AI is taking your job

… but not how you think

Someone I know was hiring for a position and received a flood of applications. They had one remote interview with a person who was clearly using ChatGPT to answer questions and they shut down the interview immediately. A few days later they joined a call for another interview for the same position and it was the same person as before, under a completely different name with a completely different resume.

This person had submitted multiple AI-generated resumes to the job posting 🤦‍♂️

Applying for a job now often means competing against a flood of AI-generated resumes and hoping your application makes it past automated filters. And on the flip side, hiring managers face the Herculean task of finding real candidates among piles of AI-crafted applications. And they’re increasingly using AI to do this 😬

That’s the kind of competition we’re dealing with. And yet, a personal connection—a real conversation—cuts through all of that.

Digital interactions dominate our lives, but I’m constantly reminded of the unique power of in-person connections. Every job I’ve had since graduating from BYU came through personal relationships—either someone recommending me or me knowing the right person at the right time. These connections aren’t just helpful; they’ve been game-changers in my career.

Why In-Person Connections Matter More Than Ever

When I landed a job at PayPal, it wasn’t because I aced some online application or had a perfect LinkedIn profile. It was because of a relationship I’d built with someone at a conference. I wasn’t even looking to move to California, but that connection opened the door to a rare remote position at the company.

Fast-forward to today: post-COVID and in the era of AI, these human connections are even more critical.

Sure, you can build relationships online. You can contribute to open-source projects, network through mutual connections, or attend virtual meetups. I’ve done all of these things and they definitely help. Keep doing it. But nothing beats sitting down with someone, looking them in the eye, and sharing a handshake or a laugh.

There are people I know online that I don’t vibe with. Every single time when I meet them in-person that relationship gets better (even if I still don’t really vibe with them after the fact).

It’s one of the reasons I’m so passionate about attending and organizing conferences and meetups. I’ve seen it over and over again: people come for the talks, but they leave with new friends, collaborators, mentors, and sometimes jobs (maybe not today, but definitely in the future).

What We’re Doing at Epic Web Conf and Camp

At Epic Web Conf 2024 (and previously at Remix Conf), we structured the schedule to maximize those moments of connection. Single track, extended breaks, long lunches, and fun activities were all deliberate choices. The talks inspire and teach, but the real value comes from the conversations in the hallways, over drinks, or during a group activity.

Epic Web Camp takes that even further. Imagine 30 people spending a few days together in the Utah mountains, with hotel-style accommodations, outdoor adventures, and plenty of downtime to chat. Last year, we did speed networking, high ropes courses, and impromptu talks. Next year, we’re making it even better—more time to relax, connect, and build meaningful relationships with more people.

The Human Advantage Over AI

Here’s the thing: AI can automate a lot of things, but it can’t replicate human relationships. When you meet someone in person—even just once—it strengthens every future interaction you’ll have with them, online or otherwise. Those connections lead to better work, new ideas, and a richer life.

If you’re looking for ways to build these kinds of relationships, I’d love for you to join us at Epic Web Conf in March 2025 or Epic Web Camp in September 2025. Tickets for the conference are available now, and camp tickets will open later in the year.

The world is becoming more digital by the day, but that only makes our human connections more valuable. Let’s make them count. I can’t wait to meet you.

Building a Stripe App: A Step-by-Step Guide to QR Code Generation

Why Build a Stripe App?

I recently participated in an audio space with the Stripe team, and something they said really stuck with me: the Stripe app store is a growing area that isn’t overly saturated yet. There’s a lot of potential for new apps, and companies can use this opportunity to grow.

I work at a company called This Dot Labs, and we’ve created several Stripe apps and even own one. After looking at the data, I can confirm that the Stripe team was right!

Creating a QR Code Generator App

For this tutorial, we’ll build a QR code app that can take a URL and generate a code for it. This is a good use case to help you understand the ins and outs of Stripe’s developer tools.

Why QR Codes?

QR codes are useful tools that have become common in e-commerce, restaurants, and other industries. While Stripe already has a QR code tool, we’ll make our own to familiarize ourselves with their syntax and problem-solving approaches.

Project Structure

Before we dive into the implementation, let’s look at the structure of our Stripe App QR Code project:

• .vscode: Contains settings for Visual Studio Code
• source/views: Holds the main application views
• .gitignore: Specifies files to ignore in version control
• stripe-app.json: Defines the Stripe app configuration
• ui-extensions.d.ts: TypeScript declaration file for UI extensions
• .build: this is where the built Stripe app gets placed.

Step-by-Step Implementation

###1. Install Stripe Locally First, you need to install Stripe on your local machine. The documentation provides great instructions for this:

• For Mac users: Use Brew to install
• For Windows users: Download the package and add it to your environment variables

You can find the details here in the stripe docs to install the Stripe CLI https://docs.stripe.com/stripe-cli

When using Windows, you must do stripe login from Powershell, NOT from Git bash or any other tool. After the server is up, then you can continue using git bash for everything else. After stripe login, you need to enter stripe apps start. Once you do that, the server is up and running and you can go back to using git bash or any other tool.

2. Install Dependencies

We’ll be using an extra package for QR code generation. Install it using npm:

npm install qrcode

3. Set Up the Main Component

Let’s look at the home.tsx file, where we’ll use Stripe’s UI components:

import { Box, ContextView, Button, TextField, Banner } from '@stripe/ui-extension-sdk/ui';

These components are similar to other UI libraries like Bootstrap or Tailwind CSS.

4. Create the UI Structure

Our app will have:

• An input field for the URL
• Validation using a regex pattern
• Error handling for invalid URLs
• QR code generation and display

Here is the Home.tsx file that is located in the src/views folder

import { Box, ContextView, Button, TextField, Img, Banner } from '@stripe/ui-extension-sdk/ui';
import { useState } from 'react';
import QRCode from 'qrcode';
const Home = () => {
  const [url, setUrl] = useState('');
  const [qrCode, setQrCode] = useState('');
  const [error, setError] = useState('');
  const generateQRCode = async () => {
    try {
      if (!url) {
        setError('Please enter a URL.');
        return;
      }
      //basic regex pattern for URL validation
      const urlPattern = new RegExp(
        '^(https?:\\/\\/)?' +
          '((([a-z\\d]([a-z\\d-]*[a-z\\d])*)\\.)+[a-z]{2,}|' +
          '((\\d{1,3}\\.){3}\\d{1,3}))' +
          '(\\:\\d+)?(\\/[-a-z\\d%_.~+]*)*' +
          '(\\?[;&a-z\\d%_.~+=-]*)?' +
          '(\\#[-a-z\\d_]*)?',
        'i'
      );
      if (!urlPattern.test(url)) {
        setError('Please enter a valid URL (e.g., https://example.com)');
        return;
      }
      const qrCodeDataUrl = await QRCode.toDataURL(url, {
        width: 200,
        margin: 2,
      });
      setQrCode(qrCodeDataUrl);
      setError('');
    } catch (error) {
      console.error('Error generating QR code', error);
      setError('Failed to generate QR Code. Please try again.');
    }
  };
  return (
    <ContextView
      title="URL QR Code Generator"
      brandColor="#635bff"
      externalLink={{
        label: 'Stripe Docs',
        href: 'https://stripe.com/docs',
      }}
    >
      <Box css={{ stack: 'y', rowGap: 'large', padding: 'medium' }}>
        <Box css={{ font: 'heading', marginBottom: 'medium' }}>Generate User Payment QR Code</Box>
        <TextField
          label="Enter URL"
          placeholder="https://example.com"
          value={url}
          onChange={(e) => setUrl(e.target.value)}
          type="url"
        />
        {error && <Banner type="critical" title="Error" description={error} />}
        <Button type="primary" onPress={() => generateQRCode()} disabled={!url}>
          Generate QR Code
        </Button>
        {qrCode && (
          <Box
            css={{
              stack: 'y',
              rowGap: 'medium',
              alignSelfY: 'center',
              marginTop: 'large',
            }}
          >
            <Box css={{ font: 'heading' }}>Your QR Code</Box>
            <Img src={qrCode} alt="Generated QR Code" />
            <Button
              type="secondary"
              onPress={() => {
                window.open(qrCode, '_blank');
              }}
            >
              Download QR Code
            </Button>
          </Box>
        )}
      </Box>
    </ContextView>
  );
};
export default Home;

