Many engineering teams suffer from a common frustration: feeling like they are part of a feature factory. Tickets come in, code goes out, and nobody is quite sure if it actually made a difference.
The gap between writing good code and building a successful business often feels massive. Business leaders speak in terms of Monthly Recuring Revenue (MRR), Annual Recurring Revenue (ARR), Customer Acquistion Cost (CAC) and retention, while engineering leaders speak in terms of Kubernetes, technical debt and velocity.
But the most effective technology leaders: CTO, VP, Lead Engineer bridge this gap. They understand that their ultimate job isn’t just to manage technology; it is to generate business value through technology.
To do this, we need a shared language. Using foundational concepts from Josh Kaufman’s The Personal MBA, we can translate core business drivers into engineering reality.
Market Research → Value Creation
You can’t create value without understanding what people actually want and are willing to pay for. Too many teams build expensive, complex features based on assumptions. In tech, market research isn’t just surveys, it’s instrumentation.
We need to stop guessing and start validating. This means building telemetry into products from day one to see how users actually behave, not just what they say they want. It means embracing rapid prototyping and A/B testing to validate hyphotheses before committing months of engineering effort.
Area: Discovery & Validation
Metric: Feature Adoption Rate (Are they actually using what we built?)
Marketing → Customer’s Attention
Attracting customers requires getting their attention in a crowded marketplace. Engineers often dismiss marketing as fluff, but bad engineering kills marketing efforts. If you spend $10 to get a user to click an ad, and they land on a white screen that takes 6 seconds to load, you just lit $10 on fire.
Site performance is marketing. Core Web Vitals and SEO renderability directly impact visibility. Furthermore, engineering must build the growth loops: sharing mechanics and seamless onboarding flows that turn one customer into two.
Area: Performance & Growth
Metric: Page Load Time / Mobile Performance Scores
Value Delivery & Operations → Optimal Pricing
People must trust your ability to deliver on what’s promised consistently. This reliability justifes your pricing. Your sales team is out there promising a solution to customer problems. Your infrastructure is the mechanism that delivers on that promise. If the system is down, the value delivery is zero.
This is the realm of Site Reliability Engineering (SRE), Continuous Integration and Delivery (CI/CD) pipelines, and scalable architecture. We justify premium pricing by providing enterprise-grade reliability and security.
Area: Reliability & Scalability
Metric: Uptime/Availability and Deployment Frequency
Customer Service → Customer’s Satisfaction
Satisfaction depends on exceeding expectations and solving problems when they arise. If a user encounters friction, a confusing UI, or a bug, their satisfaction plummets.
Reactive customer service is waiting for a support ticket. Proactive engineering customer service is having the observability tools to know a user hit an error boundary before they even report it. It also means prioritizing UX polish and reducing friction in a self-service workflows so users never need to talk to a human.
Area: Observability & UX
Metric: Mean Time To Recovery (MTTR)
Finance → Retained Eearnings
Profit sufficiency requires bringing in more money than is spent. Engineering is often the single most expensive department in a modern company both in salaries and infrastructure costs. We have a massive responsibility to manage that investment wisely.
FinOps is the active management of cloud costs (AWS/GCP/Azure). But it also means managing technical debt. Like financial debt: tech debt accrues interest in the form of slower development speeds. If we spend too much time servicing interest (fixing bugs due to brittle code), we have less capacity to build new value.
Area: FinOps & Efficiency
Metric: Cloud Cost per Unit (e.g cost per customer, cost per transaction)
Shifting the Mindset
We are not a cost center that types code. We are the engine that powers the business model.
- If our code is buggy, customer service fails.
- If our servers are slow, marketing fails.
- If our architecture is bloated, finance fails.
By understanding these five business pillars, we can make a better decisions. When faced with competing priorities (e.g new feature vs refactoring legacy code), don’t just argue technical merits. Argue on business impact. Which choice better servces value creation, reliability or financial efficiency?