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I was recently quoted in a TechBullion article on balancing speed and security in business risk management. The core idea was simple: increasing business velocity does not remove the need for risk management. It changes its economics. This is not a technical nuance. It is a decision problem. At higher velocity, both the cost of failure and the cost of inaction increase. Mistakes surface faster. Consequences propagate wider. Delays become more expensive. Yet most organization

What could be the long-term impact of AI on career progression in knowledge work? I saw a post recently asking whether AI will replace junior Scrum Masters. That question itself is not new. But it triggered a realization I had not connected this way before. And it is not very comfortable. How people actually learn a profession Most professional growth follows a pattern often described as Shu–Ha–Ri , a concept from Japanese martial arts. Shu : Follow the rules Ha : Break the r

An advantage that everyone has is not an advantage. Agentic tools handle boilerplate, tests, and even non-trivial features. If your bottleneck was implementation speed, it's gone. Yet Amdahl's Law still applies: the speedup you get from accelerating one part is limited by the parts that don't speed up. The early assumption was that being good at writing code with AI is a competitive edge. It is, but the gap is closing fast. The tools are the same, the models are the same, and

A 2025 BCG analysis cited by Business Insider suggests that only around 5% of companies extract meaningful value from AI investments . The rest experiment, present, and absorb cost. The instinctive explanation is technical immaturity. Models are new. Tooling evolves quickly. Talent is scarce. That explanation is convenient. The DORA 2025 State of AI-Assisted Software Development report shows something more structural. When governance exists, system dynamics look different. W

A comment under one of my posts last week, about the importance of connecting delivery to business outcomes and metrics, raised a very fair question: What about the business? Shouldn’t it also be connected to delivery? Absolutely. It should. This is exactly why the CTO role is crucial for any organization. Even a small business has the same fundamental requirement as a multi-billion-dollar company listed on the NYSE. The scale may differ. The frequency may differ. But the dep

Your project is “on track,” but users and the business are not better off? Most likely, you are getting exactly what you planned for: outputs, not impact. Over the years, I have seen many failed projects. Almost none of them failed because people were lazy or sabotaging the work. Teams were fully committed and working hard, just not on what actually mattered. Plans focused them on deliverables, not on change in reality. Progress looked convincing internally, while users and b

Teams are shipping code faster than ever with AI tools. But code you do not really understand is still tech debt. If you merge AI-generated snippets without knowing how and why they work, you are signing up to debug and extend them later, or to live with a codebase that bites back. GitClear’s 2025 analysis of 211M changed lines from big-tech and enterprise repositories shows what this looks like at scale. Duplicate code blocks are up 8x. Copy-and-paste changes now exceed refa

TL;DR. Moral superiority sells well. And this is why we see it a lot. It gives easy wins today. But it steals the future. If you don’t manage it, or better, avoid it, it replaces thinking with righteousness. Engineers, including CTOs, cannot afford that. We are paid to care about outcomes, consequences, and reality, not emotions and hype. Agile frameworks are a very good example of how this trap works. Agile frameworks easily become a gold cage of moral superiority. I have m

Our team has been using agentic tools daily for more than half a year now. Here's something that worked for us.  The agent handles tests and boilerplate well. However, without rigorous constraints, it breaks things that were just fine before. On longer files it degrades noticeably, loses context and duplicates fragments. AI-Refactoring without proper test coverage ends predictably badly. The key idea that we came to: don't ask the agent to write good code, set the quality sta

Funny thing: most companies don’t slow down because of strategy, talent, or market pressure. They slow down because their technology quietly starts working against them. That force has a name: technical debt. And despite how it sounds, it is not just an engineering issue. It is a business constraint. What technical debt really means Technical debt is the gap between how your systems should work and how they actually work today. Sometimes this gap is intentional. You move fast

Two psychologists once tried to prove humans are rational. They ended up winning a Nobel Prize for proving the opposite. Kahneman and Tversky showed that our brain doesn’t optimize for truth - it optimizes for survival. That’s why we anchor to the first number, stick to old beliefs, or double down on decisions we already know are bad. Not because we’re flawed, but because evolution made our thinking fast, not perfect. Researchers have documented 180+ cognitive biases. Each on

Building a superapp needs strategically selecting functionalities that drive user retention, increase engagement, and unlock revenue. Here’s why these five features are critical, backed by research and real-world data: 1. Unified Wallet & Payments Why It Matters: User Convenience: 78% of superapp users in China cite integrated payments as their primary reason for using platforms like WeChat Pay. Business Impact: Apps with embedded wallets see 25-40% higher transaction complet

by Someone Who Remembers Life Before the Hype Cycle Let us begin with the obvious: everyone, everywhere, is talking about AI. Loudly. In all directions. Some believe it will save us; others think it will destroy us, and a few suspect it might merely rearrange our calendars with passive-aggressive flair. As for me, well, I have no intention of joining either camp. I’m far too old, cynical, and frankly too busy sipping lukewarm tea to march behind yet another flag. So instead,

At Agile2025, Gehtsoft sets a new standard for high-stakes IT delivery, showcasing a fintech 200k-user superapp project from concept to...

The rise of AI prompts a tough question: are traditional software engineers facing extinction? At Gehtsoft, we see a different picture....

Many teams equate busywork with progress, but real success comes from delivering value, not just output. Learn how Evidence-Based Management (EBM) helps Agile teams shift from effort-based thinking to outcome-driven delivery using clear, data-backed business metrics.

Fixing a broken DevOps project is harder than building one from scratch, especially when it's faking agility. This article shows how CIOs can take action to rescue projects afflicted by Fake DevOps and get delivery back on track.

What does it take to prevent fake DevOps? This post breaks down the essential steps leaders must take to build real DevOps. Not just tools and automation, but strategic decisions rooted in the Three Ways and Five Principles. If even one is missing, dysfunction follows.

Fake DevOps emerges when teams focus on process over purpose, creating the illusion of progress without real results. Learn what drives it, what reinforces it, and how to reverse it.

Behind the tools and rituals are you really doing DevOps? Learn how to tell the difference between real and fake.