• ContextView is at the top level of the app where we see the Title and the link to the Stripe Docs that we placed in our Context View.
• Box is how you use Divs.
• Banners can be used to show notification errors or any other item you wish to display.
• Textfields are input fields.
• Everything else is pretty self-explanatory.

5. Handle Content Security Policy

One problem I personally ran into was when I tried to redirect users, the Stripe policies would block it since I did not express that I knew what it was doing. I had to go into the stripe-app.json file and mention the specific security policies. For this particular exercise, I kept these as null.

This is my stripe-app.json file.

{
  "id": "com.example.my-stripe-app",
  "version": "0.0.1",
  "name": "My Stripe App",
  "icon": "",
  "permissions": [],
  "stripe_api_access_type": "platform",
  "ui_extension": {
    "views": [
      {
        "viewport": "stripe.dashboard.home.overview",
        "component": "Home"
      },
      {
        "viewport": "stripe.dashboard.invoice.detail",
        "component": "Invoice"
      }
    ],
    "content_security_policy": {
      "connect-src": null,
      "image-src": null,
      "purpose": ""
    }
  }
}

6. Configure App Views

As you can see here, the stripe-app.json file shows the views for each file I have. The Home.tsx file and the Invoice.tsx are also included This is our way of saying that for each view we have, show the app functionality on that page. Our stripe-app.json file will show it but also, the manifest.js file in our .build folder will also show the same. Any view that doesn’t have a file will not show the application’s functionality. So, if I were to go to transactions, the app would not show the same logic as the home or invoices page.

By following these steps, you’ll have a fully functional QR code generator app for Stripe. This is just a simple example, but the potential for Stripe apps is massive, especially for businesses serving e-commerce customers.

If you need help or get stuck, don’t hesitate to reach out, danny.thompson@thisdot.co. The Stripe team is also very active in answering questions, so leverage them as a resource. Happy coding!

My Journey to Building Authority in QA

This was written with the help of AI using BlogRecorder.

This year has been a rollercoaster, to say the least. I’ve seen some incredible growth in my online presence, and I’ve learned some hard lessons along the way. I want to share my experiences with you, from expanding my social media following to launching digital products, and how I’m planning to revolutionize QA education.

The Growth of My Online Presence

I’ve managed to grow my LinkedIn account from 600 to 5000 followers and my Twitter from around 100 to over 800 followers. My email list has also seen a significant increase, going from about 30 readers to over 450. On top of that, I’ve made over $450 from digital products and services designed to help those in QA with their job hunt or to learn valuable career skills.

Learning from a Failed High Ticket Offer

Back in July, I invested in some high ticket offer coaching to pitch my first high ticket offer to my readership. I introduced a “job hunt wingman” service for QA professionals, priced at $1,000 a month. Unfortunately, it didn’t take off as I had hoped. The price was steep, and without social proof of my success in helping others, it was a tough sell. I’ve realized that I should have started by helping someone at a low cost or even for free to build that proof and trust.

Gaining Valuable Skills and Refocusing

Despite the setback, I’ve gained invaluable skills that I’ll carry with me into the future. I’ve also taken a step back to reassess my approach. I realized that my technical portfolio and online presence didn’t reflect my current abilities or the value I could offer. It was time for a change.

My Three-Pronged Strategy

On July 28th, I made a decision and shared it on Twitter. For the rest of 2024, I would focus on three main areas:

1. Launching a Personal Website: a personal website that I could be proud of, using a template to avoid the hassle of designing it myself.
2. Updating My Personal Projects: work on projects that showcase my current level of skill and display them on my website, along with my contributions to the QA community like my newsletter, interviews, open-source contributions, etc.
3. Creating a New Course: I’m developing a course to teach QA automation, including how to be hirable forever, leveraging content creation, and using AI tools like Cursor.

A New Approach to QA Education

When I say “create a course,” I’m not just creating a typical course; I’m building a learning experience that goes beyond the norm.

It’ll be different than any course the QA industry has seen before, leveraging my unique blend of tech & business experiences.

This will be a hybrid education model, not entirely self-paced, with human feedback on student work. I want to provide a support system through DMs and video calls, and foster a learning community where students can collaborate and support each other.

The Social QA Boot Camp

Launching on Black Friday this year, the course will be priced affordably, with an option for weekly check-ins at a higher price. I’m focused on making the course content-rich yet concise, with audio alternatives for lesson texts. I’ve already enrolled beta testers who are providing feedback to ensure the course is user-friendly and effective.

Ensuring Quality and Building Authority

I’m committed to reviewing student work personally, to ensure they leave the course with high-quality projects and content. This course is my way of building authority in the QA education space and providing social proof for my business.

The Future of QA: An Evergreen Skillset

I believe that to remain competitive, QA professionals must become more social and contribute to their community. That’s why I’m passionate about teaching not just technical skills but also communication, marketing, and sales skills. My goal is to help every QA become evergreen professionals, equipped to stand out in a saturated market.

Conclusion

I’m excited to launch this course and make a real impact on those who join. It’s not just about QA; it’s about how to be a QA that remains hirable for the foreseeable future.

Stay tuned for the Social QA Bootcamp, where we’ll redefine what it means to be a QA professional in today’s market.

Get on the course waitlist

https://chasingquality.ck.page/social-qa-waitlist

Embracing Slow Networks: Improving User Experience

Recently, Noah Falk on X shared a video that sparked a conversation about why your application needs client-side JavaScript:

He demonstrated the Hey calendar app’s performance on a slow network, revealing a significant delay when adding a new event—a delay caused by the app’s reliance on server communication to display the contents of a popover.

The Reality of High Latency

The truth is, not everyone has the luxury of a fast internet connection. As developers, we can’t control the network conditions our users will face. That’s why it’s crucial to consider how our applications perform under high latency (especially for productivity apps like a calendar). Some may dismiss these concerns, assuming that everyone has access to high-speed internet, but that’s simply not the case. We must acknowledge that poor user experiences do occur and that they matter.

I’ve experienced this frustration firsthand with the Hey email service. Despite my initial interest, the sluggish response due to Hotwire’s architecture led me to stop using it. This isn’t to shame the technology or its supporters but to emphasize the importance of continuously striving to improve user experience.

React Server Components: A Game Changer?

