Templates vs SaaS: A Solo Founder Guide

During the California Gold Rush, the miners who got rich were the exception. The people who reliably made money? The ones selling pickaxes, shovels, and denim jeans. Levi Strauss didn't pan for gold. He sold pants to the people who did.

This story gets repeated so often in startup circles that it's become a cliche. But here's what nobody talks about: the economics have fundamentally shifted. And if you're starting a tech business in 2025, you need to understand why the "sell the shovel" advice might be leading you astray.

The question I keep wrestling with: should you sell templates, prompts, and boilerplates to other builders? Or should you build the full "done-for-you" product yourself? The answer isn't obvious anymore. And generative AI is making this even more complicated.

The Template Economy Is Real (And Profitable)

Let me start with the compelling case for selling templates and boilerplates. The economics are genuinely attractive.

ShipFast, a Next.js boilerplate created by indie hacker Marc Lou, hit $40,000 in monthly revenue within its first month. By April 2024, it was doing $133,000 monthly. Total revenue? Around $250,000 at roughly 90% profit margins. One product. One person. No employees. No customer support team.

The value proposition is elegant: developers who would spend 40-80 hours setting up authentication, payments, and landing pages can buy ShipFast and compress that to a weekend. At $50/hour in development costs, that's $2,000-$4,000 in saved time. ShipFast sells for a fraction of that.

The template market extends far beyond code. PromptBase hosts over 20,000 AI prompts, with some sellers earning five figures monthly. The broader prompt engineering market is projected to grow from $380 billion in 2024 to $6.5 trillion by 2034, according to Precedence Research. Digital audio workstation templates, design system kits, Notion templates, copywriting swipe files. The template economy is massive.

And here's the part that matters for solo founders: templates are achievable. You create the product once, sell it forever. No ongoing customer success team. No infrastructure to maintain. No retention metrics to obsess over. You build it, market it, and move on to the next thing.

The Catch: You're Selling to Professionals

But here's where the template business model reveals its constraints. When you sell templates, boilerplates, or prompts, your customer base is fundamentally limited to other professionals.

A code boilerplate buyer needs to know how to code. A DAW template buyer needs to know how to produce music. A copywriting template buyer needs to understand marketing enough to customize the template for their specific situation. You're not selling solutions to problems. You're selling tools to people who already know how to solve problems.

This creates a market size ceiling. The world has far more people who want their problems solved than people who want to learn how to solve their own problems. A songwriter who doesn't know how to produce can't use your DAW template. But they could pay for a finished production service.

The template business also suffers from low defensibility. Once someone sees ShipFast succeeding, they can create their own Next.js boilerplate. The market tolerates this because the addressable market is large enough, but differentiation becomes increasingly difficult. Your only competitive moats are brand reputation, community, and marketing reach. None of those are durable advantages without continuous effort.

The Brutal Economics of Building Full Products

If templates have ceiling problems, full SaaS products have floor problems. The statistics are sobering.

Analysis of over 1,000 micro-SaaS businesses reveals that 70% generate less than $1,000 in monthly revenue. Only 1-2% exceed $50,000 monthly. The success stories that dominate Twitter and indie hacker forums are statistical outliers, not representative outcomes.

Customer acquisition costs in SaaS average $702 per customer, according to Userpilot research. Fintech companies face even worse numbers at $1,450 per customer. CAC payback periods have extended by 150% in recent years. That means you might spend 12-18 months just recovering your acquisition costs before seeing profit.

Building full products also means building everything else: customer support, onboarding, documentation, retention systems, churn analysis. A template business might require 10 hours a week of marketing. A SaaS business requires a full-time commitment across multiple functions.

But here's the counterpoint: 95% of micro-SaaS businesses achieve profitability within 12 months. That's in stark contrast to venture-backed companies that might burn money for years. The key differentiator is that bootstrapped founders maintain discipline around costs. Successful micro-SaaS operations report 80% profit margins, which sounds impressive until you remember that most of those are making less than $1,000 monthly.

AI Is Rewriting These Rules

Everything I've written so far assumes the traditional calculus. But generative AI is actively disrupting both sides of this equation.

