What Survives the Downturn: Ivan Gekht on Recession-Proofing a Tech Career

Svetozar Eliseev

10 Oct 2024 — 1 min read

In this episode of Developers Rising, Gehtsoft CEO Ivan Gekht joins the conversation on how developers can build careers that endure—even thrive—in economic downturns.

Ivan brings the same clarity he applies to high-stakes software architecture to the question of personal strategy:

“What makes you irreplaceable isn’t tools—it’s judgment under pressure.”

In this 30-minute conversation, he dives into:

The difference between velocity and value in tough markets
Why engineering judgment beats trendy tech stacks
How developers can shift from “code delivery” to problem ownership
What hiring managers really look for when headcounts freeze

At Gehtsoft, we’ve weathered recessions by focusing on outcomes, not optics. This episode breaks down what that means for individual developers navigating a volatile future.

🎧 Watch on YouTube: Recession-Proof Your Tech Career (Developers Rising)

Risk Management under Real Velocity: Push Detection Downstream, Limit Blast Radius

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

AI and the missing first step in learning

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

Code Is No Longer the Bottleneck. Now What?

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&

AI does not fail because of models. It fails because of governance.

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

Read more

Risk Management under Real Velocity: Push Detection Downstream, Limit Blast Radius

AI and the missing first step in learning

Code Is No Longer the Bottleneck. Now What?

AI does not fail because of models. It fails because of governance.

Cookie Settings