Introduction
During a recent interview, I was asked: What is your approach to technical strategy? How do you choose the right tools, technology, and architecture and why? This is a deceptively simple question, but one that defines a leader’s ability to drive scalable, efficient, and impactful technology decisions. And its follow up; What do you do about technical debt?
Instead of relying on convention or trends, my approach is rooted in first-principles thinking, a method that strips problems down to their core truths and reasons up from there. In this post, I’ll break down my framework for making technical decisions about strategy and debt and share how you can apply it to your own engineering strategy.
Technical Strategy
1. Start with Business Objectives, Not Technology
Technology is a tool to solve business problems, not the other way around. Before evaluating technical solutions, I always ask:
What is the company trying to achieve?
What are the key constraints (time, cost, security, compliance)?
How does this decision impact scalability and long-term growth?
Understanding these fundamentals ensures that every technical choice aligns with actual business needs rather than personal preference or industry hype. For years, higher-level managers were incentivized to meet managed business objectives through structured bonus plans. The carrot-and-stick approach meant that objectives were carefully negotiated upfront to minimize business risk while keeping teams focused on driving measurable impact. This same principle should apply to technical strategy. Decisions must be tied directly to business value, ensuring that technology investments align with long-term goals rather than short-term trends.
2. Deconstruct the Problem Using First-Principles Thinking
First-principles thinking requires breaking a problem down into its fundamental truths and rebuilding the solution from the ground up. Instead of accepting existing architectures or tools as the default, I ask:
What are the absolute requirements vs. inherited assumptions?
What is the simplest, most effective way to solve this without unnecessary complexity?
If we were to build this from scratch today, what would be the optimal approach?
This mindset prevents teams from blindly following trends and instead focuses on what actually works for the specific challenge at hand.
3. Selecting the Right Tools, Technology, and Architecture
Once I have a clear understanding of the problem, I evaluate solutions based on:
✅ Scalability & Maintainability – Can this solution handle 10x growth?
✅ Cost vs. Value – Does the investment provide real business impact?
✅ Team Fit & Expertise – Will the team be productive using this technology?
✅ Security & Compliance – Does this align with required standards?
✅ Vendor Lock-in & Long-Term Viability – Is this a sustainable choice?
I avoid tool-first thinking, where teams pick a technology because it’s popular rather than because it’s the best fit. Every decision is made intentionally, with clear reasoning behind it.
4. Iterate and Validate with Data
The best strategy includes room for experimentation. After making a choice, I advocate for:
Small, testable iterations before full-scale adoption.
Real-world performance testing instead of relying on theoretical best practices.
Quick pivots if a decision proves inefficient or costly.
By continuously validating decisions, we avoid costly missteps and ensure that technology choices evolve alongside business needs.
Technical Debt
Managing Technical Debt: More Than Just One Byte at a Time
Another critical question: What is your approach to paying down accumulated technical debt?
An age old question: How do you eat an elephant? One bite at a time.
The updated response might be one byte at a time, but this is not the right approach. Technical debt often accumulates faster than it can be eliminated, making a reactive strategy ineffective. Instead, I take a strategic and systemic approach (doge like):
Categorize and Prioritize Debt: Not all debt is created equal. I identify high-impact issues that affect scalability, security, or developer productivity and address them first.
Establish a Debt Repayment Plan: Integrating debt reduction into regular development cycles ensures ongoing improvements without disrupting feature velocity.
Prevent Future Debt: Shifting focus to engineering discipline, code reviews, automated testing, and robust architecture decisions helps minimize future debt accumulation.
Communicate Trade-Offs Transparently: Ensuring that business leaders understand the cost of technical debt and the risk of ignoring it, helps align priorities between technical teams and stakeholders.
The key is to balance innovation with maintainability, ensuring that technical debt is managed proactively rather than reactively.
Conclusion: Building a Resilient Technical Strategy
A strong technical strategy isn’t about following trends, it’s about making deliberate, well-reasoned choices that align with the company’s long-term vision. By applying first-principles thinking, breaking problems down to their fundamentals, and prioritizing business outcomes over tech hype, we create systems that are scalable, secure, and adaptable.
The next time you’re faced with a major technical decision, ask yourself: Am I making this choice because it’s the best solution, or because it’s what’s always been done?
Would love to hear from others—what frameworks do you use for making technical decisions? Drop a comment below!