On the template side, AI is making the underlying skills more accessible. A musician who can't produce can now use AI tools to generate arrangements. A marketer who can't code can use no-code platforms combined with AI to build functional applications. The professional skill barrier that defined template buyers is eroding. If AI can help anyone do what templates enabled professionals to do, the template market faces compression.

On the full-product side, AI is dramatically reducing what it takes to build and maintain software. I wrote about my experience building a SaaS with Claude Code. Tools that previously required teams now fall within reach of individual founders. No-code agencies are building custom applications for clients at 80% lower cost and 70% faster than traditional development.

Research from Rockingweb's analysis shows AI-native companies reaching $5 million annual recurring revenue in 24 months, compared to 37 months for traditional SaaS companies. Companies without competitive AI integration face 40-60% efficiency disadvantages by 2027. AI isn't just a feature anymore. It's table stakes.

This creates an interesting reversal. The defensive moat around full software products has always been the difficulty of building them. High barriers meant competition was limited to well-funded teams or technical founders. But if AI makes software dramatically easier to build, does the traditional SaaS moat start to crumble?

And if that moat crumbles, does the "sell the shovel" logic flip? Maybe the real opportunity is no longer selling tools to builders, but becoming the builder yourself. Because if everyone can build, the value shifts from the building to the knowing what to build.

The Third Path: Productized Services

Productized services sit between templates and full SaaS. You package expertise into a repeatable offering without building software. Content marketing retainers, design subscriptions, conversion optimization packages. The economics work: 40-75% gross margins, and customer acquisition often happens through referrals rather than expensive paid channels.

The constraint is scaling. You trade time for money. Without additional humans, revenue hits a ceiling. But here's where productized services shine: many successful template and SaaS businesses started here. You learn what customers actually need by doing the work. You develop templates as internal tools. The service business funds product development and provides market intelligence that guessing can never match.

The Volume Dependency Problem

Here's the math template advocates rarely discuss: a productized service at $4,000/month per client generates $40,000 monthly from ten relationships. To match that with a $99 template, you need 404 sales per month. Every month. Forever.

Marc Lou's ShipFast success relied on years of building in public before launch. His viral launches weren't luck. They were compound interest from consistent audience cultivation. For someone starting from zero, replicating that volume requires either significant marketing investment or years of content creation. The template business model is really a marketing business model with a product attached.

Is the Info Product Dead?

There's a deeper question lurking here. The broader information product market has been struggling for years. College competes with YouTube. Online courses compete with ChatGPT. Why pay $497 for a course when you can ask an AI to teach you the same thing for free?

Templates are essentially packaged information. And if the info product market is compressing, templates face the same pressure. The differentiator becomes audience trust, not product quality. This is why Money Map Press hires ex-Fox News anchors to sell financial newsletters. They're not buying expertise. They're buying an audience that already trusts a familiar face.

For info products and templates alike, audience may matter even MORE than for full software products. Software solves a problem regardless of who built it. Information products live and die by whether people trust the source enough to pay when free alternatives exist everywhere.

A Decision Framework

Choose templates if: You have existing distribution. You're technical and can build for other technical people. You want minimal operational complexity. You're patient enough to build audience before expecting revenue.

Choose full products if: You can identify a specific problem affecting non-technical users. You're willing to commit to the full operational load. You can achieve product-led growth. You have runway to survive 12-18 months to profitability.

Avoid info products unless: You already have a dedicated audience that trusts you. The information you're packaging can't be easily replicated by AI or found free on YouTube. You're prepared to compete on personality and trust rather than content quality alone.

Start with productized services if: You have domain expertise but no audience. You need revenue immediately rather than eventually. You want to learn what customers actually need before building anything. This is exactly what I did with Music Made Pro. I started by offering done-for-you lyric swap services, learning what customers actually wanted through hundreds of orders. That customer intelligence led directly to ChangeLyric, my first real attempt at productizing the solution. I wrote about that journey in my piece on building a SaaS with Claude Code.

The AI factor changes this calculus: it makes the full-product path more achievable for solo founders than ever before. If you have domain knowledge and customer understanding, AI can help you build the product that addresses it. As I discussed in my piece about not using AI as your value proposition, the AI isn't the point. The customer problem is the point. AI is just the tool that makes solving it feasible for one person.

My honest advice? Stop asking which business model is better. Start asking which problem you understand deeply enough to solve. The model is just execution detail. The customer problem is everything.