Ep 61: Subscription Overload—How New AI Lets Designers Consolidate

Subscription Overload: How New AI Lets Designers Consolidate | AI for Interior Designers™
AI for Interior Designers™ Podcast

Subscription Overload: How New AI Lets Designers Consolidate

The AI app gold rush is winding down. Here is what happened, why most of those tools were never built for you, and how designers can finally stop renting fragmented software and start owning their workflows.

This blog was written using AI as a recap from the recording, then edited by the author for accuracy and details.
Key Takeaways
  • Most AI design apps were not built for designers. They were built for the masses — low-hanging fruit from developers who saw a market and had no understanding of professional design process.
  • The AI app gold rush is winding down. Apps that were just wrappers around ChatGPT or Gemini are disappearing because the foundation models themselves now do the same thing cheaper and better.
  • Designers can now build their own apps. Vibe coding — chatting with an AI to build a functional tool — is accessible enough that you do not need a developer to create a workflow that fits how you actually work.
  • Never pay for an annual subscription on a niche AI tool. The landscape changes too fast. Stick to monthly on anything that is not a core foundation model like ChatGPT, Gemini, or Claude.
  • The industry is consolidating into fewer, stronger platforms. Acquisitions like Perplexity buying Visual Electric point toward a future of integrated systems — which is better for designers tired of fragmented subscriptions.

The Short Answer

The flood of AI design apps that hit the market over the past two years is receding. Most of them were not built for professional designers — they were built for anyone who wanted to DIY their house, by developers who had no idea what professional design actually involves. The ones that are disappearing deserved to. And the shift that is happening now — toward fewer, stronger platforms and designer-built custom tools — is genuinely good news for your workflow and your subscription budget.

How AI Apps Are Actually Built — and Why That Matters

Most designers do not realize this: the AI apps they have been paying for did not build their own AI. They took someone else's AI — OpenAI, Google Gemini, Anthropic — and wrapped an interface around it. Think of it like a retailer. The foundation models are the wholesale supplier. The app is the store. You pay retail prices for something the store is sourcing wholesale.

That structure is fine when the wrapper adds genuine value — training the model on something specific, connecting multiple AI tools together, or solving a workflow problem that a raw chat interface cannot solve efficiently. The problem is that most design apps did not do that. They just put a slightly friendlier interface on top of a model that already existed and charged $50 a month for it.

"Why do I need to pay you $50 when I can do this for $20 and so much more internally? These apps are starting to pull back — and the ones that are surviving are the ones that actually do something the raw AI model cannot."

— Jenna Gaidusek

The way Jenna explains it: the good apps are like a room designed by a professional. They took the individual wholesale components — image generation here, text processing there, research capability over there — and assembled them into something coherent that serves a specific purpose better than any individual piece could. The bad apps just took one wholesale component and resold it at a markup with a nice logo.

Where Apps Are Ending Up: Gone, Acquired, or Surviving

The market is sorting itself into three buckets right now — and the category an app lands in tells you a lot about whether it was ever genuinely useful.

Going Away
Apps that were pure wrappers — a chatbot interface on top of ChatGPT marketed as an "interior design AI." The foundation models now do what they did, cheaper. No reason to exist.
Being Acquired
Apps with genuine differentiation — unique workflows, trained models, multi-model integration — getting absorbed by larger platforms. Visual Electric into Perplexity is the recent example. This is a win for the acquired team.
Surviving
Apps built by people who actually understand the industry — often by teams where one person is a designer. They do something specific, well, that the raw AI cannot replicate easily. They are niche but they earn their subscription.

Jenna also noted that apps built by husband-and-wife teams — where one partner is a designer and the other is a developer with a direct line to the actual workflow — consistently outperform those built by outside developers guessing at what designers need. MyDoma is one example she points to. That constant feedback loop between the designer and the builder is what produces tools that actually fit.

The Acquisition Wave: What Perplexity Buying Visual Electric Actually Means

The week before recording this episode, Jenna received an email that Visual Electric — one of her longtime favorite image creation tools for interior designers — had been acquired by Perplexity.

Her reaction: genuinely excited. Not because of what it means for Perplexity's business, but because of what it fills in. Perplexity has always been Jenna's preferred research browser — an aggregator of multiple AI models that surfaces the best response to any query rather than being locked to one model. Its weakness was visual output. Visual Electric's strength was exactly that: generating multiple image options at once, across multiple models, with finer control than what ChatGPT or Gemini offered natively.

This kind of acquisition is the consolidation signal the market has been pointing toward. Fewer, stronger platforms that do more things well — rather than dozens of single-purpose tools you have to stitch together yourself. That is genuinely good news for designers who are tired of managing ten subscriptions to cover one workflow.

Jenna also flagged a broader pattern she has been watching: the major AI companies opened their technology to developers, encouraged them to build apps on top of it, and then — predictably — either replicated the functionality themselves in a major update or acquired the apps that added real value. For the apps that were just wrappers, this was an extinction event. For the apps that built something genuinely different, it was an acquisition opportunity.