The discussion naturally leads to React server components (RSCs) and whether they fall into the same trap as Hotwire, requiring server interaction for UI updates. While RSCs do involve server communication, they offer a unique advantage with the use client directive. This allows developers to seamlessly transition a component from server-driven to client-interactive without a complete overhaul.

With Hotwire, improving a feature like the Hey calendar popover would mean a significant shift to JavaScript, moving templates, and potentially re-architecting the feature. On the other hand, RSCs enable a more straightforward approach. By simply adding use client at the top of a file, you can introduce state and client-side reactivity without the need to juggle between Ruby and JavaScript code.

Embracing Innovation and Honesty in Technology

As we evaluate the technologies we use, it’s essential to do so with honesty and a focus on enhancing user experience. Personal attacks have no place in this process. Instead, we should celebrate the advancements in our field and the different approaches to application development.

React Server Components are exciting because they allow developers to easily toggle between server and client-side rendering. This flexibility doesn’t require a shift in your mental model or coding approach. It’s this simplicity and adaptability that make RSCs a valuable tool in the web developer’s arsenal.

Conclusion

In the end, it’s all about creating the best possible experience for users, regardless of their internet speed. Innovations like React Server Components are pushing the boundaries of what’s possible, enabling us to build applications that are both robust and responsive. As we continue to explore these technologies, let’s keep the user at the forefront of our minds, ensuring that everyone can enjoy a seamless and engaging online experience.

Generative AI vs LLMs: Key differences explained

Generative AI encompasses various forms of creative AI, including text, images, and music, while LLMs specifically focus on language, meaning all LLMs are generative AI, but not all generative AI is classified as LLMs.

Imagine this: You’re scrolling through reddit, reading posts on X (aka Twitter), or talking to your coworkers, and words like “Generative AI,” “LLM,” and “machine learning” keep coming up.

You nod along, but deep down, you might be wondering, _What do these words actually mean? And why does everyone seem so excited—or nervous—about them?

_If you’ve ever felt this way, you’re definitely not alone (I know I’ve been there 😅). In the last few years, AI has become a hugely popular topic (especially on social media).

As a result, many people seem to be throwing around these “AI words” as if they all mean the same thing.

But what do these terms really mean, and how are they connected? Let’s start with the basics.

What Is generative AI?

You can think of Generative AI (GenAI) as an umbrella term. It’s all about creating something new—hence the “generative” in its name.

Whether it’s images, music, text, or code, GenAI tools are designed to take what they’ve learned and generate original content.

This means they’re not just copying what they’ve seen—they’re creating something entirely new that’s based on the prompt you provide (which is why learning a bit about prompt engineering can really help you get the results you want! 😉).

Here are a few examples of GenAI tools you might recognize:

• DALL-E and Midjourney are both great tools for generating images! In the past, I’ve used both to generate images for websites I was working on and for social media banners and posts. For example, my banner on X was generated by MidJourney! (but personally I think DALL-E is the easiest to use when it comes to writing prompts, so that’s what I use now).

• SoundRaw is a nice choice for creating royalty-free background music for shorts or videos. I don’t have the best ear for music, but even I can use this tool to make something that sounds decent!
• ChatGPT and Claude are excellent for writing and editing text. Basically anything “important” that I write nowadays, I’ll send over to Claude for some feedback. Unfortunately, Claude has some pretty strict rate limits. You can only send about 40 messages per day on the free tier unless you subscribe to a paid plan. That’s why I’d rather just access Claude through Pieces!
• Grok is amazing when it comes to generating images, especially images based on your X profile! Recently there have been all kinds of trends like “Draw me as an anime character”, “Generate what you think my room looks like based on my X profile”, or “Generate me as a Lego character”.

Here’s how Pieces looks as a Lego:

If you end up generating an image based on your X profile, we’d love to see it! Just tag us @getpieces

But how does GenAI actually create (or generate) these things? 🤔

To put it simply, it’s trained on massive amounts of data to recognize patterns found in that data. Once it learns those patterns, it can then generate similar (but unique) outputs.

Now that we’ve covered GenAI, let’s talk about LLMs (Large Language Models).

How does an LLM even work?

LLMs are a specific type of generative AI that focuses on text. They’re trained on datasets that usually include books, articles, and code (although the type of data really depends on the purpose of the LLM).

Once trained, they can use what they’ve learned to respond to prompts in a way that feels almost.. kinda sorta.. Human.

Here are a few LLMs you might’ve heard of:

• GPT (Generative Pre-trained Transformer): Great for help with coding, writing docs, and brainstorming ideas, some examples are ChatGPT 4, ChatGPT 4o (my personal favorite in the ChatGPT family), and most recently ChatGPT o1.
• LLaMA (Large Language Model Meta AI): Built for research, some examples are Llama 2 7B and Llama 3 8B (which are both local models that you can access through Pieces). One thing that’s cool about these local models, is that you can use them even when you’re not connected to wifi!
• Claude: Known for long-form writing and creative tasks. Claude 3.5 Sonnet probably is my favorite LLM just because of the way it writes compared to other LLMs.

Since LLMs are focused on language-based data and tasks, it makes them ideal for anything text-related (think editing articles, code generation, content creation, language learning, etc.).

Fun fact: Pieces for Developers gives you access to 25 distinct LLMs 🤯.

Don’t like the output one LLM gives you? Just switch to another (you can even switch mid-conversation!).

With Pieces, you’re able to easily move between models like ChatGPT, Claude, and Gemini until you find the response that works best for you.

What are the limitations of GenAI & LLMs?

While GenAI and LLMs can be super useful, they’re not perfect.

They rely on the data they’re trained on, so if that data has biases or incorrect/outdated information, it can affect their output (or the responses you get back).

Another problem is that If you ask them a hard question or just a question that they’re unsure about, they might not admit they don’t know and could just make up an answer instead. This can be especially annoying when you are trying to learn something new and end up going down the wrong path due to these “hallucinations”.

What’s the difference between generative AI vs large language models?

Now we know a bit about GenAI and LLMs, but what’s the real difference?

Generative AI is the umbrella term covering everything from text generation to images, music, and more. LLMs are a specific part of GenAI focused on creating and understanding language.

Here’s a simple way to think about it: LLMs are generative AI, but generative AI is not always an LLM. Generative AI is the broad category for any AI that creates something new, while LLMs are a type of generative AI focused specifically on text.

That’s why earlier in the article we mentioned ChatGPT and Claude in both the GenAI and LLM sections. ChatGPT is both Generative AI and an LLM. On the other hand, DALL-E, which is used for image generation, is Generative AI but not an LLM.

What is the hierarchy of artificial intelligence?

Now that we understand a bit about Generative AI and LLMs, how do they fit into the bigger picture of “AI” as a whole?

To make sense of it, think of AI as a set of layers (like an onion!), each getting more specific as you get deeper.

The image above breaks it down like this:

Artificial Intelligence (AI)

This is the broadest category and includes anything that mimics human intelligence. This could include conversational AI (ChatGPT), Image generation (DALL-E), the AI that powers self-driving cars, and so much more! This is where it all starts.

Machine Learning (ML)

An essential part of AI that helps systems learn from data and get better over time. The more data the system processes, the more accurate its predictions and decisions become.

Deep Learning (DL)

A type of Machine Learning that uses neural networks to recognize patterns and handle complex tasks.

