Franz Zieris

@franzzieris
49 Followers
134 Following
49 Posts
Associate Senior Lecturer for Software Engineering @ Blekinge Institute of Technology (BTH) in Sweden, doing qualitative research
Websitehttps://zieris.net
Workhttps://www.bth.se/eng/research/research-areas/software-engineering/

Nilay Patel's interview with the CEO of Grammarly's parent company is a master class in how to confront a tech executive with facts and skepticism. Strongly recommended.

https://www.theverge.com/podcast/898715/superhuman-grammarly-expert-review-shishir-mehrotra-interview-ai-impersonation

Confronting the CEO of the AI company that impersonated me

Superhuman CEO Shishir Mehrotra on the difference between attribution and impersonation — and what AI companies should owe creators.

The Verge

One way of seeing agentic coding (machine in the driver's seat) is as a continuation of the erosion of the mental model of the system, where on one end of the spectrum we have mob programming (continuous strong consistency/alignment of a shared mental model) and on the other agentic coding (dissolves not just the shared mental model, but even the individual one).

In between (from mob to agentic) are promiscuous pairing → pairing → work in isolation (individual) + async reviews → agentic coding.

I will say one thing for generative AI: since these tools function by remixing/translating existing information, that vibe programming is so popular demonstrates a colossal failure on the part of our industry in not making this stuff easier. If a giant ball of statistics can mostly knock up a working app in minutes, this shows not that gen-AI is insanely clever, but that most of the work in making an app has always been stupid. We have gatekeeped programming behind vast walls of nonsense.

@theorangetheme @davidgerard

I’ve never really believed in the 10x developer, but I was quite fortunate that I spent a long time in software development before I encountered a very real phenomenon (surprisingly common in big tech companies): the -1x developer. The person who creates so many problems that it is an entire other person’s job to clean up the results of the mistakes that they make.

In some rare cases, you may even encounter a -2x or -3x (or more) developer: someone who writes code very quickly and leaves a trail of devastation. They will do things like start a large-scale refactor that doesn’t solve any real problems and introduces some major design flaws, get half way through it, and then use the fact that they are leading this major transition to get promoted and transferred to a different part of the company. The team left behind has to deal with either finishing the refactoring and ending up in a worse place, or undoing all of their work. Both approaches delay new features and the team looks much less productive while they deal with this fallout. And the sudden drop in perceived productivity after they leave is used as evidence for how great they were (‘oh, yes, when I was in that team we were shipping new features and I was leading a transition to pay down a load of technical debt. As soon as I left, the whole thing fell apart. It’s a shame, but I had to move to a place where my skills could benefit the company more.’).

I can see LLMs allowing a -1x developer to easily become a -10x developer. And honestly believe that they are more productive because they never realised that their productivity was negative to start with. I would be entirely unsurprised to discover that industry is now littered with LLM-enabled -10x developers. Technical debt is too weak a term for their output. Companies are accumulating technical nuclear waste and it will be decades of work to fix all of the problems that they have caused.

TIL: “ai;dr”

What a banger:

> We should not be complacent about AI’s effect on attitudes to, and capacities for, knowledge acquisition, and on the willingness to take intellectual risks.

#howAIDestroysInstitutions #genAI #criticism #scholarly #paper #schoolOfLaw

#boston #universityoflaw #WoodrowHartzog #JessicaMSilbey

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5870623

How AI Destroys Institutions

Civic institutions—the rule of law, universities, and a free press—are the backbone of democratic life. They are the mechanisms through which complex societies

Smite et al 2025: "A Wave of Resignations in the Aftermath of Remote Onboarding"
HR data from 2016-2025 in Ericsson Sweden [showed that] employees onboarded remotely during the pandemic were significantly more likely to resign within their first three years, even after returning to the office.
https://arxiv.org/abs/2510.05878
#nwit
A Wave of Resignations in the Aftermath of Remote Onboarding

The COVID-19 pandemic has permanently altered workplace structures, normalizing remote work. However, critical evidence highlights challenges with fully remote arrangements, particularly for software teams. This study investigates employee resignation patterns at Ericsson, a global developer of software-intensive systems, before, during, and after the pandemic. Using HR data from 2016-2025 in Ericsson Sweden, we analyze how different work modalities (onsite, remote, and hybrid) influence employee retention. Our findings show a marked increase in resignations from summer 2021 to summer 2023, especially among employees with less than five years of tenure. Employees onboarded remotely during the pandemic were significantly more likely to resign within their first three years, even after returning to the office. Exit surveys suggest that remote onboarding may fail to establish the necessary organizational attachment, the feeling of belonging and long-term retention. By contrast, the company's eventual successful return to pre-pandemic retention rates illustrates the value of differentiated work policies and supports reconsidering selective return-to-office (RTO) mandates. Our study demonstrates the importance of employee integration practices in hybrid environments where the requirement for in-office presence for recent hires shall be accompanied by in-office presence from their team members and more senior staff whose mentoring and social interactions contribute to integration into the corporate work environment. We hope these actionable insights will inform HR leaders and policymakers in shaping post-pandemic work practices, demonstrating that carefully crafted hybrid models anchored in organizational attachment and mentorship can sustain retention in knowledge-intensive companies.

arXiv.org

@greut @pluralistic
From the article:

“AI is the asbestos we are shoveling into the walls of our society and our descendants will be digging it out for generations,”

#AI

To understand how effectively people currently use and will use AI one can look at two previous transformative technologies: the spreadsheet and the search engine.

The first point is, of course, that they have been transformative. There was a definite 'before' and 'after' for individuals and businesses.

They have been effective. That does not, however, mean their widespread adoption has meant they have been used effectively, and the way these products have evolved has also been suboptimal.

Loving this: "The Copilot Delusion"

Quotes:
"Copilot isn’t that. It’s just the ghost of a thousand blog posts and cocky stack-overflow posts whispering, "Hey, I saw this once. With my eyes. Which means it's good code. Let’s deploy it." Then vanishing when the app hits production and the landing gear won’t come down."

"The problem isn’t just laziness. It’s degradation. Engineers stop exploring. Stop improving. Stop caring. One more layer of abstraction. One more lazy fetch call inside a render loop. Eventually, you’re living in a cathedral of technical debt, and every user pays."

"At that point, you’re not working with a copilot. You’re playing Russian roulette with a loaded dependency graph."

"But even if you're just slapping together another CRUD app for some bloated enterprise, you still owe your users respect. You owe them dignity."

https://deplet.ing/the-copilot-delusion/