Secure Boot was designed to solve one of the most fundamental security problems in computing: how to ensure that only trusted software starts your machine. But like any architectural decision, it came with its own trade-offs, and its own technical debt.

In this episode of Technical Debt: Design, Risk and Beyond, Maxim Silaev and Nikita Golovko explore Secure Boot as a case study in how solving one kind of debt often creates another. Maxim explains how the pre-Secure Boot world fragmented BIOS loaders, vendor-specific boot hacks, and no shared trust model, which was itself a form of technical debt waiting to explode. Nikita then breaks down how Secure Boot centralized trust and improved integrity, while introducing new risks: reliance on external signing authorities, firmware lock-ins, and single points of failure.

Together, they unpack:

• How Secure Boot actually works, and why the world before it was pure architectural chaos
• Why "centralized trust" solved one problem but created another
• How dependency on Microsoft’s signing keys became an industry-scale risk
• What communication failures between OEMs, OS vendors, and users taught us about architectural assumptions
• How AI might help us audit and secure firmware chains in the future

Whether you’re in firmware, architecture, or security, this episode shows how even the most well-intentioned design can accumulate invisible debt, and why architecture is as much about people and trust as it is about code.

Next episode: How to design architecture specifically to minimize technical debt from the start.

Technical debt is not just about code! 

it is the visible symptom of deeper organisational issues. When companies try to move faster than their systems, teams, or leadership structures allow, debt shows up in technology but originates elsewhere.

In this episode of Technical Debt: Design, Risk, and Beyond, we will talk with Simon Copsey, a management and technology leader who writes and consults on how technical debt reflects strategy, culture, and communication. Simon shares why debt is felt far beyond engineering, how to spot the hidden debts beneath the surface, and what leaders can do to prevent debt from eroding trust and agility.

📍 Connect with Simon:

• Website: curiouscoffee.club
• LinkedIn: linkedin.com/in/simoncopsey

🎧 Join us to explore how looking at technical debt through an organisational lens changes the way we understand and manage it.

Frontend moves fast — but with every new framework, testing shortcut, or design compromise, teams risk piling up technical debt that quickly becomes visible to users and costly to the business.

In this episode of Technical Debt: Design, Risk, and Beyond, we talk with Christian Joecker, a web developer and UX designer with over 10 years of experience helping companies like BMW, Volkswagen, United Airlines, and the Fraunhofer Institute build and scale digital products.

Christian shares his perspective on:

• Why frontend debt is different from backend or infrastructure debt
• How the constant wave of frameworks creates long-term risks
• The role of testing and documentation in avoiding costly mistakes
• Lessons from integrating new features into legacy stacks
• The one piece of advice he’d give his younger self about handling technical debt

📍 Connect with Christian:

• Website: https://jocker.dev
• LinkedIn: https://www.linkedin.com/in/christianjoecker

🎧 Tune in for practical stories and insights into frontend debt — why it’s visible, why it matters, and how to manage it before it manages you.

Everyone has their own definition of "architecture". For some, it is diagrams. For others, it is documentation, a set of rules, or technical excellence. Some see it as task-setting, others as an evolving discipline. But what does IT architecture really mean in practice?

In this episode of Technical Debt: Design, Risk and Beyond, hosts Maxim Silaev and Nikita Golovko unpack the many faces of architecture. Drawing on real-world stories, they explore how architecture is more than static rules: it is a living, dynamic process shaped by communication, assumptions, and culture.

Together they discuss:

• Why architecture is not "done" once, but evolves with teams and products
• Architecture-as-code: what it is and why it matters
• How wrong assumptions or poor requirements become architectural debt
• Architecture in unexpected places: team structures, product roadmaps, even AI systems
• The human side: communication and technical excellence as architectural pillars

In this episode, Maxim reflects on communication and cultural alignment, while Nikita brings an AI perspective, showing how architecture shifts when data and automation take center stage.

Whether you’re a developer, architect, or product leader, this episode challenges the way you think about architecture, not as a static document, but as an active force that shapes every decision and every debt.

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.

We often talk about “paying off technical debt” as if it were a one-time event, but is that even possible? In this episode, Maxim Silaev and Nikita Golovko dive deep into what it truly means to address technical debt and why the language of "paying off" can be misleading.

Through personal stories, hard lessons, and client case studies, they will examine when refactoring creates real value, and when it is just polishing code, and why debt reduction must be tied to business outcomes. They discuss cultural practices, leadership framing, and the traps teams fall into when they chase perfection instead of progress.

Topics we have covered:

• Why "debt payoff" is not always the right metaphor
• How to prioritise debt work so it will create a business value
• The difference between strategic refactoring and wasteful refactoring
• How teams can measure progress beyond code metrics
• Stories of successful debt reduction and painful failures
• Practical strategies for aligning debt work with product goals

Legacy doesn’t have to mean “bad.” In this episode of Technical Debt: Design, Risk and Beyond, hosts Maxim Silaev and Nikita Golovko discuss and challenge the myths around legacy code. They explore when legacy systems are a liability, when they’re a quiet strength, and why fear often drives decisions more than facts.

Drawing from personal stories and consulting experiences, they discuss real cases where legacy code either supported growth for years or quietly undermined business stability. You’ll hear about LinkedIn’s feed re-architecture, a startup that collapsed under information debt, and a client who treated a fragile core system as untouchable — until it broke the business.

Topics we've covered:

• Why legacy does not automatically mean a "four-letter word"
• The danger of rewriting for emotional reasons
• Lessons learned from LinkedIn’s feed modernisation
• A case study: a startup incomplete by unreliable external data
• The “untouchable module” that brought down a client product
• Practical ways to revive legacy without burning all down

Next episode: What Does It Really Mean to Pay Off Technical Debt?

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 velocity
• How communication debt becomes the real bottleneck
• Patterns and principles that help teams scale safely
• What Twitter’s post-acquisition architecture reveals about org-to-system alignment
• The architect’s role in building scalable structures and guardrails

Whether your team is doubling or just stretched thin, this episode offers practical insight into designing for growth, not just surviving it.

In this episode, we explore how product strategy - even when not explicitly technical - has a profound and in most times invisible impact on software architecture. From market segmentation to feature prioritisation, many product decisions quietly affect long-term architectural consequences.

We unpack how phrases like "just support one more use case" or "we might add multi-tenancy later" seem innocent, but translate directly into complexity, coupling, and irreversible system shape. When architects are not present early, architecture becomes reactive, trying to retrofit decisions that were never meant to scale.

But it is not all doom. In this episode, we discuss what architects can do to influence strategy without blocking innovation: translating technical consequences into business terms, setting guardrails instead of rigid rules, and partnering with product teams to co-design for adaptability.

Real stories illustrate what happens when product and architecture can move in sync, and when they can not.

Topics covered:

• How product strategy quietly drives architectural direction
• The danger of "temporary" decisions that become permanent
• What signals architects should look for in product conversations
• Frameworks and mental models to map product to structure
• How to influence roadmap conversations as a technical leader
• Stories of success and pain - directly from the field

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 like
• Cultural anti-patterns that silently create debt
• Team practices that embed sustainability into development
• How leaders and incentives drive the right (or wrong) behavior
• Real-world examples of cultural impact on technical debt
• Practical steps to start improving your engineering culture today

Next up:
We’ll look at how product strategy shapes your tech stack — often in ways you don’t see until it’s too late.