Generative AI (GenAI)

Built on Deep Learning, this is where AI starts creating new things, like images, music, text, and code.

LLMs (Large Language Models)

A specific type of Generative AI focused on language. LLMs power tools like ChatGPT, Claude, and Pieces!

Integrating generative AI and LLMs in your workflow

If you’ve made it this far, you’re well on your way to understanding AI (congrats!). But you might be thinking, how can I actually use AI in my work or daily life? 🤔

Here are some practical ways to get started:

Create engaging content

• Tools like ChatGPT or Claude help you come up with ideas, draft blog posts, and create outlines quickly.
• If you enjoy writing your articles/notes in Obsidian, the Pieces Obsidian plugin is super useful. Its long-term memory engine keeps your workflow context accessible, while Pieces copilot is there to answer any questions as you write.

Leverage developer tools

• Use code generation tools to save code snippets and generate code directly in tools like VS Code, Chrome, or Obsidian.
• Combine Pieces with GitHub Copilot—GitHub Copilot autocompletes your code while Pieces has access to all of your workflow context to answer any questions that you might have.

Generate unique images

• Tools like DALL-E, Midjourney, or Grok let you create custom images for presentations or social media.
• If the AI-generated graphics aren’t perfect (it is pretty difficult to get them exactly the way you want them to look), you can use Canva to edit them (they even have some AI-powered editing tools available now).

Build interactive chatbots

• Chatbots can act as your coding assistant, answer questions about your portfolio, act as a virtual therapist or astrologer, or even help diagnose medical issues (which is probably a terrible idea!).
• You can integrate chatbots into your coding projects using APIs like OpenAI’s API (for models like ChatGPT) or Anthropic’s Claude API. Or, you can use one of our SDKs to call your preferred LLM through Pieces OS—for free.

Hopefully, now you have some ideas on how you can integrate AI into your workflow! Honestly, whatever you need “AI help” with, there’s probably something out there for you (if not, then you could even build it yourself).

That said, GenAI and LLMs have quite literally changed everything. And not just for developers.

People who in the past could barely draw stick figures are now creating amazingly detailed works of art (If you don’t believe me take a look at Midjourney’s Explore page).

And those who never thought they’d try coding are now building their own simple websites and games.

These are just a few examples. GenAI and LLMs are making it easier than ever for anyone to create, code, and bring their ideas to life. The tools are here – what will you do with them?

Quitting caffeine

The Decision to Quit

Eight months ago, I made a significant decision: I quit caffeine. It wasn’t easy, as caffeine had been a part of my life for as long as I could remember. My use varied, increasing during stress and decreasing when I tried to cut back. At times, it reached excessive levels. I disliked the anxiety and confusion that caffeine caused. Caffeine let me work with intensity. But I often found I hadn’t accomplished much.

I had attempted to quit before, but it was challenging. I’d abstain for a few months, then return when motivation lagged.

This time has been different. I find myself in a better position to live the life I desire. It’s hard to credit changes to quitting caffeine with so many other things changing in my life. Still, if my performance stays the same or improves, it’s proof I can manage without it. Let’s explore how quitting caffeine has affected various aspects of my life.

Sleep Quality and Quantity

Sleep Duration

After quitting, my sleep increased. I’d sleep 12 hours daily, with regular naps. This initial period of increased sleep helped me feel more balanced and restored.

Now, I average seven hours of sleep per night, even with the chance to sleep longer. I suspect that, with better sleep hygiene, I could sleep for more than eight hours and feel even more refreshed.

Sleep Disturbances

Some believe that recovering from caffeine dependence only takes a few weeks. Yet, the sleep disturbances I’ve had argue otherwise. For at least two periods during this process, I’ll wake up in the middle of the night, unable to fall back asleep. This problem occurs less often, now happening only a few times a month.

Increased Dream Vividness

Caffeine suppresses REM sleep. Since quitting, I’ve noticed more vivid dreams. Dreaming helps to process thoughts, giving me clarity when I’m awake.

Energy and Motivation

Morning Energy Levels

In my caffeine-consuming days, I’d often wake up energized, even before my first drink. I suspect it was due to the ever-present caffeine in my system or the anticipation of my first drink of the day.

Now, I wake up refreshed on most mornings. But sometimes there’s a tiredness that is hard to shake. A bit more sleep resolves this, when I can get away with it. Otherwise, I move forward with my daily routine and soon feel fine. Either way, my morning energy is more calm, which is perfect for most of what I need to focus on anyways.

Consistent Energy Throughout the Day

Maintaining optimal energy levels to live my best life is a top priority for me. Yet I was so tired of caffeine’s artificial energy that I didn’t care how much energy I lost. The good news is that my energy is not only better than ever, but also consistent throughout the day.

Improved Focus and Flow

While on caffeine, I associated feeling wired with productivity. If I didn’t feel like I was a rocket taking off, I believed I needed more caffeine or a nap. In the first few months after quitting, I had to retrain myself. I had to stop confusing that feeling with motivation.

I’m pleased to report that my energy and focus are now at their best without caffeine. The right task can put me in a flow state, immersing me in my work and making it hard to disengage. I rarely had this experience with caffeine, but it has become more common since quitting.

However, caffeine can make boring tasks seem interesting. This can help make a tedious life tolerable, which can be a trap.

Mental Clarity and Life Choices

Evaluating Priorities

As expected, my motivation bottomed out when I quit caffeine. Fortunately, I timed this to happen around Christmas, making it more manageable. As I began to recover, I saw that caffeine-fueled zeal had driven some parts of my life. After removing the caffeine, the excitement disappeared. This realization highlighted the potential dangers of relying on caffeine for artificial motivation.

Quitting caffeine may lead to one of the most significant changes in my life. It has allowed me to see what excited me and what didn’t, enabling me to choose the life I want to build.

Increased Calm

I now feel a calm, steady energy without caffeine. I am less reactive to small annoyances, which is a big benefit.

Caffeine’s anxiety-inducing effect has played a major role in this progress. A key change is the removal of nervous energy, the kind that makes people over-apologize. I suspect caffeine-related anxiety is a big, unrecognized problem. Many could reduce their anxiety by cutting back on caffeine.

It’s convenient that society normalizes caffeine. Not only does it make work seem more engaging, but it also prevents you from noticing that the work is boring.

Challenges with Exercise

Exercise is the primary area where I can’t tell if life without caffeine is better. Since quitting, my workouts have been less consistent and intense.

It’s challenging to disentangle these issues from other ongoing life changes. I perform best when I exercise in the morning, but that is also when I’m most productive in my work. I’m in a critical transition in my life, so I’ve decided to use my mornings for work.

Since I’m less inclined to exercise later in the day, I’m more likely to skip working out altogether. I’m testing new ways to boost my motivation and will update you on my progress.

I’m unsure if I’ll ever regain the energy that caffeine once gave me for intense weightlifting. Time will tell if my potential is truly capped or if there’s a way to fix this.

Reduced Soda Consumption

I made the switch from regular Coke Zero to the caffeine-free version. The taste is the same. But, the urge to drink it is less without caffeine. This shows the reinforcing effects of caffeine in action.

Caffeine makes you pee more due to various physiological mechanisms. Combined with cutting my fluid intake, I’m making a lot fewer trips to the bathroom. Which is useful for focused productivity.

