Why We're Moving Off Squarespace

Arta's First Pivot

Hey Fieldnotes Crew,

Today we're documenting Arta's first major pivot.

As promised from day one of this series, we're here to share the wins and the lessons. This is one of those lessons I'm glad surfaced now instead of six months from now. After a little over a month building the Arta website on Squarespace, I've decided to pivot to Lovable.

As I've gotten deeper into the technical side of Answer Engine Optimization (AEO), I've realized Squarespace doesn't provide the level of technical flexibility I want for Arta's long term growth. Things like llms.txt implementation, advanced schema customization, and deeper control over site architecture are either limited or require workarounds that don't align with how I want to build. These aren't just technical details. They're foundational components of AI visibility.

There's a gap between what we teach and what our site can do, and we're not willing to leave it open. Before helping clients improve their AI visibility, we need to prove the process on ourselves.

This pivot puts me a little behind my original launch timeline, and it means rebuilding the site from scratch. But that's exactly why I'm glad the lesson surfaced now. It's much easier to strengthen a foundation before launch than rebuild one after. More importantly, it allows me to learn how to build and manage a website using AI. That's a skill that benefits Arta, strengthens our client work, and makes us better marketers in the long run.

So let's break down how I'm making this transition as smooth as possible.

Step 1: Pause and Gather

I've officially stopped development on Squarespace.

At this point, there's no value in polishing a site that's about to be rebuilt. Instead, I'm focusing on gathering everything I'll need for the migration: screenshots of the current site, all existing copy, brand assets, links, and content.

To be clear, this isn't a rebrand. Arta's voice, mission, positioning, and visual identity aren't changing. The platform underneath it is. The goal is to move to a platform that gives us more control, more flexibility, and more room to grow as AI search continues to evolve. And honestly, building an AI visibility business on a platform that uses AI to help build websites feels pretty fitting.

Step 2: Go Slow on Purpose

I could try to force this migration in a week. I'm not going to.

The current website remains live while I work through the transition, which gives me the freedom to prioritize quality over speed. The goal isn't to launch as fast as possible. The goal is to launch a site that's technically sound, conversion focused, and built for long term growth. A rushed launch only creates more work later.

Progress over perfection still applies, even when progress means starting a section over.

Step 3: Lean on My Network

One of my longest and closest friends has experience with vibe coding in Lovable and is looking to continue developing that skill set. We've scheduled a working session into our busy schedules to learn together.

I get guidance from someone who's already spent time in Lovable. She gets another chance to deepen her experience with the platform. It's a win-win situation and a reminder that sometimes the fastest way forward isn't doing everything yourself. It's learning alongside people you trust.

Step 4: Get Specific, Then Get Moving

One lesson I've learned quickly is that AI tools perform best when they're given clear direction. So before jumping into the build, I'm getting extremely specific about what the new website needs to accomplish.

That includes:

• Maintaining brand consistency
• Improving user experience and navigation
• Strengthening conversion pathways
• Supporting future AEO initiatives
• Allowing for technical enhancements like llms.txt and schema implementation

Once I know exactly what I want, I can use Claude and ChatGPT to create detailed prompts for Lovable that guide the build instead of leaving things to chance. The goal isn't to guess my way through the process. The goal is to direct it intentionally.

What I Wish I'd Known Before Choosing Squarespace

If you're a small business owner evaluating website platforms right now, here's something I didn't fully understand a month ago: not all website platforms are equally prepared for the future of search. Squarespace is genuinely great for beautiful design, quick deployment, and ease of use. For many businesses, it's an excellent choice. But as I've learned more about AI visibility, I've realized that technical flexibility matters more than I initially thought.

A few questions I'd ask before committing to any platform:

• Can you add or manage an llms.txt file?
• Can you implement custom schema markup for things like services, FAQs, and organizational information?
• How much control do you have over the site's technical structure?
• Will the platform adapt as AI search evolves over the next few years?

I didn't ask those questions when I started building Arta because, honestly, I didn't know enough yet. And that's probably the biggest lesson from this pivot. The deeper you go into any specialty, the longer your "wish I'd known that sooner" list becomes.

Why This Matters

The biggest lesson from this pivot is that AI visibility starts long before content creation. It starts with infrastructure. The platform you choose influences what technical optimizations are possible, how easily you can implement them, and how much control you have as AI search continues to evolve.

AI visibility isn't a one time setup. It's an ongoing technical and content practice that requires adaptability. The businesses that win in AI search won't just create good content. They'll build strong technical foundations that make that content easier for AI systems to understand, trust, and surface.

That's why this decision matters beyond Arta. If we're asking clients to take AEO seriously, our own foundation has to meet the same standard.

Looking Ahead

That's the plan: three weeks, one new platform, one new skill, and a stronger technical foundation for everything Arta builds moving forward. The goal of this case study has never been to show a perfect path. It's to document the real process of learning AEO, making decisions with incomplete information, adjusting when necessary, and building a business in public.

We'll keep sharing the wins, the pivots, and the lessons as they happen.

See you in the next Fieldnotes update!