Develop Yourself

Become an AI engineer in 45 days: https://parsity.io/ai-devLuke Miller, founder of DCNY, joins the Develop Yourself podcast to share how his 40+ person engineering team uses agentic engineering to build and deploy software at remarkable speed and scale for nearly 200 clients.We talk about what agentic engineering actually looks like in practice, how to maintain quality while moving faster, why engineers need to become more product-minded, and what developers should focus on as AI continues to reshape software careers. Luke also shares his perspective on vibe-coded apps, hiring agentic engineers, and why the most valuable skill may simply be learning how to build things that are genuinely useful.If you’re a developer trying to understand where AI is taking software engineering—and how to adapt without losing yourself in predictions—this episode is for you.

Dallas Davenport is founder of Aivara, an AI automation marketing agency. We met in a Skool group when I offered to look at her app, and I fully expected a vibe-coded dumpster fire (I've dunked on plenty of those). Instead it was complex, it already had users, and it was pretty freaking good.The app is dealership software that replies to customer messages, pulls live inventory off the lot, and automates a bunch of other stuff car dealers deal with. She built it with Claude and she's not a software developer (and doesn't want to be).We talk about how she learned Claude well enough to pull that off, why her site barely mentions AI (dealers just want to sell more cars), how she gets B2B customers without social media, and how she'd vet a developer when she can't read the code herself.

Quite simply, I lay out EXACTLY what I'd build if I were trying to set myself up as an AI engineer. The type of project, the concepts and the tools to learn and why.I genuinely believe that in 2-3 years, the people who learn this stuff will have a massive advantage in the market.You can pick up the project here: https://www.parsity.io/ai-eng-side-project

Want to get into the top 10% of your engineering team by leveraging agentic engineering workflows? I'm planning a 2 day workshop here: https://form.typeform.com/to/EDuBEz4UI shipped a feature with AI in record time.Then I actually read the code.60+ files. Weird abstractions. Tests that technically passed but proved almost nothing. Components rebuilt from scratch for no good reason. What looked like a finished feature was probably 70–80% of the way there.And the worst part? This wasn’t my first time doing this.I’ve also sat in a code review as a senior engineer and realized I couldn’t properly explain code that “I” had just written.I use Claude and Codex constantly. I’m not going back to hand-writing everything. But after using AI to build software at startups, inside my own business, and on large production systems, I think we’re learning the wrong lesson from how fast these tools can code.The question isn’t whether AI can write the code.It’s how much you need to understand before you’re willing to ship it.

I'm opening 12 spots for a weekend workshop in October for devs who want to ship quality software with agents.Sign up here: https://form.typeform.com/to/EDuBEz4U"You're absolutely right, I should have caught that"I'm one of the top 10% of AI users in a 1,000-person engineering org this year. I'm not an AI hater, I ship with these tools daily and I think they're genuinely fun to use. But I've also watched "customers don't care about the code" turn into an excuse for engineers to stop thinking entirely, and that's how you end up with 5,000 lines nobody can explain, a catastrophic bug in prod, and Claude cheerfully saying on the way down.Let's explore ways to maintain quality software without becoming a "meat proxy"