Author: Chad Michel
The Price Per Token Is Dropping. Will It Stay That Way?
LLMs are at the heart of the current AI movement. An LLM’s ability to respond to prompts with human-like responses is astonishing. All of our first interactions with ChatGPT in 2022 were amazing. The first time I used GitHub Copilot to generate a basic database access method, it was clear that something significant was about…
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Building a RAG Model
It feels like everyone wants to sprinkle a little AI on every software project right now. Sometimes for good reason, and sometimes just because they want a little AI. But AI, much like a seasoning for our food, might not be an improvement. We need to know what tool to use and when. One of…
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Putting GitHub’s New AI Agent to the Test
GitHub has been on a tear recently, adding a lot of new features in a short amount of time. It’s exciting to see the platform evolve so quickly, especially with its deeper integration of AI. One of the newer features that caught my eye is Agent tasks. The core idea is that these tasks can…
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Harnessing the Hype: A Pragmatic Guide to Using AI in Development
Artificial Intelligence is no longer a futuristic concept; it’s another part of our development toolbox. And like any powerful tool, it can be used to build incredible things with great efficiency, or it can create a mess that is difficult to untangle. The key isn’t just using AI; it’s using it with discipline and intent….
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CodeBreak: AI-Assisted Development – Part 3
In Part 2 of this series, we improved the prompts, which solved some of the last issues. But in Parts 1 and 2, a hidden helper was living beneath the surface, helping us along. That helper is the copilot-instructions.md file. I am pre-prompting the LLM with this file to show how I want things to…
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CodeBreak: AI-Assisted Development – Part 2
In Part 1 of this series, we used a template to help with our prompting. Ultimately, it generated code for us. But that code wasn’t perfect. It had many small issues. Probably the most annoying was that it often gets import statements wrong. Now, these are super easy to fix, but they still require fixing….
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CodeBreak: AI-Assisted Development – Part 1
AI (Large Language Models, or LLMs) can be helpful in generating code quickly. The problem is that they often don’t generate useful code. To be honest, they often generate erroneous and potentially insecure code. In this blog post, I will show a potential template to use when prompting LLMs that will help get you closer…
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Coding with AI: How to Get the Results You Actually Want
You can’t talk about software right now without talking about AI or, more accurately, LLMs. These are helping us write software faster. But can they help us be much faster? The common way they help us is by autocompleting code for us. I start writing a method called upsertUser, and then the AI will automatically…
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Core Use Cases
In this series, we are focusing on creating a software system. This has many steps. We created a mental model. Next, we got an overview of the project. Then, we gathered requirements and built an epic-level backlog. In this step, we are going to take those artifacts and break them down into core use cases…
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The 8 Cs of a Software Architect
How do you think about roles and how people fit into roles? This question often arises when evaluating how someone fits into a particular role. No one is perfect or a perfect fit for any role. But the right people will fit most of a given role. It is valuable to have consistent ways to…
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