Introduction: The Build vs. Solve Dilemma

If you’ve spent any time in engineering, you know this crossroads. Do you jump in and build something quick, or step back and hunt for a deeper solution? It isn’t just theory—it’s a choice that shows up with nearly every ticket, every “quick” request, every nagging pain point that could use a script (or maybe something more).

Engineering isn’t just about writing code—it’s about deciding what to build, when, and why. Get this wrong, and you’ll end up patching the same holes, week after week. Get it right, and you deliver real value—not just for yourself, but for your team and organization.

The urge to “just fix it” is strong. I’ve been there—sometimes speed feels like everything. But as MIT Sloan Review points out, even seasoned leaders risk solving the wrong problem if they don’t zoom out first.

Here’s one tool I lean on: the ‘ladder of abstraction.’ Before acting, I ask—am I staring at a surface-level symptom, or is this actually a system-wide problem? This simple question is often where my whole approach shifts.

Recognizing Patterns: From Isolated Requests to Systemic Problems

It’s easy to treat every request as unique—a quick fix here, a script there. You feel productive, people thank you, and things keep moving. But if you start noticing déjà vu—similar requests piling up—it’s time to ask: Am I just patching holes in a leaky ship?

How do you tell if you’re seeing a pattern and not just coincidence? Look for signals like:

• Multiple people tripping over the same problem
• Recurring themes in support tickets
• A steady stream of “can you just…” requests orbiting the same pain point

Frequency and similarity are clues that there’s something bigger underneath.

Take password resets as an example. It’s tempting to automate more resets, but what if the real culprit is confusing onboarding? One root-cause fix can save hours of future support. As The Auditor Online highlights, it’s easy to treat symptoms until they become “just how things are.”

Recognizing patterns is the first step. If you want to craft scalable solutions—and escape a life of endless reactive support—don’t skip this pause for reflection.

If you’re looking for ways to deepen your team’s ability to spot these patterns and solve unseen issues, how proactive engineers solve unseen problems offers actionable strategies that can transform your approach.

Framework: When to Just Build

Let’s slow down for a second—because sometimes, what you really need is a quick win. Not every problem calls for a whiteboard session or committee approval. There are moments when speed truly does matter more than strategy.

Here’s how I decide when “just build” is exactly the right call:

• The need is clear and urgent.
  If waiting creates risk or blocks something important, act fast. For example: if a deployment is stuck on a broken script, unblocking it takes priority over perfect planning.
• The requester owns the problem.
  If the person asking will use and maintain your fix themselves, go for it! One-off tools for self-sufficient users rarely circle back as headaches.
• The request is isolated—not systemic.
  Ask yourself honestly: Is this truly a one-time thing? If so, there’s no need to overthink or overbuild.
• Minimal technical debt risk.
  Could your quick fix cause future headaches? If not—if the scope is tight and context clear—give yourself permission to move quickly (but keep an eye on maintainability).

Quick fixes are tempting—I’ve chased their dopamine hit plenty—but they can quietly sneak technical debt into your systems if you’re not careful. Jacek Woźniak warns that even the fastest builds deserve some forethought.

My rule: Think like an MVP (Minimum Viable Product). When stakes are low and context is tight, deliver the simplest solution that works. Don’t gold-plate or pre-optimize for a future that may never come.

For more on making these rapid decisions without sacrificing quality, see the technical decision playbook: ship fast or refine?, which provides tips on balancing velocity with reliability in engineering teams.

The best engineers know when decisive action is needed—a single script can stand between your team and progress. Build it, but keep it simple.

Framework: When to Think Bigger and Solve

But let’s be honest—sometimes building fast is exactly the wrong move. Digging deeper can create lasting impact instead of endless short-term relief.

Here’s my checklist for when to step back and solve at scale:

• Patterns span teams or workflows.
  If several people—even across different functions—are struggling with similar issues, there’s usually a systemic root worth addressing.
• The request is a symptom, not the disease.
  Sometimes storage access issues point to missing documentation or poor onboarding—not just another script. Don’t take every ask at face value; invest in root cause analysis before jumping into code. Techniques like “Five Whys” or “Iceberg Problem Solving” can reveal what’s really driving repeated pain points.