Conclusion

I realize speaking ill of caffeine is not going to be popular. Everyone’s different, and it might be right for you. It was valuable to hear the stories of colleagues who have quit over the years, so I’m sharing mine.

I’d love to hear about your personal experiences with caffeine.

See you next week.

Three Sectors Leading SPY Back to Offense

KEY TAKEAWAYS

• The market came out of defensive mode after the election.
• Old resistance at 585 is now support for SPY.
• XLC, XLY, and XLF are all showing strength.

First of all, for those of you looking for a new video this week, I have intentionally skipped it because I didn’t want to make a video right before such an important event with much uncertainty.

After the elections, which were obviously eventful, I wanted to see what the market’s reaction would be and let the dust settle down before diving into any analysis, which might have been too preoccupied and presumptuous too early.

However, it’s now Friday, the end of the week, and we have a little more color on how markets have responded to the election results. It’s time to see what the sector rotation is telling us and how the chart of the S&P 500 has changed—because it has definitely changed!

The S&P 500’s Post-Election Reversal

If you look at that chart right now with the annotations, which were the cornerstone of my view, I have to say that it was a little conservative going into the elections. This has now pretty much turned around. On the chart, a very clear island reversal is now visible.

We have the gap down on the 31st of October, followed by three more or less sideways days, which took SPY to a low of just around 567. On November 5th, election day, the market closed at the high, followed by a massive gap up the day after. It was not only a gap up but also a move above the S&P 500’s all-time highs.

So we have a massive gap up. We have an island reversal, which completed just above pretty important support around 565, and we now already have two days of good follow-through. That is a strong sign. This market wants to go higher, at least in the near term.

If we switch to the weekly chart for SPY, those mild divergences between the RSI and price and the MACD and price are still visible, but the price action itself is so strong that it cannot and should not be negated.

So, at least in the near term, this market wants to go higher. For now, corrections holding above support around 585 (the former peak) should be regarded as buying opportunities.

Reversals in Sector Rotation

On the relative rotation graph for the 11 S&P sectors above, I have intentionally set the tail length at six trading days. That means that each tail has seven nodes, and the 4th node, so the middle one, is November 5th. This allows us to see the 3 days leading up to election day and then the 3 days after election day. As you can see, most of the tails have continued to travel in the direction they were already heading.

The most prominent ones are consumer discretionary and communication services, which entered and moved further into the leading quadrant. On the other side is the utility sector, which accelerated further into the lagging quadrant.

Sectors with Notable Changes

I want to highlight a few sectors that really changed direction, where we saw a change in detail before and after election day. The two sectors with the most prominent changes are financials and health care.

This first RRG shows the tails for both sectors ending on the 5th of November.

Financials Sector (XLF)

If we zoom in on the tail for XLF, you can see that it ended November 5th just inside the weakening quadrant. It just crossed over from leading to weakening. Then, in the 3 days after November 5th, it completely reversed course and is now almost back into the leading quadrant.

Health Care Sector (XLV)

The same sort of move is visible on the other side of the chart for the healthcare sector, XLV. On November 5th, XLV had just crossed into the improving quadrant and was on a positive heading. In the 3 days after, the sector completely reversed course and is now back into the lagging quadrant at a negative heading.

XLP and XLRE Rolling Over

Other sectors where we see a change in the course of the tail include consumer staples, which was inside the improving quadrant but hooked back down, rolled over, and is now back into the lagging quadrant, and real estate, which was also inside the improving quadrant but rolled over and is now accelerating into the lagging quadrant.

The technology sector changed course a bit, but not as clearly as the other sectors. It is still right around the 100 level on the RS ratio scale and very close to the benchmark without a very clear direction.

The Big Winners Post-Election

I think the biggest winners from these election results with good potential going forward are consumer discretionary (XLY), and Communication Services (XLC).

XLY is obviously led by TSLA, which is distorting the performance of the consumer discretionary sector with an almost 27% gain in 3 days. But consumer discretionary stocks have picked up roughly between 3% and 7% across the board, which still indicates strength. The communication services sector is slightly more evenly spread out, and has a good base and a good foundation to move higher and push further into the leading quadrant.

Conclusion

All in all, the market as a whole seems to have reversed its course. After only a very mild corrective move, it has now started a new up leg in the existing uptrend. The sectors that have come out on top are consumer discretionary and communication services, followed by financials.

All 3 are on the right-hand side of the RRG, either already inside the leading quadrant or almost there, and traveling at a positive RRG heading. On the opposite side, the sectors with a less favorable outlook are health care, consumer staples, and utilities. Overall, the sector rotation has now shifted from defense back to offense.

#StayAlert, and have a great weekend. —Julius

---

Julius de Kempenaer
Senior Technical Analyst, StockCharts.com
Creator, Relative Rotation Graphs
Founder, RRG Research
Host of: Sector Spotlight

Please find my handles for social media channels under the Bio below.

Feedback, comments or questions are welcome at Juliusdk@stockcharts.com. I cannot promise to respond to each and every message, but I will certainly read them and, where reasonably possible, use the feedback and comments or answer questions.

To discuss RRG with me on S.C.A.N., tag me using the handle Julius_RRG.

Different Approaches to Visual Editing in Headless CMS

This article outlines the benefits and potential downsides of different ways to edit content visually. Headless CMSs are starting to add visual components, from side-by-side previews to WYSIWYG inline editing and a lot in between. Some pure players, like Builder.io and Uniform, decided to start visually and work their way back to CMS-like functionality.

Now that all marketing is identical, it’s really hard to choose. In this article, I will explain the different approaches to help you make an informed decision.

Beware, the market changes fast. The vendors mentioned in this article might have changed their offerings since writing this.

TL;DR? Take the questionnaire

This questionnaire will help to figure out what you need in terms of visual editing in your CMS. If you want to know how to all works, read the rest of the article below.

The Four Categories of Visual Editing in CMS

Regarding CMS, the editing experience can vary greatly depending on the platform and the user’s specific needs. Let’s dive into the different categories of CMS editing experiences, their pros and cons, and some examples of platforms that fit into each category.

Category 1: Visual Preview

In this category, the CMS form fields and the website are displayed side by side. You can see your website update in real-time as you fill out the form.

Notes:

• For instant updates: Requires a front-end SDK
• For updates on save: Common in CMSs with strict schema validation rules. Can be done without SDK
• Preview links: Some CMSs provide links to a specific build of the front end that queries the draft API, opening in a new tab

Pros:

• Ideal for editing domain data
• Similar to traditional CMS editing but with a potentially better view of the content being edited

Cons:

• Can be pretty abstract
• Editing is not visually driven

Vendor examples: Hygraph, Directus, Amplience, Strapi, Contentstack

Category 2: Contextual Live Editing

This category allows you to click on an element on your site, triggering a sidebar with a CMS form for editing. Sometimes, this redirects you to your CMS interface in a new tab.

Notes:

• Requirements: A front-end SDK, Vercel’s Stega data, or HTML annotations

Pros:

• Clicking on an element in the preview website opens the corresponding CMS form for editing
• A significant improvement over side-by-side previews

Cons:

• Feels like a WYSIWYG, but isn’t
• Developers may need to put in extra effort to implement design-like features

Vendor examples: Sanity, Storyblok, kontent.ai

Category 3: Almost WYSIWYG

This category offers block-based visual editing, providing a more structured, pattern-like approach. It is based on a design system.

Notes:

• Requirements: A front-end SDK
• Additional Features: Some platforms offer external API data managing, mapping, and editing. Also seen are personalization and sitemap management

Pros:

• Native features for WYSIWYG-style editing with guardrails to stay within the design system specifications

Cons:

• Some vendors have complex setups
• Others are easier to implement but require a bigger buy-in as they handle external data ingestion and mapping

Vendor examples: Uniform, Contentful Studio, Sitecore XM, builder.io, Plasmic, Netlify Create

Category 4: Full WYSIWYG

In this category, you design like a designer, and a website is created. All CSS properties, animations, and other design elements are available.

Notes:

• The platform controls your codebase and hosting

Pros:

• Easy to get started; anyone can design something

Cons:

• Hard to scale
• A mix of design data vs. domain data
• Content not reusable
• Code and hosting are provided by the platform

Vendor examples: Wix, Weweb, Webflow, Squarespace

Understanding Domain vs Design Content

Let’s discuss the difference between domain content and design content and why it is so important in choosing visual editing vendors.

Domain Content

Definition: Domain content refers to structured, clean, and semantic data that defines the core information and properties of a specific domain (e.g., products, users, articles) without concern for its presentation. Domain content sits at the brand’s core and can be reused in many different contexts.

Characteristics:

• Strict data-focused schema definitions (no fields for presentation features)
• Focuses on the “what” (content and information)
• Reusable across different channels and platforms
• Maintains longevity and integrity over time

Real-world Example: You don’t expect payment providers to have data about credit cards that explain how big the logo of a certain credit card is shown on a user’s checkout screen. That’s the job of the designer and the front-end implementation.

Design Content

Definition: Design content refers to the specific instructions, order, and styles for presenting domain data in a front-end application.

Characteristics:

• Focuses on the “how” (visual representation and styling)
• Tends to be more volatile and subject to frequent changes
• Tightly coupled with the current design and presentation logic

Real-world Example: A banner component with an image, a title, and a description might look different in different contexts. Selecting which banner variant you want to show is design content; the content itself comes from a CMS and is domain content.

Making the Right Choice

The less you mess with domain-specific content, the more reusable it is and the longer it lasts. If you start mixing your domain content with design content, you will be working yourself into a corner regarding data flexibility and governance down the line.

However, focusing too much on the strictness of using only domain content will make it infinitely more complex for content editors who need to build a website with that content. Mixing domain content with design content could be your best bet to make everyone happy. Proper governance is a must here.

Conclusion: It Depends

Different categories offer different benefits and drawbacks based on your company’s approach to data management, your need for ever-changing pages, and your technical abilities.

There are factors other than how you want to manage your content, like how much complexity you want in your front-end channels (websites, apps, kiosks, etc). Some pure players like Uniform pride themselves on the saying: “more clicks, less code,” and they store a lot on the platform. Others, like Netlify Create, focus on code first and do not own any of your brands’ data.

The key is finding the right balance for your specific needs and use cases.

AI is taking your job

… but not how you think

Someone I know was hiring for a position and received a flood of applications. They had one remote interview with a person who was clearly using ChatGPT to answer questions and they shut down the interview immediately. A few days later they joined a call for another interview for the same position and it was the same person as before, under a completely different name with a completely different resume.

This person had submitted multiple AI-generated resumes to the job posting 🤦‍♂️

Applying for a job now often means competing against a flood of AI-generated resumes and hoping your application makes it past automated filters. And on the flip side, hiring managers face the Herculean task of finding real candidates among piles of AI-crafted applications. And they’re increasingly using AI to do this 😬

That’s the kind of competition we’re dealing with. And yet, a personal connection—a real conversation—cuts through all of that.

Digital interactions dominate our lives, but I’m constantly reminded of the unique power of in-person connections. Every job I’ve had since graduating from BYU came through personal relationships—either someone recommending me or me knowing the right person at the right time. These connections aren’t just helpful; they’ve been game-changers in my career.

Why In-Person Connections Matter More Than Ever

When I landed a job at PayPal, it wasn’t because I aced some online application or had a perfect LinkedIn profile. It was because of a relationship I’d built with someone at a conference. I wasn’t even looking to move to California, but that connection opened the door to a rare remote position at the company.

Fast-forward to today: post-COVID and in the era of AI, these human connections are even more critical.

Sure, you can build relationships online. You can contribute to open-source projects, network through mutual connections, or attend virtual meetups. I’ve done all of these things and they definitely help. Keep doing it. But nothing beats sitting down with someone, looking them in the eye, and sharing a handshake or a laugh.

There are people I know online that I don’t vibe with. Every single time when I meet them in-person that relationship gets better (even if I still don’t really vibe with them after the fact).

It’s one of the reasons I’m so passionate about attending and organizing conferences and meetups. I’ve seen it over and over again: people come for the talks, but they leave with new friends, collaborators, mentors, and sometimes jobs (maybe not today, but definitely in the future).

What We’re Doing at Epic Web Conf and Camp

At Epic Web Conf 2024 (and previously at Remix Conf), we structured the schedule to maximize those moments of connection. Single track, extended breaks, long lunches, and fun activities were all deliberate choices. The talks inspire and teach, but the real value comes from the conversations in the hallways, over drinks, or during a group activity.

Epic Web Camp takes that even further. Imagine 30 people spending a few days together in the Utah mountains, with hotel-style accommodations, outdoor adventures, and plenty of downtime to chat. Last year, we did speed networking, high ropes courses, and impromptu talks. Next year, we’re making it even better—more time to relax, connect, and build meaningful relationships with more people.

The Human Advantage Over AI

Here’s the thing: AI can automate a lot of things, but it can’t replicate human relationships. When you meet someone in person—even just once—it strengthens every future interaction you’ll have with them, online or otherwise. Those connections lead to better work, new ideas, and a richer life.

If you’re looking for ways to build these kinds of relationships, I’d love for you to join us at Epic Web Conf in March 2025 or Epic Web Camp in September 2025. Tickets for the conference are available now, and camp tickets will open later in the year.

The world is becoming more digital by the day, but that only makes our human connections more valuable. Let’s make them count. I can’t wait to meet you.

Building a Stripe App: A Step-by-Step Guide to QR Code Generation

Why Build a Stripe App?

I recently participated in an audio space with the Stripe team, and something they said really stuck with me: the Stripe app store is a growing area that isn’t overly saturated yet. There’s a lot of potential for new apps, and companies can use this opportunity to grow.

I work at a company called This Dot Labs, and we’ve created several Stripe apps and even own one. After looking at the data, I can confirm that the Stripe team was right!

Creating a QR Code Generator App

For this tutorial, we’ll build a QR code app that can take a URL and generate a code for it. This is a good use case to help you understand the ins and outs of Stripe’s developer tools.

Why QR Codes?

QR codes are useful tools that have become common in e-commerce, restaurants, and other industries. While Stripe already has a QR code tool, we’ll make our own to familiarize ourselves with their syntax and problem-solving approaches.

Project Structure

Before we dive into the implementation, let’s look at the structure of our Stripe App QR Code project:

• .vscode: Contains settings for Visual Studio Code
• source/views: Holds the main application views
• .gitignore: Specifies files to ignore in version control
• stripe-app.json: Defines the Stripe app configuration
• ui-extensions.d.ts: TypeScript declaration file for UI extensions
• .build: this is where the built Stripe app gets placed.

Step-by-Step Implementation

###1. Install Stripe Locally First, you need to install Stripe on your local machine. The documentation provides great instructions for this:

• For Mac users: Use Brew to install
• For Windows users: Download the package and add it to your environment variables

You can find the details here in the stripe docs to install the Stripe CLI https://docs.stripe.com/stripe-cli

When using Windows, you must do stripe login from Powershell, NOT from Git bash or any other tool. After the server is up, then you can continue using git bash for everything else. After stripe login, you need to enter stripe apps start. Once you do that, the server is up and running and you can go back to using git bash or any other tool.

2. Install Dependencies

We’ll be using an extra package for QR code generation. Install it using npm:

npm install qrcode

3. Set Up the Main Component

Let’s look at the home.tsx file, where we’ll use Stripe’s UI components:

import { Box, ContextView, Button, TextField, Banner } from '@stripe/ui-extension-sdk/ui';

These components are similar to other UI libraries like Bootstrap or Tailwind CSS.

4. Create the UI Structure

Our app will have:

• An input field for the URL
• Validation using a regex pattern
• Error handling for invalid URLs
• QR code generation and display

Here is the Home.tsx file that is located in the src/views folder

import { Box, ContextView, Button, TextField, Img, Banner } from '@stripe/ui-extension-sdk/ui';
import { useState } from 'react';
import QRCode from 'qrcode';
const Home = () => {
  const [url, setUrl] = useState('');
  const [qrCode, setQrCode] = useState('');
  const [error, setError] = useState('');
  const generateQRCode = async () => {
    try {
      if (!url) {
        setError('Please enter a URL.');
        return;
      }
      //basic regex pattern for URL validation
      const urlPattern = new RegExp(
        '^(https?:\\/\\/)?' +
          '((([a-z\\d]([a-z\\d-]*[a-z\\d])*)\\.)+[a-z]{2,}|' +
          '((\\d{1,3}\\.){3}\\d{1,3}))' +
          '(\\:\\d+)?(\\/[-a-z\\d%_.~+]*)*' +
          '(\\?[;&a-z\\d%_.~+=-]*)?' +
          '(\\#[-a-z\\d_]*)?',
        'i'
      );
      if (!urlPattern.test(url)) {
        setError('Please enter a valid URL (e.g., https://example.com)');
        return;
      }
      const qrCodeDataUrl = await QRCode.toDataURL(url, {
        width: 200,
        margin: 2,
      });
      setQrCode(qrCodeDataUrl);
      setError('');
    } catch (error) {
      console.error('Error generating QR code', error);
      setError('Failed to generate QR Code. Please try again.');
    }
  };
  return (
    <ContextView
      title="URL QR Code Generator"
      brandColor="#635bff"
      externalLink={{
        label: 'Stripe Docs',
        href: 'https://stripe.com/docs',
      }}
    >
      <Box css={{ stack: 'y', rowGap: 'large', padding: 'medium' }}>
        <Box css={{ font: 'heading', marginBottom: 'medium' }}>Generate User Payment QR Code</Box>
        <TextField
          label="Enter URL"
          placeholder="https://example.com"
          value={url}
          onChange={(e) => setUrl(e.target.value)}
          type="url"
        />
        {error && <Banner type="critical" title="Error" description={error} />}
        <Button type="primary" onPress={() => generateQRCode()} disabled={!url}>
          Generate QR Code
        </Button>
        {qrCode && (
          <Box
            css={{
              stack: 'y',
              rowGap: 'medium',
              alignSelfY: 'center',
              marginTop: 'large',
            }}
          >
            <Box css={{ font: 'heading' }}>Your QR Code</Box>
            <Img src={qrCode} alt="Generated QR Code" />
            <Button
              type="secondary"
              onPress={() => {
                window.open(qrCode, '_blank');
              }}
            >
              Download QR Code
            </Button>
          </Box>
        )}
      </Box>
    </ContextView>
  );
};
export default Home;

• ContextView is at the top level of the app where we see the Title and the link to the Stripe Docs that we placed in our Context View.
• Box is how you use Divs.
• Banners can be used to show notification errors or any other item you wish to display.
• Textfields are input fields.
• Everything else is pretty self-explanatory.

5. Handle Content Security Policy

One problem I personally ran into was when I tried to redirect users, the Stripe policies would block it since I did not express that I knew what it was doing. I had to go into the stripe-app.json file and mention the specific security policies. For this particular exercise, I kept these as null.

This is my stripe-app.json file.

{
  "id": "com.example.my-stripe-app",
  "version": "0.0.1",
  "name": "My Stripe App",
  "icon": "",
  "permissions": [],
  "stripe_api_access_type": "platform",
  "ui_extension": {
    "views": [
      {
        "viewport": "stripe.dashboard.home.overview",
        "component": "Home"
      },
      {
        "viewport": "stripe.dashboard.invoice.detail",
        "component": "Invoice"
      }
    ],
    "content_security_policy": {
      "connect-src": null,
      "image-src": null,
      "purpose": ""
    }
  }
}

6. Configure App Views

As you can see here, the stripe-app.json file shows the views for each file I have. The Home.tsx file and the Invoice.tsx are also included This is our way of saying that for each view we have, show the app functionality on that page. Our stripe-app.json file will show it but also, the manifest.js file in our .build folder will also show the same. Any view that doesn’t have a file will not show the application’s functionality. So, if I were to go to transactions, the app would not show the same logic as the home or invoices page.

By following these steps, you’ll have a fully functional QR code generator app for Stripe. This is just a simple example, but the potential for Stripe apps is massive, especially for businesses serving e-commerce customers.

If you need help or get stuck, don’t hesitate to reach out, danny.thompson@thisdot.co. The Stripe team is also very active in answering questions, so leverage them as a resource. Happy coding!

My Journey to Building Authority in QA

This was written with the help of AI using BlogRecorder.

This year has been a rollercoaster, to say the least. I’ve seen some incredible growth in my online presence, and I’ve learned some hard lessons along the way. I want to share my experiences with you, from expanding my social media following to launching digital products, and how I’m planning to revolutionize QA education.

The Growth of My Online Presence

I’ve managed to grow my LinkedIn account from 600 to 5000 followers and my Twitter from around 100 to over 800 followers. My email list has also seen a significant increase, going from about 30 readers to over 450. On top of that, I’ve made over $450 from digital products and services designed to help those in QA with their job hunt or to learn valuable career skills.

Learning from a Failed High Ticket Offer

Back in July, I invested in some high ticket offer coaching to pitch my first high ticket offer to my readership. I introduced a “job hunt wingman” service for QA professionals, priced at $1,000 a month. Unfortunately, it didn’t take off as I had hoped. The price was steep, and without social proof of my success in helping others, it was a tough sell. I’ve realized that I should have started by helping someone at a low cost or even for free to build that proof and trust.

Gaining Valuable Skills and Refocusing

Despite the setback, I’ve gained invaluable skills that I’ll carry with me into the future. I’ve also taken a step back to reassess my approach. I realized that my technical portfolio and online presence didn’t reflect my current abilities or the value I could offer. It was time for a change.

