Balancing Speed and Quality in Technical Product Management

"Move fast and break things" sounds good until you're the one explaining to customers why their payments failed.

I've shipped products under intense deadline pressure. I've also cleaned up the mess from teams that shipped too fast. The answer isn't "always prioritize quality" or "always prioritize speed." It's knowing when to make which tradeoff.

The Real Tradeoff

Here's what people get wrong: speed vs. quality isn't one decision. It's hundreds of small decisions:

• Do we write tests for this feature?
• Do we refactor this messy code or work around it?
• Do we handle this edge case or document it as known limitation?
• Do we do a proper code review or just merge it?

Each decision is a bet. Sometimes speed wins. Sometimes quality wins. The skill is knowing which.

When to Prioritize Speed

1. Validating product-market fit

If you're not sure anyone wants what you're building, ship the ugly version fast. Learning that nobody wants your product after 6 months of polishing is worse than learning after 2 weeks of hacking.

2. Competitive pressure

Sometimes second place is last place. If a competitor is about to launch the same feature, shipping 80% of the quality in half the time might be the right call.

3. Reversible decisions

UI copy? Ship it, you can change it tomorrow. Payment processing logic? Take your time.

4. When the cost of delay is high

A feature that's worth $100K/month costs $3,300 for every day you don't ship it. Factor that into your quality decisions.

When to Prioritize Quality

1. Core infrastructure

The foundation affects everything built on top. Rushing your database schema, API contracts, or authentication system creates pain for years.

2. Anything touching money or sensitive data

Payment bugs don't just annoy users — they create legal liability, chargebacks, and trust destruction. Same for data privacy.

3. When the cost of bugs is high

If a bug means waking up at 3am, losing customers, or manual data cleanup, invest in quality upfront.

4. Hard-to-reverse decisions

Public APIs, data models, external integrations — these are hard to change once customers depend on them.

My Decision Framework

For any feature or decision, I ask:

Practical Quality Tradeoffs

Not all quality is equal. Here's what I cut first vs. last:

Cut first (when under pressure):

• Perfect code style
• Comprehensive documentation
• Edge case handling for unlikely scenarios
• Performance optimization (unless it's critical path)

Cut last (protect these):

• Tests for critical paths (payments, auth, data integrity)
• Security basics
• Error handling that prevents data loss
• Logging that enables debugging

Never cut:

• Data integrity safeguards
• Security vulnerabilities
• Anything that could harm users

The Quality Debt Conversation

When you ship fast, you accumulate quality debt. That's fine — but be honest about it.

I keep a running list of "things we shipped fast that need cleanup." Every sprint, we allocate 10-20% of capacity to paying down this debt. (More on managing this strategically in Technical Debt Is Not the Enemy.)

Teams that ignore quality debt eventually stop being able to ship fast at all. The mess catches up with you.

What "Good Enough" Looks Like

For most features, I aim for:

• Works correctly for the happy path and common error cases
• Doesn't break other things
• Has tests for the critical logic
• Can be debugged when something goes wrong
• Can be changed without rewriting everything

This isn't "high quality" by purist standards. But it ships, it works, and it can be improved later.

Bottom line: The goal isn't perfect quality or maximum speed. It's shipping something good enough, fast enough, with enough awareness of the tradeoffs that you can fix problems before they become disasters. Know when to cut corners, and know which corners you can never cut.