· Unstuck · 6 min read
Why most SaaS teams get stuck and how to avoid the rebuild trap
Development has stalled and the word “rewrite” is starting to appear in conversations. This moment is common in growing SaaS products and it’s often where momentum is either recovered or quietly lost for months.
I was on a call recently with a founder whose product had stopped moving forward. Revenue existed, customers were engaged, but feature delivery had slowed to a crawl. The advice coming back from the team was blunt: the system was fundamentally flawed and needed to be rebuilt from scratch.
For a founder, this is a uniquely uncomfortable position. There is already significant time and money invested. The product works well enough to sell, but not well enough to evolve. A rebuild feels risky, but continuing as-is feels worse.
What’s often missed in this moment is that getting stuck is not a sign the product has failed. It’s usually a sign the product has grown faster than the team’s ability to reason about it. How that gap is handled determines whether the next six months are spent shipping or standing still.
Why SaaS Teams Get Stuck
Many SaaS products hit friction somewhere between early traction and the push to scale. Revenue starts coming in, customer feedback accelerates, and the product that worked well enough to launch now feels increasingly resistant to change.
A few patterns show up repeatedly.
The rebuild trap. When the codebase feels messy or slow to change, starting fresh can sound like the cleanest solution. Teams have learned a lot since version one, and a rewrite promises to apply those lessons all at once. In reality, rewrites almost always take longer than expected, pause all feature delivery, and recreate many of the same problems in a new form.
Unclear priorities. As customer requests, internal improvements, and strategic bets pile up, everything starts to feel urgent. Teams jump between tasks, partially finish work, and lose a clear sense of what actually moves the business forward.
Unexamined technical debt. Not all tech debt is harmful. Some of it is a rational trade-off. The problem arises when teams don’t distinguish between debt that is actively slowing delivery and debt that is merely untidy. Without that clarity, effort is spread too thinly.
Decision paralysis. When the system feels fragile, every decision carries perceived risk. Teams compensate by analysing options repeatedly rather than committing. Over time, discussion replaces progress.
If some of these challenges hit close to home, that’s normal. The good news is that teams rarely need to rebuild to recover momentum. The key is learning how to separate genuine constraints from background noise.
The real cost of staying stuck
When a team loses momentum, the impact compounds quickly.
Feature throughput drops, often to near zero. Roadmaps exist, but they stop reflecting reality. Customer requests accumulate, and responses drift toward vague promises rather than delivery.
Competitive position erodes quietly. Teams that were behind six months ago pull ahead simply by continuing to ship.
Morale declines. Developers generally want to see their work in the hands of users. Extended periods of stalled delivery and circular planning sap motivation and increase attrition risk.
Costs rise without obvious line items. Salaries remain fixed, but output falls. Missed deals, delayed upsells, and preventable churn often outweigh the visible engineering spend.
A practical way to regain momentum
Teams typically frame the situation as a binary choice: tolerate the pain or commit to a full rebuild. In practice, there is a broad middle ground focused on understanding and relieving the specific constraints that matter right now.
A useful way to think about this work is in three parts.
1. Clarify what is actually blocking progress
The first step is diagnosis rather than action. The goal is to identify which issues genuinely limit delivery today.
That usually involves mapping the current state honestly. Where does technical debt slow changes measurably? Where are workflows unclear or inconsistent? Which decisions recur because there is no shared or documented answer?
Importantly, this is not about fixing everything. It is about isolating the small number of constraints that, if addressed, would unlock disproportionate progress.
2. Make targeted, low-risk improvements
Once the real blockers are visible, improvement work can be tightly scoped.
Instead of rewriting entire subsystems, teams often get better results by extracting or stabilising the specific areas under pressure. For example, introducing clearer boundaries for new features, documenting how to work safely within an unusual architecture, or improving one brittle integration that slows every release.
These changes are deliberately incremental. They aim to reduce friction while keeping the product moving.
3. Build habits that prevent relapse
Sustainable progress depends less on any single refactor and more on decision-making habits.
Regular review of technical debt, clear ownership of system areas, and simple criteria for deciding whether to fix, tolerate, or work around an issue all help prevent the same problems from resurfacing.
The objective is not a pristine codebase. It is consistent forward motion.
A concrete example
In one case, an MVP had been built by an agency using a highly abstract, schema-driven approach. Controllers and UI components were generated at runtime using reflection. While technically impressive, this made everyday changes extremely difficult.
The maintenance team had reached a point where even small changes felt risky. Features stretched from weeks into months, and many were abandoned partway through. Internally, the startup felt far heavier than its size suggested.
A closer review revealed that the core domain logic was sound. The issue was not correctness, but accessibility. Developers struggled to understand where behaviour originated or how to extend it safely.
Rather than rewriting the system, the focus shifted to making it workable. The most disruptive pain points were prioritised. Clear guidance was created on how to navigate and extend the architecture. Areas where the system was being forced in unintended ways were corrected. Infrastructure was simplified where it had grown beyond actual needs.
The impact was noticeable. Feature delivery accelerated from months to weeks, operational costs fell significantly, and the persistent question of whether a rebuild was necessary largely disappeared once the team could make progress again.
Why this perspective matters
As products mature, complexity is inevitable. What determines long-term velocity is not the absence of problems, but the ability to identify which problems matter and address them without halting delivery.
Most teams do not need dramatic resets. They need clearer visibility, tighter prioritisation, and confidence that incremental improvement is both valid and effective.
I’ll continue sharing practical observations from client work and from building my own products, including what worked, what didn’t, and the trade-offs involved. The most useful lessons tend to come from real constraints faced by real teams.