In partnership with

The Future of AI in Marketing. Your Shortcut to Smarter, Faster Marketing.

Unlock a focused set of AI strategies built to streamline your work and maximize impact. This guide delivers the practical tactics and tools marketers need to start seeing results right away:

• 7 high-impact AI strategies to accelerate your marketing performance

• Practical use cases for content creation, lead gen, and personalization

• Expert insights into how top marketers are using AI today

• A framework to evaluate and implement AI tools efficiently

Stay ahead of the curve with these top strategies AI helped develop for marketers, built for real-world results.

Download the Free Report

I have a CS degree. I used to code every day. Then I stopped.

Two years passed. Frameworks changed. Best practices evolved. My muscle memory faded. The thought of opening an IDE felt overwhelming.

Then I built a competitive running app (you can download it here) From scratch. In one week. AI tools made it possible.

Here's what I learned.

The Rust Is Real

Two years away from code is a long time. React had changed. TypeScript had changed. The entire mobile development ecosystem had changed.

I still understood the concepts. I could read code fine. But writing it from scratch? My fingers had forgotten. Syntax that used to flow automatically now required Googling.

This is where AI became my bridge back.

AI as a Coding Partner

I used Claude Code as my main tool. Not as a replacement for thinking. As a partner for doing.

The difference matters. I still designed the architecture. I still made the decisions. But when I needed to remember how to set up a Supabase client or configure HealthKit permissions, Claude filled in the gaps instantly.

It felt like pair programming with someone who never forgets syntax.

Lovable for the Visual Layer

I started with Lovable for the UI. It's an AI tool that generates interfaces. You describe what you want. It builds it.

The result? Clean. Professional. It got me from blank screen to working prototype fast.

But design is just the surface. The hard part is everything underneath.

Break the Problem Into Pieces

AI tools get confused easily. Give them a big, vague goal? They spin in circles. They suggest fixes that break other things.

The fix: break everything down. Then break it down again.

My app needed several things: HealthKit integration, user authentication, weekly matchmaking, real-time competition stats, and push notifications. Each one is its own challenge.

I tackled them in order of difficulty. Hardest first.

Solve the Hardest Problem First

HealthKit was my foundation. If I couldn't pull step data reliably, nothing else mattered.

So I started there. Not with the flashy UI. Not with user accounts. With the boring, technical, mission-critical piece.

Getting background sync to work properly took time. HealthKit has quirks. It needs to sync hourly without draining battery. It needs to handle offline scenarios. It needs to update an iOS widget.

Once HealthKit worked, I moved to authentication. Then matchmaking. Then real-time updates. Then notifications.

Each step built on the last.

Use Multiple AI Agents

Here's a trick that saved me hours: don't rely on one AI.

I used Claude. I used Gemini. I let them review each other's suggestions. When Claude got stuck on a HealthKit issue, Gemini often found a different angle. When Gemini's Supabase query had bugs, Claude caught them.

Think of it like having multiple developers on your team. Each brings different strengths.

Use Expo and React Native

For mobile apps, Expo is a game-changer.

React Native already has great documentation. Expo takes it further. It removes the painful parts: build configurations, device testing, deployment pipelines.

With Expo, you write code. You scan a QR code. Your app runs on your phone. That's it.

I used Expo Router for navigation. Legend-State for managing data. Supabase for the backend. Each tool is well-documented. Each one plays nicely with the others.

The less time you spend on infrastructure, the more time you spend on your actual product.

Expect Dead Ends

I hit walls. A lot of them.

The iOS widget wouldn't update. Background sync drained the battery. The matchmaking algorithm matched people unfairly. Real-time updates caused race conditions.

Some code ran perfectly in the simulator. Then crashed on a real phone.

This is normal. Dead ends aren't failures. They're information. Each wrong path teaches you something about the right one.

The Bigger Lesson

AI isn't replacing developers. It's accelerating them.

My CS degree still mattered. Understanding architecture still mattered. Knowing how to debug still mattered. AI just handled the parts my brain had forgotten.

Two years of rust. One week to shake it off. That's the power of these tools.

I built a competitive running app. Users match anonymously. They compete on weekly step counts. There's HealthKit integration, push notifications, even an iOS widget. It works.

Want to try it? The app is called Tandem. It's live on TestFlight right now. Download it, get matched with a stranger, and see if you can outwalk them this week. I'd love to know what you think.

If you've been away from code, AI is your on-ramp back.

Do the Thing

Life is unpredictable. The best ideas come from trying. The best skills come from building.

Stop waiting for the perfect moment to get back in. Open Claude Code. Describe what you want to make. And start.

The road will be messy. That's the beauty of it.

Catch you soon.

If this helped, share Get Into AI with someone who's been away from code and needs a push to get back in.