A generative engineering culture is one where nothing seems to fall through the cracks, “we should” gets prioritized and becomes reality, and original ideas and value come primarily from engineers, rather than management. A culture like this is an engine for building capacity, quality, innovation, and sophistication.
How to Create a Great Team Culture (and Why It Matters): Build safety, share vulnerability, establish purpose.: Queue: Vol 17, No 1
As leader of the team, you have significant influence over your team's culture. You can institute policies and procedures that help make your team happy and productive, monitor team successes, and continually improve the team. Another important part of ...
The golden mean of design and engineering - The Intercom Blog
For great products to be built, both design and engineering need to be in balance. If you have a super strong engineering team but a weak or underserved design team, you will struggle.
In spite of hype, many companies are moving cautiously when it comes to generative AI | TechCrunch
Companies are extremely interested in generative AI as vendors push potential benefits, but turning that desire from a proof of concept into a working product is proving much more challenging.
Don't Feed the Thought Leaders
In this article, the author shares their experience as an engineering manager and the challenges they faced when trying to reach alignment and prev...
Deep research requires a slower pace than tech industry work
Anyone working in an industry for a while will become accustomed to that culture—its processes, its norms, its values, its tacit knowledge. Much of this is incredibly valuable, of course, but these ideas can also represent constraints. There are some important impedances here between tech industry culture and research culture. In particular, tech culture is calibrated to a much faster pace. This can lead to impatience or early abandonment when confronting problems which require a researcher’s pace.
Deep research requires a slower pace than tech industry work
Anyone working in an industry for a while will become accustomed to that culture—its processes, its norms, its values, its tacit knowledge. Much of this is incredibly valuable, of course, but these ideas can also represent constraints. There are some important impedances here between tech industry culture and research culture. In particular, tech culture is calibrated to a much faster pace. This can lead to impatience or early abandonment when confronting problems which require a researcher’s pace.
Why Generative UI Is the New Frontier for Business Software
In an era where AI constructs UIs on the fly, discover how SAP is tapping generative UI to reimagine how works gets done.
Computational hermeneutics: evaluating generative AI as a cultural technology
Generative AI (GenAI) systems are increasingly recognized as cultural technologies, yet current evaluation frameworks often treat culture as a variable to be measured rather than fundamental to the system's operation. Drawing on hermeneutic theory from the humanities, we argue that GenAI systems function as "context machines" that must inherently address three interpretive challenges: situatedness (meaning only emerges in context), plurality (multiple valid interpretations coexist), and ambiguity (interpretations naturally conflict). We present computational hermeneutics as an emerging framework offering an interpretive account of what GenAI systems do, and how they might do it better. We offer three principles for hermeneutic evaluation—that benchmarks should be iterative, not one-off; include people, not just machines; and measure cultural context, not just model output. This perspective offers a nascent paradigm for designing and evaluating contemporary AI systems: shifting from standardized questions about accuracy to contextual ones about meaning.
Generative artificial intelligence: The Times and Sunday Times editorial guidelines
As we explore the potential of generative artificial intelligence our commitment is to uphold our high editorial standards.
Cognitive engineering
Cognitive engineering is an interdisciplinary field that applies principles from cognitive psychology, cognitive neuroscience, and human factors to design and develop engineering systems that effectively support or enhance human cognitive processes.[1][2] The field emerged in the 1980s when Donald Norman and others recognized the need to better understand how humans interact with complex technological systems.[3]
Engineering managers have a new job description
Why engineering managers are expected to be hands-on again and how AI tools are making it possible to stay technically sharp while still leading.
A Software Engineering Culture Test
See a shorter, and updated version of this test here: The Pragmatic Engineer Test: 12 Questions on Engineering Culture [https://blog.pragmaticengineer.com/pragmatic-engineer-test/]. I've talked with dozens of software developers about what they like and dislike about their workplace - team, and company - professionally. I'm starting
I'm thinking about what *generatives* are most applicable in the atmosphere — per Kevin Kelly, "better than free" qualities that can't be copied even on the internet: edge.org/conversation/kevin_kelly-bett… Things like contextualization, personalization, sensemaking…ideas? Need to write about this more!
