Why Proof-of-Concept Code Quality Can Make or Break Your M&A Deal

Buying one tech company with another? Don’t sign that deal until you’ve looked under the hood. I’ve seen deals fall apart—or get renegotiated at a steep discount—because someone assumed the code would “just work.” Spoiler: it often doesn’t. When evaluating a target, the quality of their proof-of-concept (PoC) code isn’t just a detail. It’s a signal. A strong PoC can tell you the team knows what they’re doing. A weak one? That’s a warning sign. In my years doing technical due diligence, I’ve learned that how a company handles PoC development can make or break the entire M&A outcome.

Why Proof-of-Concept Code Quality Matters in M&A

Sure, financials matter. Market share matters. But if the tech can’t scale or integrate, none of that matters much. During M&A, investors look at assets and potential. What they *should* be asking is: “Can this code actually become a real product?”

The PoC code reveals more than technical skill. It shows discipline, foresight, and how well the team builds for the long term. A well-structured PoC suggests a team that thinks ahead. A messy one? That’s a team cutting corners—great for a quick demo, terrible for a real product.

Indicators of High-Quality PoC Code

When I review a PoC, I’m not looking for perfection. I’m looking for signs of care and intention. Here’s what stands out:

• Clear Documentation: I love when I can understand what the code does in five minutes. Good docs mean the team respects the next person who’ll touch it—maybe your engineers.
• Modular Architecture: Can you swap out a component without breaking everything? That’s modularity. It means the team thought about change, not just speed.
• Test Coverage: If they tested the PoC, they care about reliability. No tests? That’s a gamble—and not the fun kind.
• Code Comments and Best Practices: Clean names, helpful comments, and consistent style tell me the team values clarity. That’s a good sign for integration.

Red Flags in PoC Code Quality

Now, the stuff that makes me pause—or reach for my concerns list:

• Spaghetti Code: One giant file with tangled logic? That’s not a PoC. That’s a time bomb.
• Hardcoded Values: If the database URL or API key is baked in, they didn’t plan to deploy this anywhere real. That’s a red flag for scalability.
• Lack of Version Control: No Git history? Or a messy, inconsistent one? That tells me the team lacks process—and that’s a problem for any integration.
• Frequent Crashes or Bugs: If the PoC crashes during the demo, what’s it going to do under real load? Instability here points to deeper issues.

Scalability Assessment: Ensuring Future Growth

You’re not buying this company for today. You’re buying it for what it can become. And that means scalability. Can the tech handle ten times the users? A hundred? Can it adapt to new features without breaking?

Scalability isn’t just about traffic. It’s about flexibility. Can you add new markets? New services? Or will every change require a rewrite?

Key Scalability Metrics

When I assess scalability, I look at how the system behaves under pressure. Here’s what I check:

• Load Testing: I run simulated traffic to see how the system holds up. Tools like JMeter or Locust help here. If response times spike or errors pile up, that’s a concern.
• Database Performance: A slow database kills scalability. I check indexing, query efficiency, and caching. A well-tuned DB is a quiet hero.
• Microservices Architecture: Breaking the system into independent services makes scaling easier. If it’s a monolith, ask: how will this grow?
• Cloud Infrastructure: Auto-scaling, load balancing, and managed services? That’s a sign they’re ready for growth. No cloud strategy? That’s a limitation.

Code Example: Load Testing with JMeter


// Using JMeter to simulate 1000 concurrent users
// Thread Group: 1000 threads, 10-second ramp-up
// HTTP Request: GET /api/v1/products
// Assertions: Response time < 2000ms, status code 200

Technology Risk Analysis: Identifying Hidden Pitfalls

Some risks don’t show up in a demo. They’re buried in the codebase, the stack, or the legal docs. Ignoring them can cost millions later. I’ve seen deals delayed for months because someone didn’t check the license on a third-party library.

Technology risk isn’t just about bugs. It’s about what can derail integration, security, or compliance.

Common Technology Risks

• Outdated Technology Stack: If they’re using a framework from 2012, that’s a problem. It’s harder to hire for, harder to maintain, and often less secure.
• Licensing Issues: Every third-party tool or library needs a valid license. Some open-source licenses are so restrictive they can block commercial use. Always check.
• Security Vulnerabilities: A quick scan with OWASP ZAP can find SQL injection, XSS, or weak API endpoints. Fixing these post-acquisition is expensive.
• Data Privacy Compliance: If they handle EU or California data, they *must* comply with GDPR or CCPA. Non-compliance isn’t just risky—it can kill the deal.

Actionable Takeaways for Risk Mitigation

• Conduct a Security Audit: Run automated scans and manual checks. Find the weak spots before they find you.
• Update and Patch: Outdated dependencies are a common entry point for attacks. Keep everything current.
• Compliance Review: Get legal and compliance on board early. They’ll help you avoid fines—or worse, a blocked deal.
• Use Static Code Analysis: Tools like SonarQube or ESLint catch bugs and bad patterns before they hit production.

Code Quality Audit: A Step-by-Step Approach

A code audit isn’t just about finding bugs. It’s about understanding the state of the tech. I use a clear process to keep things focused.

Step 1: Static Code Analysis

I start with automated tools. SonarQube is my go-to. It flags:

• Duplicated code (a sign of rushed work)
• Overly complex methods (hard to maintain)
• Security vulnerabilities (critical to fix)
• Code smells (small issues that add up)

Step 2: Code Review

Then I bring in engineers. They look for readability, structure, and whether the code fits your team’s standards. A diverse team catches more issues.

Step 3: Test Coverage Analysis

Good test coverage means the team tests what matters. I use JaCoCo or Coverage.py. If critical paths are untested, that’s a gap.

Step 4: Performance Testing

Finally, I test performance. Tools like Apache Benchmark (ab) or Gatling show how the system behaves under load. Bottlenecks? Let’s find them now.

Real-World Example: The Impact of Poor Code Quality

A few years ago, we reviewed a company with a slick demo. The PoC looked great—until we looked at the code. It was one long file, with hardcoded values, no tests, and zero documentation. We estimated it would take three months to untangle just to start integration. That delay, plus the cost of rewriting, dropped the valuation by 20%. The buyer walked away with a better deal—or walked away entirely.

Lessons Learned

• Proactive Due Diligence: Catching tech issues early saves money and time. Wait too long, and you’re stuck with the bill.
• Invest in Quality: Good code is an investment. It reduces debt, speeds up integration, and lowers risk.
• Plan for Scalability: If the stack can’t grow, neither can the business. Always ask: “What happens when demand doubles?”

Conclusion: The Role of Code Quality in M&A Success

PoC code isn’t just a proof of idea. It’s a proof of process. A well-built PoC tells you the team thinks long-term. A messy one? That’s a sign of shortcuts.

Technical due diligence isn’t optional. It’s how you avoid surprises. By focusing on code quality, scalability, and technology risks, you spot the problems before they cost you. You’ll make smarter offers. And when you do close the deal, integration will be smoother.

Buying a company isn’t just about the tech. It’s about the team behind it. And the best way to judge both? Look at the code. If it’s built to last, you’re on the right track.

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