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Driving Better Outcomes in the Engineering Industry

Ashwani KumarOctober 5, 20245 min read

Driving Better Outcomes in the Engineering Industry

Eight years ago, I thought being a great engineer meant writing great code. Clean functions, elegant algorithms, clever optimizations.

I was wrong.

Don't get me wrong - code quality matters. But after leading teams, shipping products, and watching some projects succeed wildly while others failed quietly, I've learned that driving outcomes requires a completely different mindset.

Outcome vs. Output

Here's the uncomfortable truth that took me years to internalize:

Nobody cares about your code. They care about what your code does.

  • Your users don't see your beautiful architecture
  • Your PM doesn't care about your test coverage percentage
  • Your CEO doesn't know what a microservice is

What they all care about is: Did we move the needle?

This doesn't mean code quality is irrelevant. It means code quality is a means to an end, not the end itself.

The Metrics That Actually Matter

At Radius Agent, when I built MEL AI, I didn't measure success by lines of code or number of features. I measured:

  • Daily Active Usage - Are people actually using this?
  • Time Saved - Did we reduce contract review time?
  • User Retention - Do they come back?

The result? 150% increase in DAU, 40% reduction in review time. Those numbers told me we were driving real outcomes.

A Framework for Outcome-Driven Engineering

┌────────────────────────────────────────────┐
│            OUTCOME FRAMEWORK               │
├────────────────────────────────────────────┤
│  1. Start with the problem, not the tech   │
│  2. Define success metrics upfront         │
│  3. Ship the smallest thing that works     │
│  4. Measure, learn, iterate                │
│  5. Kill what doesn't work                 │
└────────────────────────────────────────────┘

What I've Learned About Shipping

1. Perfect is the Enemy of Shipped

I've seen brilliant engineers spend months perfecting systems that never saw production. Meanwhile, "good enough" solutions were solving real problems for real users.

The first version of MEL AI was embarrassingly simple. It barely worked. But it was in users' hands within weeks, and their feedback shaped everything that came after.

2. Debugging Time is a Leading Indicator

At Rentomojo, I helped reduce debugging time by 50% through better observability. Here's what I learned: if your team spends more time debugging than building, you have an outcome problem.

Every hour spent hunting down bugs is an hour not spent delivering value. Investing in observability, logging, and monitoring isn't overhead - it's leverage.

3. The Best Engineers Are Force Multipliers

The highest-impact engineers I've worked with aren't necessarily the fastest coders. They're the ones who:

  • Write code that others can understand and modify
  • Build tools that make the whole team faster
  • Document decisions so others don't repeat mistakes
  • Mentor juniors instead of gatekeeping knowledge

At Peoplegrove, I optimized an algorithm that reduced processing time from 2 hours to 15 seconds. But the bigger impact was documenting the approach so others could apply similar thinking to their own problems.

The Uncomfortable Conversations

Driving outcomes sometimes means having conversations that feel uncomfortable:

  • "We should kill this feature - the data shows nobody uses it"
  • "This architecture is overengineered for our scale"
  • "We're solving the wrong problem"

These conversations are hard. They can feel like criticism. But outcome-driven teams have them regularly because they care more about results than being right.

Practical Steps to Drive Better Outcomes

1. Instrument Everything

You can't improve what you can't measure. Before writing a feature, ask:

  • How will we know if this works?
  • What metric will move?
  • How will we measure it?

2. Talk to Users

Engineers often build in isolation. The best insights come from watching real users interact with your product. Every month, I try to sit in on customer calls or support tickets. The perspective is invaluable.

3. Set Weekly Goals, Not Just Quarterly

Quarterly OKRs are great for alignment. But outcomes happen weekly. What's the one thing you can ship this week that will move a metric?

4. Celebrate Learning, Not Just Launching

Failed experiments are still outcomes. If you learned something, you drove value. Create a culture where "we tried X and learned it doesn't work" is celebrated, not hidden.

5. Automate the Repetitive

Every hour your team spends on manual processes is an hour they're not spending on outcomes. I've seen teams transform their productivity just by automating deployments, testing, and monitoring.

The Long Game

Here's what I wish someone had told me eight years ago:

Your career trajectory follows the outcomes you drive, not the code you write.

The engineers who get promoted, who get the interesting projects, who build successful products - they're not necessarily the best coders. They're the ones who consistently move metrics in the right direction.

Write good code, yes. But always ask: What outcome is this code driving?

What strategies have helped you drive better outcomes? I'd love to hear your experiences. Connect with me on LinkedIn.