Pluralsight profile to follow me:

https://www.pluralsight.com/authors/steve-buchanan

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Im Speaking at BITCON 2025 – Easiest Way to Run LLMs Locally: Meet Docker Model Runner

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🎤 I’m excited to share that I’ll be returning to BITCON in a week! I will be speaking at BITCON 2025, a gathering focused on Black voices in technology, innovation, and community. You can check out the full speaker lineup here: BITCON 2025 Speakers. The conference this year is virtual and its free. You can check out the site here: https://bitcon.blacksintechnology.net

The conference has a ton of great speakers lined up from some of the largest tech companies such as Google, Microsoft, and more. And to top it off the keynote this year is Kelsey Hightower! You dont want to miss this one.

My Session: “The Easiest Way to Run LLMs Locally: Meet Docker Model Runner”
Docker Captain: Steve Buchanan DMR session

At BITCON, I’ll be presenting “The Easiest Way to Run LLMs Locally: Meet Docker Model Runner”. In this session, I’ll look at:

  • Why run LLMs locally? The benefits in terms of cost, privacy, latency, and control
  • How Docker Model Runner simplifies things — containerizing large models, managing dependencies, and lowering friction
  • Demo and walkthrough — showing you step by step how to get a model up and running on your own machine or server
  • Best practices, pitfalls, and tips — what I’ve learned building and deploying these systems
  • Q&A / hands-on help — to get you started with your own setup

My goal is that attendees leave with a concrete, reproducible process they can apply right away.

Why It Matters

Large language models (LLMs) are powerful, but running them locally has often felt out of reach for smaller teams, indie devs, or people in resource-constrained environments. With the right tooling (like Docker Model Runner), we can lower that barrier—unlocking more experimentation, more privacy, and more control over where and how inference happens.

I believe this aligns well with the mission of BITCON: elevating voices, demystifying advanced tech, and making it accessible. I hope this talk helps bridge a gap for folks who want to explore AI locally without getting lost in infrastructure.

I am excited to be speaking at BITCON again. To learn more about my session check it out here:

BITCon Session: The Easiest Way to Run LLMs Locally: Meet Docker Model Runner

BITCON is free! Be sure to register today: HERE

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Recent Blog Posts: MCP Servers, Dev, Multi-cloud Mastery, and Cloud Engineer Resumes

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This is a shorter post, but I wanted to take a moment to share what I’ve been working on lately. Over the past few months I’ve been publishing a steady stream of blog posts on Pluralsight, covering topics across cloud, AI, JavaScript, and beyond. There’s a lot happening in tech right now, and I’ve been fortunate to collaborate with the Pluralsight team to dive into some of these exciting areas:

Check out an overview the blog posts and use the the following links to read more:

Behind the Buzzword: What is MCP (MCP Server)?
A breakdown of MCP servers and why they matter in the evolving landscape of AI.
👉 Read the post

How to Run an LLM Locally on Your Desktop
Exploring why and how you might want to run a large language model on your own machine, with a closer look at Docker Model Runner.
👉 Read the post

What to Emphasize on Your Resume as a Cloud Engineer
Tips on showcasing the skills that make cloud engineers stand out in today’s job market.
👉 Read the post

Multicloud Mastery: How to Train Teams in AWS, Azure, and GCP
Practical advice on enabling engineering teams to work across multiple clouds with confidence.
👉 Read the post

6 Cloud Cost Optimization Strategies and Tools for AWS, Azure, and GCP
A set of proven strategies and tools to help control and reduce cloud spend.
👉 Read the post

How to Add User Authentication to Your JavaScript App
A straightforward guide to securing your JavaScript applications with simple authentication techniques.
👉 Read the post

I’ll be continuing to publish more content in the months ahead, so stay tuned for future posts on cloud-native engineering, AI, and practical developer skills. If you found these articles useful, I’d love for you to check them out and share them with your network.

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