# Learning New Software Development Workflows with AI

DevFeed: [Learning New Software Development Workflows with AI](<https://devfeed.tech/articles/explore-expand-exploit-21577.md>)

Original publisher: [Read original article](<https://maryrosecook.com/blog/post/explore-expand-exploit>)

Published: 2025-03-12T07:00:00Z

Content type: opinion

Language: en

Sources: [Mary Rose Cook](<https://devfeed.tech/sources/mary-rose-cook.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [Learning](<https://devfeed.tech/topics/learning.md>), [cursor](<https://devfeed.tech/topics/cursor.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [ChatGPT](<https://devfeed.tech/topics/chatgpt.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [chatgpt](<https://devfeed.tech/tags/chatgpt.md>), [code](<https://devfeed.tech/tags/code.md>), [cursor](<https://devfeed.tech/tags/cursor.md>), [programming](<https://devfeed.tech/tags/programming.md>)

## AI overview

The author reflects on how AI tools such as ChatGPT and Cursor have changed software development learning and productivity. They argue that adopting AI-assisted workflows requires replacing established programming habits, which creates cognitive strain and demands active supervision.

## Source excerpt

A few months ago, I started sleeping badly. I had been excited about AI since ChatGPT came out. I'd loved using Cursor to help me program since Jay had told me about it over the phone as I walked from Eureka Heights back home to Noe Valley. But, in January, something changed. The proximate cause was a flood of new AI releases. o3-mini, Deep Research, Lightpage. Every week, more intelligence dropping from heaven into my lap. But the bigger change was that I was getting more productive, faster. Type in a few sentences, get a hundred lines of code. A feeling of vertigo. More than that, I could learn a new technique in an hour and become significantly more productive. This was in stark contrast to the previous twenty years I'd spent learning to program. That was a slow, accretive grind. A new technique for encapsulation. A more refined understanding of what it means to "repeat yourself". Learning that you could step-debug a production web app. My friend, Sam, has this model of learning as building a graph. Each node is a piece of information or a skill or a behavior. They're interconnected. Acquiring a new node of knowledge isn't too hard. It's a bit harder to elaborate it. Which is to say, to connect it to the existing nodes in your graph. But the real fucker is when you have to unmake a part of your graph. You get cognitive dissonance because some of the nodes contradict each other or need to be pried apart or replaced. It's very painful to disassemble the graph and remake it. Learning to program was a lot of that. Learning to build software with AI feels completely different. It's much closer to learning a new discipline. Certainly, the old way of programming is relevant. But all the power comes from the new techniques in this new field that doesn't even really have a name. Further, a lot of the new techniques involve a new workflow. Copy code from your editor into GPT, make a request, get code back, paste it into your editor. No, don't do that any more. Instead, sta