Adams’ comics were about the nerd experience. About being cleverer than everyone else, not just in the sense of being high IQ, but in the sense of being the only sane man in a crazy world where everyone else spends their days listening to overpaid consultants drone on about mission statements instead of doing anything useful. There’s an arc in Dilbert where the boss disappears for a few weeks and the engineers get to manage their own time. Productivity shoots up. Morale soars. They invent warp drives and time machines. Then the boss returns, and they’re back to being chronically behind schedule and over budget. This is the nerd outlook in a nutshell: if I ran the circus, there’d be some changes around here.

Yet the other half of the nerd experience is: for some reason this never works. Dilbert and his brilliant co-workers are stuck watching from their cubicles while their idiot boss racks in bonuses and accolades.

The repressed object at the bottom of the nerd subconscious, the thing too scary to view except through humor, is that you’re smarter than everyone else, but for some reason it isn’t working. Somehow all that stuff about small talk and sportsball and drinking makes them stronger than you. No equation can tell you why. Your best-laid plans turn to dust at a single glint of Chad’s perfectly-white teeth.

The coordination work that holds projects together disappears the moment it works. On the unfairness of recognition and finding leaders who see it anyway.

Projects just drift toward chaos unless a person is actively holding them together.

The problem is that recognition follows narrative. When a project succeeds, credit flows to the people whose contributions are easy to describe. The person who presented to the board. The person whose name is on the launch email. The person who shipped the final feature. These contributions are real, I’m not diminishing them. But they’re not more real than the work that made them possible. They’re just easier to point at. Easier to put in a slide. And I think that’s where the unfairness starts, slowly, without people really noticing.

Rather than assuming young workers are antisocial or unfriendly, consider why they might find it difficult to interact with others and help them figure out what would make it easier. If they seem overly sensitive, explore why this might be, rather than judging them.

Create space for conversation

Gen Z has been raised in a world of asynchronous communication—texts, DMs, emails, as well as Zoom meetings where they can turn off their video and audio, and participation is often optional. Forget about telling these employees you have an open-door policy; they won’t walk through it. Instead, leaders may need to create intentional, low-pressure spaces for conversation.

Encourage socialization

Your role as a leader isn’t just to manage their work—it’s to introduce them to workplace culture. Do you provide opportunities for socialization? Maybe it’s Cornhole Fridays, a bowling league or a team lunch. Better yet, ask them what they want. Identify your most outgoing employees and form a culture committee. Make socialization part of onboarding, not an afterthought.

Create a formal development plan

The one skill that separates senior engineers from everyone else isn’t technical. It’s the ability to take ambiguous problems and make them concrete.

Senior engineers look at the big, messy, abstract thing and start digging:

• They ask questions nobody else thought to ask.
• They separate what matters from noise.
• They identify what should be done now vs. what to punt.

As software engineers we don’t just crank out code—in fact these days you could argue that’s what the LLMs are for. We need to deliver code that works—and we need to include proof that it works as well. Not doing that directly shifts the burden of the actual work to whoever is expected to review our code.

Why moving judgment to the edges wins in the long run

Quality is the degree to which a product or service meets or exceeds user expectations.

Building quality software is already hard. Centralized quality starts and ends with leadership-driven quality standards and reviews, where a single stakeholder reviews our work and decides whether it meets their standards. This has been the standard at every company I’ve worked with; design and engineering are both taught through critique and reviews from the earliest stages of production to the final delivery of a complete product. This approach can work brilliantly when executed with precision, but it creates a bottleneck: no matter how talented, a single person can only review so much.\

Decentralized quality means putting quality in the hands of workers, not managers.

🎤💥 Oops...The Cert Died Again – Official Lyric Video 💥🎤
From the album: WOW Now That’s What I Call Digital Trust

🔐 It happened again... another expired certificate, another outage, another avoidable disaster. But this time, we’re singing about it.

Unit tests act as living documentation, showing code behavior, staying up-to-date with changes, and covering edge cases to improve code clarity and reliability.

• Unit tests explain code behavior

• Unit tests are always in sync with the code

• Unit tests cover edge cases

https://news.ycombinator.com/item?id=41871629

A new set of principles for placing design at the heart of digital business

The trouble with best practices

The result is a familiar waterfall process, where strategy leads to UX, UX leads to UI, UI leads to “finished” designs, and only then does engineering begin.

Most of the team’s energy goes into producing artifacts for this flow. Storyboards, user journeys, and wireframes are all methods that once helped keep design human-centered, but are now implemented as key deliverables needed for businesses to measure progress.

One cost is that the work is slow. Product teams struggle under the weight of these processes and, at worst, end up filling their time completing checklists instead of doing impactful work. Because the work is done in isolation in page-based, manual design tools far away from the medium we’re designing for, the outputs tend to be derivative, perpetuating a pervasive monoculture in digital design.

