The ability of generative AI tools to analyse huge datasets can also be used to help spark creative inspiration. This can help us if we’re struggling for time or battling writer’s block. For example, if a social media manager is looking for ideas on how to engage alumni on Instagram, they could ask ChatGPT for suggestions based on recent popular content. They could then pick the best ideas from ChatGPT’s response and adapt them. We may use these tools in a similar way to how we ask a colleague for an idea on how to approach a creative task.

We may use these tools in a similar way to how we use search engines for researching topics and will always carefully fact-check before publication.

we will not publish any press releases, articles, social media posts, blog posts, internal emails or other written content that is 100% produced by generative AI. We will always apply brand guidelines, fact-check responses, and re-write in our own words.

We may use these tools to make minor changes to a photo to make it more usable without changing the subject matter or original essence. For example, if a website manager needs a photo in a landscape ratio but only has one in a portrait ratio, they could use Photoshop’s inbuilt AI tools to extend the background of the photo to create an image with the correct dimensions for the website.

Forget trying to decide what your life’s destiny is. That’s too grand. Instead, just figure out what you should do in the next 2 years.

Visuals can stir up feelings or paint a scene in an instant. However, they may not always nail down the details or explain things as clearly as words can. Words can be very precise and give you all the information you need. Yet, sometimes they miss that instant impact or emotional punch.

For each visual you add to your presentation, you should ask yourself “What does it really say?” And then check: Does it enhance the meaning of my message, or is it purely decorative? Does it belong at this point in my presentation? Would it be better for another slide? Is there a better image that says what I want to say?

Computers don’t feel, and that means: they don’t understand what they do, they grow images like cancer grows cells: They just replicate something into the blue. This becomes apparent in the often outright creepiness of AI images.

AI is really good at making scary images. Even if the prompt lacks all hints of horror kitsch, you need to get ready to see or feel something disturbing when you look at AI images. It’s like a spell. Part of the scariness comes from the cancer-like pattern that reproduces the same ornament without considering its meaning and consequence.

Placing pictures next to each other will invite comparisons. We also compare images that follow each other. Make sure that you do not inadvertently compare apples and oranges.

When placing multiple images in a grid or on one slide after the other, ensure they don’t clash in terms of colors, style, or resolution. Otherwise, people will focus more on the contrast between the images rather than their content.

Repeating what everyone can see is bad practice. To make pictures and text work, they need to have something to say about each other.

Don’t write next to the image what people already see. A caption is not an ALT text.

The most powerful combination of text and image happens when the text says about the image what you can’t see at first sight, and when the image renders what is hard to imagine.

Do not be boring or overly explanatory. The visual should attract their attention to your words and vice-versa.

If a visual lacks meaning, it becomes a decorative placeholder. It can dilute your message, distract from what you want to say, and even express disrespect to your audience.

The Learn In Public movement has encouraged thousands of people to write, speak, draw, or otherwise pick up what mentors put down, with the end goal of lifelong L(N*P) growth in personal knowledge and network. A key part of this strategy is maintaining your own Digital Garden. A Digital Garden is your very own place (often a blog, or twitter account) to plant incomplete thoughts and disorganized notes in public - the idea being that these are evergreen things that grow as your learning does, warmed by constant attention and fueled by the unambiguous daylight of peer review. It is in part a trick for creators to play on themselves: For perfectionists who stress over shipping anything less-than-polished and therefore never ship anything, it is a license to trade off self review for peer review and increased velocity. Many report both improved quality and quantity of output after giving themselves the permission to do this.

People with audiences do of course have some obligation to not do them a disservice, else they don’t deserve that audience. However this doesn’t mean that they must do exhaustive due diligence and be authoritative in every context - there needs to be space to experiment, grow, and quite frankly, be ignorant and wrong.

I will “steelman” arguments - the opposite of “strawman arguments” - instead of picking on the weakest piece of their argument, I will confront head on their best argument by seeking first to understand before trying to be understood.

This is also a very good reason to avoid viewport units, like vw or vh, when setting font size. Those are also static, and impossible to override by the user. At most, a value like calc(1rem + 1vw) might be acceptable, since that still contains rem as a base. Even then, however, I’d recommend using clamp() or media queries to set minimum and maximum values, as screen sizes often go far beyond what we might expect or test.

To differentiate between the two: 1rem is always equal to the browser’s font size—or, more accurately the font size of the html element. rem stands for “root em,” and the root of a webpage is the <html> tag. So, 1rem = whatever the document font size is. (Which, again, by default, is 16px, but can be overridden by the user.) em, on the other hand, is the font size of the current element.

1px is equal to whatever the browser is treating as a single pixel (even if it’s not literally a pixel on the hardware screen).