The problem
At first, I wanted my SaaS starter to feel complete.
Not just useful. Not just production-shaped. Complete.
That instinct sounds good, but in practice it pushed me toward the wrong kind of complexity:
- more abstraction than immediate value
- more optionality than real product leverage
- more architecture than shipping speed
At some point, I realized I was no longer building a strong foundation for real SaaS products. I was building a framework for hypothetical future needs.
That was the turning point.
Why this matters
A SaaS starter is not valuable because it can theoretically adapt to everything.
It is valuable because it removes the expensive setup work that slows real product teams down:
- authentication surfaces
- dashboard structure
- settings architecture
- billing entry points
- coherent product layout
- reusable UI primitives
The more I focused on those concrete foundations, the more useful the starter became.
What I was overengineering
Here are the patterns I started removing.
1. Too many abstraction layers
I was tempted to generalize too early.
Examples:
- wrappers around simple product sections
- generic feature modules before having repeated use cases
- indirection between pages, state, and UI where plain composition was enough
This made the starter look “architected”, but not necessarily easier to use.
The problem with early abstraction is simple:
if the variation is not real yet, the abstraction is usually fake.
2. Optional systems with no current buyer value
I also started adding systems that felt impressive but did not solve the immediate problem of shipping faster:
- advanced permission scaffolding too early
- placeholder enterprise patterns without product demand
- configurable surfaces that were never actually configured
These things create surface area, but not always leverage.
A good starter should reduce the distance between “clone repo” and “start building your product”.
3. Generic dashboards
Generic dashboards are one of the fastest ways to make a starter feel fake.
A serious starter does not need a random KPI grid, a fake activity feed, and placeholder charts.
It needs:
- clear information hierarchy
- realistic empty states
- good defaults for common product surfaces
- room for real product logic
That is a very different goal.
What I kept
I did not remove complexity blindly.
I kept the parts that create real product leverage.
1. Authentication surfaces
A SaaS starter should help developers skip repetitive auth work.
That means keeping strong foundations for:
- sign in
- sign up
- password reset
- protected app areas
- session-aware layouts
2. Settings architecture
Settings are often underestimated, but they are one of the most stable and valuable product surfaces in SaaS.
A good starter should already have structure for:
- profile
- account
- security
- billing
- organization-ready evolution later
3. Billing entry points
Even if the billing engine is not fully wired yet, the UX surface matters early.
Developers need a serious foundation for:
- plan presentation
- upgrade entry points
- billing settings
- invoice and trust patterns later
4. A coherent layout system
Instead of adding more abstraction, I put more effort into consistency:
- public marketing pages
- authenticated app shell
- settings navigation
- dashboard hierarchy
- reusable sections and cards
That creates much more value than speculative flexibility.
The rule I use now
This is the rule I use for PyColors now:
if a feature does not make shipping faster, clarity better, or product structure stronger, it probably does not belong in the starter yet.
That rule removes a lot of noise.
What this changed in practice
Once I simplified the starter, the direction became much clearer.
Instead of asking:
“How can this support every possible SaaS?”
I started asking:
“How can this help a developer ship a credible SaaS product faster this week?”
That shift changed everything.
It improved:
- maintainability
- product clarity
- onboarding speed
- implementation confidence
- upgrade path between free and pro
Blog content vs guide content
This article is intentionally opinionated.
It is not meant to replace a structured guide.
If you want the more educational version of the same topic, start here:
If you want the actual product surface behind this thinking, explore:
Final takeaway
I did not stop overengineering because simplicity looks better.
I stopped because a starter becomes more useful when it is closer to real shipping needs and farther from imaginary future abstraction.
That is the direction behind PyColors:
- stronger product surfaces
- less fake complexity
- faster path to a real SaaS
Turn this article into shipping leverage
Explore the PyColors offer connected to this implementation pattern.