Leadership in Tech
Leadership in Tech
#338 – August 16, 2026
good managers always stand behind their team, even when things go wrong
The same side of the table
5 minutes by Stay SaaSy
Good managers always stand behind their team, even when things go wrong. Throwing someone under the bus destroys trust and creates a culture of fear that hurts future performance. Instead, step in gracefully, redirect the conversation, or take ownership of the situation. The best people want to work with leaders who have their back.
How G2i tests engineers for judgment, not just code
sponsored by G2i
The bar for a "good" engineer resets with every model release: a year ago the standard was one agent in a tab, now it's orchestrating three or more without losing quality. G2i has recruited engineers for over a decade, and for the last two years has put that judgment to work in frontier AI lab work. Their live vetting sessions score real signal across RL pipelines, RAG, agentic development, LLM engineering, and eval judgment. It’s more about taste, not syntax. Experience a different way to recruit.
Don't be a meat proxy
1 minute by Niklas Gruhn
Niklas argues that pasting AI responses directly into conversations wastes everyone's time. People can run their own prompts, so just forwarding output adds nothing and often makes things worse since AI writing tends to be long, jargon heavy, and sometimes wrong. He says the real value comes from reading the output, checking it, and then explaining it in your own words. That effort is the contribution. Without it, you are just a middleman.
Negative-interest tech debt
2 minutes by Jesse Duffield
Tech debt is usually prioritized by how fast it compounds, but Jesse points out that AI may be changing that calculation. If AI keeps improving, fixing messy code in the future could be easier than fixing it today, even after more code has piled on top. That makes the effective interest rate on tech debt potentially negative, which would mean shipping fast now beats cleaning up later. Companies are already betting on this, though nobody yet knows if the bet will pay off.
AI competence and judgement gap
10 minutes by Itamar Gilad
AI lets people do tasks they couldn't before, but there's a catch: your ability to do something can now outrun your ability to judge whether it's good. A developer might write bad marketing copy, or a product manager might ship flawed code, without realizing it. Using AI as a judge helps but also creates new risks, including overconfidence and colleagues using AI to second-guess each other's work. Nobody has clear answers yet.
The goal is (still) value
6 minutes by Francisco Trindade
AI adoption and higher output do not automatically mean more value. Francisco says that engineering teams should measure what really matters: customer outcomes, delivery speed, and the investment needed to achieve them. Instead of focusing on AI usage, prompts, or token spending, leaders should connect metrics to cycle time and cost. The goal is simple: deliver useful results faster and with less investment.
And the most popular article from the last issue was: