by Gary Worthington, More Than Monkeys

Startups often think they face a straightforward choice: either test thoroughly and move slowly, or skip testing altogether and move quickly. In reality it doesn’t work like that. You can save time in the short term by cutting corners, but eventually the lack of discipline catches up with you and the team spends more energy fixing regressions, firefighting outages, and trying to untangle a messy codebase than they do building new features.

The point isn’t to replicate the overhead of a large enterprise QA department, it’s to introduce enough structure to prevent disasters without losing momentum. Testing in a startup should be pragmatic, stage-appropriate, and tightly linked to the parts of the system that matter most to the business.

The Cost of Ignoring Testing

It’s easy to believe you’re making progress if you can ship quickly, but ignoring testing tends to create a drag that gets worse over time. I’ve seen MVPs delivered in record time, but when it came to launch the teams ended up spending several months fixing regressions and stabilising the product because they hadn’t built even the most basic safety nets. The initial speed was an illusion; in reality, the lack of testing slowed them down when it mattered most.

I’ve also seen startups lose key deals because of this. One team pitched to a large enterprise and their proof-of-concept collapsed during the demo because a recent change had broken a critical workflow. That was the end of the conversation. There was nothing wrong with their product idea, but the absence of even minimal testing meant they never got a second chance.

Testing Is Not a QA Department

Founders sometimes assume that testing is a job for a “QA person” and therefore something that can be solved by a hire, but that mindset is borrowed from enterprises with hundreds of engineers and layers of process. In a startup, testing has to be owned by the team as a whole.

Engineers should write automated tests as they build features, product managers need to define clear acceptance criteria, and testers — when you do eventually hire them — should focus on exploratory testing and edge cases that automation will never cover. I’ve worked with small founding teams who handled this sensibly: the engineer wrote unit tests for the core business logic, the product founder manually tested end-to-end workflows before each release, and only later did they bring in a QA specialist to add depth. That is the right order of operations.

The Startup Testing Pyramid

Mike Cohn’s test pyramid is a useful guide, but it needs adapting to startup realities. At the base you have unit tests, which are quick to write, cheap to run, and catch a large proportion of everyday mistakes. Sitting above them are integration tests, which are fewer in number but extremely valuable because they confirm that your services, APIs, and databases can talk to one another. At the top you have end-to-end tests, which you should reserve for the main user flows eg.signup, login, checkout, because if you try to automate every edge case you will quickly find yourself maintaining brittle tests instead of building product.

A SaaS company with a subscription model provides a good example. Unit tests can validate the pricing logic, integration tests can check that the Stripe webhooks behave correctly, and a couple of automated end-to-end tests can cover the journey from signup through to payment. That level of coverage is enough to give confidence without burdening the team.

Stage-Appropriate Testing Strategy

The right level of testing depends heavily on the maturity of the business. At the MVP stage you should be thinking about unit tests for the core business logic and simple smoke tests to confirm that a deployment actually works, with founders doing manual exploratory testing on the product. At seed, when you are onboarding real customers, it makes sense to add integration tests around the most important flows, particularly payments and onboarding, and to invest in scripts that can quickly seed test data so developers don’t waste time setting things up manually. By Series A, you need a more formal approach: a proper CI/CD pipeline with a reliable automated test suite, contract tests to keep microservices from breaking each other, and exploratory testing led by someone whose focus is quality.

I’ve seen this progression play out in practice. A fitness app at MVP stage only had tests around the workout calculation engine, which made sense because that was the feature users cared about. A B2B SaaS product at seed introduced contract tests for its APIs so customer integrations didn’t break unexpectedly. By the time a marketplace I worked with hit Series A, they had automated the key user flows with Playwright so every release could be shipped with confidence.

Keeping Testing Costs Under Control

Testing does not need to be expensive, but you do need to be deliberate. Automating every possible path is a waste of energy when the product is small. Focus automation on the flows that generate revenue or are critical to credibility, and leave edge cases to exploratory testing until you have the scale to justify more.

Open source frameworks cover most needs. Pytest, Jest, Cypress, Playwright; these are robust, widely used, and free. You don’t need enterprise test tooling that costs more than your cloud infrastructure. And you can still bake in some performance and security discipline without spending much: Locust can help you understand how your API behaves under load, and OWASP ZAP can be used in a CI pipeline to catch obvious security issues early.

A good example is a startup I worked with that used Cypress only to automate login and checkout. Everything else was covered by manual exploratory sessions. This kept the suite lean, focused on the flows that made money, and avoided the flakiness that comes from over-automation.

Common Mistakes

The most obvious mistake is over-engineering. Startups sometimes try to build enterprise-grade frameworks when they have a handful of users, which creates overhead without adding real value. Another is neglecting test data: if you can’t seed realistic data quickly, you end up with tests that only work on one developer’s machine. And the third is outsourcing QA too early. I’ve seen startups hand over responsibility to offshore testers and six months later nobody knew what the tests were doing or why they were failing. Every deploy became a game of chance. Testing cannot be thrown over the wall.

A Practical Playbook

The sensible baseline looks like this: write unit tests for your business-critical logic, automate one or two happy-path end-to-end tests, make sure every build is checked before it goes live, and run regular exploratory sessions so humans can find the unexpected issues. Whenever a bug does slip into production, treat it as a signal that you need a new test.

One founder I know tested onboarding manually every week until Series A, and only then did they automate it. At that stage automation freed up their time for other work, but until then it would have been a distraction. That is what pragmatic testing looks like in a startup.

Closing

Testing in startups is not about achieving perfection, it’s about putting in place just enough structure to prevent avoidable failures. The discipline you bring to testing is what protects your velocity. Without it, speed is an illusion. With it, you can keep moving quickly, scale with confidence, and avoid burning months of runway fixing mistakes that should never have reached customers in the first place.

Gary Worthington is a software engineer, delivery consultant, and Fractional CTO who helps teams move fast, learn faster, and scale when it matters. He writes about modern engineering, product thinking, and helping teams ship things that matter.

Through his consultancy, More Than Monkeys, Gary helps startups and scaleups improve how they build software — from tech strategy and agile delivery to product validation and team development.

Visit morethanmonkeys.co.uk to learn how we can help you build better, faster.

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