From my own experience, clarifying what problem you’re solving up front saves time down the road (see principles here). It can feel slower at first—but it pays off when you’re not rewriting the same fix every quarter.

• The ROI of solving is clear and compelling.
  Will extra effort now save hours later? If so, make the case for a bigger project—even if it means pushing back on an immediate ask.
• The solution can scale or eliminate future work.
  Ask yourself: Will this prevent similar issues from cropping up again? Can it serve as infrastructure for new features? These are signs of high-leverage engineering.

Thinking bigger doesn’t mean endless meetings or analysis paralysis—it means zooming out before zooming in so your work has lasting value.

One tool I return to often is ‘Leverage Points’ from systems thinking. Find interventions (like better docs or smarter automation) that ripple out positive effects—you’ll multiply your impact without multiplying your hours.

If you’re wrestling with where to draw the line between quick validation and long-term scaling, POC vs. production: the critical decision playbook offers guidance on when to validate fast and when to build for robustness.

Impact: The Power of Strategic Decision-Making

Let’s pull back for a moment—because getting these decisions right (or wrong) doesn’t just affect this week’s ticket. There’s a compounding effect over months and years.

Here’s how that looks in practice: organizations accumulate dozens of one-off scripts for minor requests. At first each script solves its author’s problem—but soon no one remembers which tool does what or how they interact. Maintenance becomes a headache; onboarding new engineers means deciphering years of ad hoc tooling instead of building new features.

I can’t recommend regular ‘technical debt audits’ enough. These don’t need to be formal—just set aside time in team meetings to examine which quick fixes are dragging you down and which patterns are emerging. It’s far easier (and cheaper) to address issues before they spiral out of control.

In contrast, teams who spot patterns and invest in root-cause solutions unlock compounding productivity: smoother workflows, less duplication, fewer recurring support distractions, and happier engineers overall.

This is where your engineering judgment shines—not just building quickly, but balancing speed with long-term vision. These choices add up; they shape both your team culture and your business outcomes over time.

To expand your toolkit for making smart technical decisions with lasting impact, check out the technical decision playbook: 7 lessons for smarter engineering choices for practical frameworks and lessons learned from real teams.

Applying ‘When to Build vs Solve’ in Your Work

So how do you put all this into action? Here are habits I’ve found valuable—and seen transform teams:

• Pause before jumping in: Each time you get a new request, resist the urge to start coding immediately. Ask: Is this truly isolated? Have I seen similar asks before?
• Share context with colleagues: Pattern recognition is a team sport; often someone else has already seen (or solved) what you’re facing.
• Push back (tactfully): If you sense there’s more at stake than meets the eye, don’t be afraid to dig deeper—even if it means saying no to a quick turnaround now for better results later.
• Document your reasoning: Whether you choose a quick fix or invest in analysis, jot down why—that transparency builds trust and lets others learn from your process.
• Adopt lightweight root cause analysis: Even five minutes with “Five Whys” can uncover links between problems that aren’t obvious at first glance.
• Treat your time as an investment: The goal isn’t just code—it’s impact over time.

If you’re interested in how storytelling helps communicate these decisions and gain buy-in from stakeholders, explore the storytelling playbook for engineering buy-in for communication tactics tailored to technical teams.

Take a minute to reflect on your own stories:

• When did you build more than was asked—and did it pay off?
• Were there times when a fast fix came back to bite you?

Sharing these stories openly helps everyone sharpen their decision-making muscles—and avoid repeating mistakes others have already made.

Conclusion

The choice between building fast and solving deeply isn’t binary—it’s an art that lives in context, empathy, and pattern recognition. By building frameworks for when to build vs solve—and applying them thoughtfully—you maximize your impact and help nurture smarter engineering cultures.

So next time you face another request, pause and ask yourself: Am I solving the right problem? That small moment of reflection can be the difference between wasted effort and transformative impact.

Every decision shapes not just your codebase but also your team’s ability to solve meaningful problems together. By consistently pausing to ask better questions—and sharing what you learn—you empower yourself and those around you to create lasting value, one thoughtful choice at a time.