The “Double Diamond” process rarely works well in real projects. Here’s how the design work actually gets done in small and large organizations, and where design has most leverage.

https://www.smashingmagazine.com/2023/08/improving-double-diamond-design-process/

“The formulation of a problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill. To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science.”

— Albert Einstein & Leopold Infeld

https://www.infoq.com/articles/problem-reframing-method/

• Avoid building wrong solutions or products by directly jumping into solution thinking and not empathizing with the problem
• Finding a better problem that fits the customer’s needs better opens up a space for more innovative and sustainable solutions
• Looking at a problem from different angles helps to build more innovative and sustainable solutions or products
• Try different reframing practices and methods, such as examining bright spots or looking in the mirror; there is not a one-size-fits-all approach

https://blog.logrocket.com/ux-design/double-diamond-design-process/

Stanford's Jeremy Utley reveals that "most people are not fully utilizing AI's potential." Why is that? He explains that it lies in how we approach AI. He said a simple mindset shift could be what you've been missing in the AI revolution.

Creativity is doing more than the first thing you think of

Think of LLM as a teammate and not just a tool. Provide it feedback! Let it ask you questions!

Key Insights:
📌How treating AI as a teammate rather than just a tool can dramatically improve outcomes
📌Why you should have AI ask you questions instead of just answering yours
📌How non-technical professionals can leverage AI to achieve extraordinary results
📌The difference between treating AI as a tool versus as a teammate

00:00 Intro

If you want to learn more about creativity using AI with Professor Jeremy, please refer to the link below!
👉 https://www.jeremyutley.design/ai-newsletter

Perl came for free. How much have I contributed in return? Absolutely nothing.

I work as what I’d call an inside-contractor.
I’m a speed-dial (is that still a thing?) phone call away.
Occasionally, a client will call me a dozen times in a day.
I’m closer than their coleague in the next office.

We have decades of experience trying to automate processes. The biggest lesson is that automation is not about the easy and known flow, but about exception handling.

The best diagnosis for exception handling I can think of is to wait on line at the post office. If you’ve ever done that, you know the thought of “doesn’t anyone just want to mail a package” comes to mind. As it turns out the entire flow at the post office (or DMV or tax office) is about exception handling. No amount of software is going to get you out of there because it is piecing together a bunch of inputs and outputs that are outside the bounds of a system.

The ability to automate hinges not just on the ability to know the steps to take for predefined inputs, and not even the steps to take if some inputs are erroneous or incomplete, but what to do if you can’t even specify the inputs.

My favorite example of the latter is how the arrival of IBM computing in the 60s and 70s totally changed the definition of accounting, inventory control, and business operations. Every process that was "computerized" ultimately looked nothing at all like what was going on under those green eyeshades in accounting. Much of the early internet (and still most bank and insurance) look like HTML front ends to mainframe 3270 screens. Those might eventually change, just not quickly. It might be that the "legacy" or "installed base" of many processes is such that the cost to change is too monumental.

https://news.ycombinator.com/item?id=41765594

The feedback we get from users is not what it seems! As software creators we apply a lens that makes us take user feedback in many different - often unhelpful - ways from how it was intended. Here's a list of user feedback myths to help jog assumptions.

For tech and AI talent, jobs at financial services companies are more desirable than they have ever been. Banks have been working hard to make it happen.

The 70% rule: If you’re roughly 70% happy with a piece of writing you’ve produced, you should publish it. If you’re 70% satisfied with a product you’ve created, launch it. If you’re 70% sure a decision is the right one, implement it. And if you’re 70% confident you’ve got what it takes to do something that might make a positive difference to the increasingly alarming era we seem to inhabit? Go ahead and do that thing. (Please!)

70% is actually better than 100%

Moving forward at 70% takes more guts, more strength of character, than holding out for 100%, because it entails moving forward amid uncertainty, anxiety, and the disagreeable feeling that comes with putting less-than-perfect work into the world.

Why LLMs will transform development but not how you think

it's about how AI tools are enabling a new category of software that simply couldn't exist before.

When someone can describe their specific needs conversationally and receive working code in response, the economics of personal software development shift dramatically.

Think of it this way: just as spreadsheets enabled non-programmers to perform complex calculations and data analysis, AI-assisted development tools are enabling non-programmers to create personal software solutions.

When giving feedback on presentations most of us are unsure what to say and how to say it without upsetting anyone. That is why I designed a set of cards that you can hand out to your audience before…

1. Messaging: the message of the talk and the call to action.

2. Clarity: how easy the talk was to understand and follow.

3. Credibility: whether the facts and arguments presented were believable.

4. Engagement: which parts were more engaging, and which less.

5. Voice: pitch, quality, tempo and pauses.

6. Language: the type of language used and variety in expression.

7. Physicality: the speaker’s body language, gestures and movements.

8. Visuals: the quality and effectiveness of any visual aids used.

9. Connection: the speakers rapport and connection with the audience.

Shifts in the book industry have been a boon to writers who work quietly behind the scenes