Technical Debt: Design, risk and beyond

Maxim Silaev & Nikita Golovko

We talk to experienced architects and technology leaders about the architectural choices they’ve made — the good, the bad, and the costly. From scaling systems to integrating legacy platforms, from misaligned domains to governance gaps, we discuss how architecture impacts technical debt.You’ll hear honest stories of architectural missteps, what teams learned from them, and how they built systems designed not just to work, but to last.

Episodes

  1. AUG 21

    Can AI help identify hidden technical debt better than humans?

    In this episode of Technical Debt: Design, Risk and Beyond, hosts Maxim Silaev and Nikita Golovko explore whether artificial intelligence can really spot technical debt more effectively than human architects and engineers. Drawing on real-world projects: from investor due diligence to scaling SaaS platforms, they share stories of how AI has surfaced invisible hotspots, misread healthy churn as risk, and mapped sprawling dependencies. Together, they examine three critical signals of hidden debt: Bug Density: how AI clusters recurring defects and predicts hotspots, versus how humans add testing relevance and guardrails.Frequent Changes (Churn): distinguishing between harmful rework and healthy iteration using AI-driven churn analysis, with human context to prevent false alarms.Dependency Sprawl: where graph-based models and SBOM scans reveal fragile chains, but human judgment decides when not to "clean up" aggressively.Maxim and Nikita also reflect on their consulting and startup experience, where AI tools accelerated discovery but human intuition and business context made the final call. The discussion closes with practical guardrails for blending AI insights with architectural judgment, so teams can make technical debt visible, manageable, and tied to real business outcomes. If you have experimented with AI to uncover hidden debt, or wondered how to balance automation with experience, this episode gives you practical frameworks, war stories, and pitfalls to avoid.

    30 min
  2. JUL 22

    The hidden cost of scaling teams and how architecture can help

    As engineering teams grow, many organizations expect velocity to increase, but often the opposite happens. In this episode, we will explore the invisible costs of scaling headcount without evolving your system architecture. From onboarding delays to tangled communication paths and team overlap, we break down why more people often leads to less effective delivery. We dive into the architectural principles that help teams scale safely: service boundaries, team ownership models, platform thinking, and clarity in decision-making. You’ll learn how Conway’s Law plays out in real life, why communication debt is a real and the most dangerous form of technical debt, and how to design systems that support autonomous teams instead of slowing them down. In our company spotlight, we break down what happened to Twitter/X after Elon Musk’s acquisition, how radical business changes exposed architectural fragility, and what lessons tech leaders can take from it. What does it mean when 80% of your engineering organization disappears overnight? Will systems survive or fail? We discuss: Why adding engineers does not always increase velocityHow communication debt becomes the real bottleneckPatterns and principles that help teams scale safelyWhat Twitter’s post-acquisition architecture reveals about org-to-system alignmentThe architect’s role in building scalable structures and guardrailsWhether your team is doubling or just stretched thin, this episode offers practical insight into designing for growth, not just surviving it.

    21 min
  3. JUN 19

    Engineering Culture that Prevents Technical Debt

    In this episode, we explore how technical debt is not just a code problem — it's a cultural one. Together, we unpack the elements of a healthy engineering culture that naturally guards against the slow decay of software systems. We start by defining what “engineering culture” really means and how it silently shapes every architectural decision, shortcut, and trade-off. From there, we dive into practical habits and team rituals that act as cultural safeguards: meaningful code reviews, shared code ownership, continuous refactoring, and treating documentation as an investment — not overhead. We also discuss how leadership sets the tone by what it rewards, how metrics shape behavior, and why engineering must align with product and business to protect long-term system health. Real stories illustrate how culture can either multiply or mitigate technical debt — and what happens when teams shift from blame and burnout to ownership and long-term thinking. We close with reflections and a call to action: examine your own team’s culture. Are you investing in the future — or borrowing from it? Topics covered: What a healthy engineering culture looks likeCultural anti-patterns that silently create debtTeam practices that embed sustainability into developmentHow leaders and incentives drive the right (or wrong) behaviorReal-world examples of cultural impact on technical debtPractical steps to start improving your engineering culture todayNext up: We’ll look at how product strategy shapes your tech stack — often in ways you don’t see until it’s too late.

    34 min

About

We talk to experienced architects and technology leaders about the architectural choices they’ve made — the good, the bad, and the costly. From scaling systems to integrating legacy platforms, from misaligned domains to governance gaps, we discuss how architecture impacts technical debt.You’ll hear honest stories of architectural missteps, what teams learned from them, and how they built systems designed not just to work, but to last.