To explain what’s happening with AI in software development, it helps to look at how a developer’s work is changing - how it was done, how it’s being done now, and where it’s heading.

Instead of computers, let’s talk about building furniture. It’s not a perfect analogy, but it works.

At some point in history, if you wanted furniture you needed to talk to a skilled craftsman. Anyone who has taken a shot at making simple furniture can attest that it takes more than hammering a few boards together. There are specialized tools and materials, each with their own strengths and weaknesses.

There’s a lot of complaining about candidates using AI during coding interviews. They say it’s “cheating”.

No, it’s not.

Using AI during an interview should be expected and encouraged. The goal of an interview isn’t to see if a candidate can pass a test. The goal is to figure out how well they would do the job.

This article talks about writing code, but the idea applies to just about any knowledge-focused job.

Let’s say you have a problem, and you’re pretty sure that writing an app is the solution. Maybe you want a basic inventory system for your small business. Or maybe you have a small piece of a large legacy system that needs upgrading. It doesn’t matter what it is.

You have a problem, you want software, and you want to make the most of agentic development.

The Problem with “Vibe-Planning”

The impulse is to just start chatting with an AI. You describe your problem, the AI suggests something, you correct it, it suggests something else, and you keep going back and forth until you have what seems like a solid plan.

This is “vibe-planning.” It feels productive, but it has a major flaw. The result is what you think is a good plan, which may or may not actually be a good plan. An AI will happily follow you down a bad path if you lead it there.

There’s a better way. The cool kids are calling it “Research, Plan, and Implement”.

The headlines are terrifying. Every day seems to bring another story about how AI is going to wipe out entire categories of jobs. “The Disappearance of the Entry-Level Job” is a popular one.

These articles paint a grim picture of a world with no starting point for a career.

Like most things, the truth is somewhere in-between. While it’s true that many familiar junior-level positions are being changed or eliminated, that doesn’t mean there are no junior-level positions.

Say it with me: “the jobs will change”.

There’s a lot of chatter about AI reshaping hiring, but it’s not as simple as “replace recruiters” or “solve everything.” The impact depends on how it’s trained, how it’s prompted, and how it’s used. It could streamline things or make them worse, depending on the setup.

Today we are releasing an early version of the Resume Editor, a web-based tool for creating and managing resumes.

This is an alpha release. This means we are still actively adding features and fixing bugs. The project is open source, and we are looking for feedback.

I’ve written quite a bit about the overall process of AI-assisted development. Not the “write code” part of it - if anything, that’s the easy part. There’s a process to writing a project which can be maintained, with bug fixes and new features.

What’s a little tough right now is constantly being in the position of being a manager, stakeholder, business, and end-user. I’ve understood it in an abstract, and tend to be careful about considering them.

It’s so very visceral now.

Most of the big players (Anthropic, Google, et. al) provide all-in-one solutions for writing code. If that’s what you’re doing, that’s fine, but you may be missing out.

For one thing, they can be pretty expensive (unless your company is paying for it). Anthropic’s best - Opus - can get really expensive, really fast. Admittedly, it still costs less than paying for an overseas team, but if it’s coming out of your wallet you’re bound to notice.

Considering how quickly everything is moving, I’m sure this post will age like milk.

So, you’ve got a great process down for developing your code. You’ve got great documentation, 100% test coverage, good git branching and tagging, and all the other detailed steps for generating code.

It sure is a lot of typing, though, isn’t it? Very repititious. Obviously, you should automate those steps! You’re only a little bit away from typing in “Write me an app that does X,Y, and Z!” and then taking a nap while it does the work!

Not so fast…

“AI is just a bubble!” Yep, sure is. So what? That’s no reason to ignore it, or to brush it off as a fad. While nobody can be 100% sure exactly how it will make the world look in five years, you can be sure the world will look different.

Calling something a “bubble” is often a way to dismiss it. But history shows that even when a bubble pops, the underlying technology doesn’t just go away. It sticks around and changes everything.