Building Your Own Apps: What Is Actually Possible Now

This is the part Jenna has been building toward all summer. She has spent hundreds of thousands of dollars over the years paying developers to build software — including the rendering and e-design platform that was acquired by MyDoma Studio in 2022. That same type of functionality, she says, can now be built in a day for about $20 using AI-powered app builders.

The approach is called vibe coding — essentially chatting with an AI to describe what you want the app to do and having it write the code. Jenna does not have a computer science background. She has tested dozens of platforms over the summer, including Base 44, Bolt, and building directly inside Gemini.

Her current recommendation after all that testing: building inside Gemini gives the most focused, reliable output for design-specific tools. The trade-off is that it lacks the built-in backend infrastructure — databases, login systems, persistent storage — that platforms like Base 44 provide. For internal team tools or simple workflows, Gemini is enough. For anything that needs secure user accounts or stored data, a more complete platform is worth the setup.

1
Start with a real problem you have. Jenna built her paint schedule app because she needed to generate paint schedules faster. She built a proposal tool because she was doing the same work repeatedly. Every good app started with an actual friction point.
2
Describe the workflow in plain language. You do not need to know how to code. Describe what you want to happen step by step — what goes in, what comes out, what it should look like — and let the AI build it.
3
Test and iterate. The first version will not be perfect. That is expected. Ask it to fix specific things. Be specific about what is wrong and what you want instead. This is still a chat conversation.
4
If you need secure storage or login systems, use a platform like Base 44 that handles the backend. For internal single-session tools, a Gemini-built app is usually sufficient.

The bigger picture Jenna is building toward is an AI App Studio for interior designers — tools built by designers for designers, maintained and updated as the technology evolves, and shared inside the community rather than sold back to the industry at SaaS prices. That is already in progress and releasing in the certificate program.

Your Subscription Audit: What to Keep, What to Cancel

Jenna spent two months trying to cancel apps she had been paying for. Half of them were hard to cancel. The lesson: be deliberate before you start, not after. Here is the framework she is now using.

Subscription Decision Framework
  • Core foundation models (ChatGPT, Gemini, Claude, Perplexity) — keep these. They are the wholesale layer everything else runs on. Annual subscriptions are reasonable here.
  • Niche AI apps — monthly only, never annual. The landscape changes too fast. You do not know if the app will exist in a year or if a foundation model will replicate its core feature in the next major update.
  • Apps built by designer-developer teams that do something the raw AI cannot — worth evaluating carefully. These are the ones with staying power.
  • Apps you use less than 20% of — cancel and replace with a custom-built workflow or a foundation model prompt that does the same job.
  • Apps that are just wrappers with preset style options like "boho," "Scandinavian," "mid-century modern" — cancel immediately. A professional interior designer has no use for that.
Frequently Asked Questions
Most of them were wrappers — a slightly simplified interface placed around an existing AI model, usually ChatGPT or Gemini, with a markup on top. When the foundation models improved to the point where a user could get the same result going directly to ChatGPT for $20 a month, there was no longer a reason to pay $50 for the wrapper. The apps that are surviving are the ones that do something genuinely different — multi-model integration, industry-specific training, or workflow automation that the raw models cannot replicate on their own.
Yes — with realistic expectations. Vibe coding, which means describing what you want in plain language to an AI that writes the code, has made basic app creation accessible to non-developers. Jenna built her paint schedule app, proposal builder, and design workflow tools this way. The limitation is backend complexity: login systems, persistent databases, and multi-user access require more setup. For simple internal tools, Gemini or Base 44 can get you there. For apps that need to store data securely and support multiple users, you will likely need some development help for the infrastructure.
Vibe coding is a term for building apps through natural language conversation with an AI rather than writing code manually. You describe what the app should do — what information goes in, what happens to it, what comes out — and the AI writes the underlying code. You review the result, test it, and ask for changes in plain language. Jenna uses this approach inside Gemini for most of the tools in her AI App Studio. Her 9-year-old daughter built a functional skincare habit app with her as their first project together to learn the format.
Visual Electric was one of the standout image generation tools for interior designers — it allowed users to generate multiple image options simultaneously across different AI models, with more fine-grained control than native ChatGPT or Gemini image tools offered. Perplexity, Jenna's preferred AI-powered research browser, acquired it. This matters because it fills in exactly what Perplexity was missing: strong visual capability. The combined platform could become a genuinely useful single tool for research and visualization together.
For core foundation models like ChatGPT Pro, Gemini, Claude, or Perplexity Pro — annual subscriptions make sense if you use them daily. These are not going anywhere and the annual savings are real. For any niche AI app or design-specific tool, stick to monthly. The AI landscape changes fast enough that an app you commit to annually might be obsolete, acquired, or discontinued within 12 months. Never lock in annually to something that has not proven long-term staying power.
Build Your Own
AI App Studio — Tools Built by Designers, for Designers
The AI App Studio lives inside the AI for Interior Designers™ Certificate Program. New apps release every week — paint schedules, proposal builders, design workflow tools — built by Jenna on her own active client projects and shared with the community.
 
Disclaimer: This blog was written using AI as a recap from the recording then edited by the author for accuracy and details.

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Ep 62: Preparing Design Students for the New Job Market with AI

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Ep 60: Work Like a Team of Four: The New AI Reality for Interior Designers