My Three-Pronged Strategy

On July 28th, I made a decision and shared it on Twitter. For the rest of 2024, I would focus on three main areas:

1. Launching a Personal Website: a personal website that I could be proud of, using a template to avoid the hassle of designing it myself.
2. Updating My Personal Projects: work on projects that showcase my current level of skill and display them on my website, along with my contributions to the QA community like my newsletter, interviews, open-source contributions, etc.
3. Creating a New Course: I’m developing a course to teach QA automation, including how to be hirable forever, leveraging content creation, and using AI tools like Cursor.

A New Approach to QA Education

When I say “create a course,” I’m not just creating a typical course; I’m building a learning experience that goes beyond the norm.

It’ll be different than any course the QA industry has seen before, leveraging my unique blend of tech & business experiences.

This will be a hybrid education model, not entirely self-paced, with human feedback on student work. I want to provide a support system through DMs and video calls, and foster a learning community where students can collaborate and support each other.

The Social QA Boot Camp

Launching on Black Friday this year, the course will be priced affordably, with an option for weekly check-ins at a higher price. I’m focused on making the course content-rich yet concise, with audio alternatives for lesson texts. I’ve already enrolled beta testers who are providing feedback to ensure the course is user-friendly and effective.

Ensuring Quality and Building Authority

I’m committed to reviewing student work personally, to ensure they leave the course with high-quality projects and content. This course is my way of building authority in the QA education space and providing social proof for my business.

The Future of QA: An Evergreen Skillset

I believe that to remain competitive, QA professionals must become more social and contribute to their community. That’s why I’m passionate about teaching not just technical skills but also communication, marketing, and sales skills. My goal is to help every QA become evergreen professionals, equipped to stand out in a saturated market.

Conclusion

I’m excited to launch this course and make a real impact on those who join. It’s not just about QA; it’s about how to be a QA that remains hirable for the foreseeable future.

Stay tuned for the Social QA Bootcamp, where we’ll redefine what it means to be a QA professional in today’s market.

Get on the course waitlist

https://chasingquality.ck.page/social-qa-waitlist

Embracing Slow Networks: Improving User Experience

Recently, Noah Falk on X shared a video that sparked a conversation about why your application needs client-side JavaScript:

He demonstrated the Hey calendar app’s performance on a slow network, revealing a significant delay when adding a new event—a delay caused by the app’s reliance on server communication to display the contents of a popover.

The Reality of High Latency

The truth is, not everyone has the luxury of a fast internet connection. As developers, we can’t control the network conditions our users will face. That’s why it’s crucial to consider how our applications perform under high latency (especially for productivity apps like a calendar). Some may dismiss these concerns, assuming that everyone has access to high-speed internet, but that’s simply not the case. We must acknowledge that poor user experiences do occur and that they matter.

I’ve experienced this frustration firsthand with the Hey email service. Despite my initial interest, the sluggish response due to Hotwire’s architecture led me to stop using it. This isn’t to shame the technology or its supporters but to emphasize the importance of continuously striving to improve user experience.

React Server Components: A Game Changer?

The discussion naturally leads to React server components (RSCs) and whether they fall into the same trap as Hotwire, requiring server interaction for UI updates. While RSCs do involve server communication, they offer a unique advantage with the use client directive. This allows developers to seamlessly transition a component from server-driven to client-interactive without a complete overhaul.

With Hotwire, improving a feature like the Hey calendar popover would mean a significant shift to JavaScript, moving templates, and potentially re-architecting the feature. On the other hand, RSCs enable a more straightforward approach. By simply adding use client at the top of a file, you can introduce state and client-side reactivity without the need to juggle between Ruby and JavaScript code.

Embracing Innovation and Honesty in Technology

As we evaluate the technologies we use, it’s essential to do so with honesty and a focus on enhancing user experience. Personal attacks have no place in this process. Instead, we should celebrate the advancements in our field and the different approaches to application development.

React Server Components are exciting because they allow developers to easily toggle between server and client-side rendering. This flexibility doesn’t require a shift in your mental model or coding approach. It’s this simplicity and adaptability that make RSCs a valuable tool in the web developer’s arsenal.

Conclusion

In the end, it’s all about creating the best possible experience for users, regardless of their internet speed. Innovations like React Server Components are pushing the boundaries of what’s possible, enabling us to build applications that are both robust and responsive. As we continue to explore these technologies, let’s keep the user at the forefront of our minds, ensuring that everyone can enjoy a seamless and engaging online experience.

Generative AI vs LLMs: Key differences explained

Generative AI encompasses various forms of creative AI, including text, images, and music, while LLMs specifically focus on language, meaning all LLMs are generative AI, but not all generative AI is classified as LLMs.

Imagine this: You’re scrolling through reddit, reading posts on X (aka Twitter), or talking to your coworkers, and words like “Generative AI,” “LLM,” and “machine learning” keep coming up.

You nod along, but deep down, you might be wondering, _What do these words actually mean? And why does everyone seem so excited—or nervous—about them?

_If you’ve ever felt this way, you’re definitely not alone (I know I’ve been there 😅). In the last few years, AI has become a hugely popular topic (especially on social media).

As a result, many people seem to be throwing around these “AI words” as if they all mean the same thing.

But what do these terms really mean, and how are they connected? Let’s start with the basics.

What Is generative AI?

You can think of Generative AI (GenAI) as an umbrella term. It’s all about creating something new—hence the “generative” in its name.

Whether it’s images, music, text, or code, GenAI tools are designed to take what they’ve learned and generate original content.

This means they’re not just copying what they’ve seen—they’re creating something entirely new that’s based on the prompt you provide (which is why learning a bit about prompt engineering can really help you get the results you want! 😉).

Here are a few examples of GenAI tools you might recognize:

• DALL-E and Midjourney are both great tools for generating images! In the past, I’ve used both to generate images for websites I was working on and for social media banners and posts. For example, my banner on X was generated by MidJourney! (but personally I think DALL-E is the easiest to use when it comes to writing prompts, so that’s what I use now).

• SoundRaw is a nice choice for creating royalty-free background music for shorts or videos. I don’t have the best ear for music, but even I can use this tool to make something that sounds decent!
• ChatGPT and Claude are excellent for writing and editing text. Basically anything “important” that I write nowadays, I’ll send over to Claude for some feedback. Unfortunately, Claude has some pretty strict rate limits. You can only send about 40 messages per day on the free tier unless you subscribe to a paid plan. That’s why I’d rather just access Claude through Pieces!
• Grok is amazing when it comes to generating images, especially images based on your X profile! Recently there have been all kinds of trends like “Draw me as an anime character”, “Generate what you think my room looks like based on my X profile”, or “Generate me as a Lego character”.

Here’s how Pieces looks as a Lego:

If you end up generating an image based on your X profile, we’d love to see it! Just tag us @getpieces

But how does GenAI actually create (or generate) these things? 🤔

To put it simply, it’s trained on massive amounts of data to recognize patterns found in that data. Once it learns those patterns, it can then generate similar (but unique) outputs.

Now that we’ve covered GenAI, let’s talk about LLMs (Large Language Models).

How does an LLM even work?

LLMs are a specific type of generative AI that focuses on text. They’re trained on datasets that usually include books, articles, and code (although the type of data really depends on the purpose of the LLM).

Once trained, they can use what they’ve learned to respond to prompts in a way that feels almost.. kinda sorta.. Human.

Here are a few LLMs you might’ve heard of:

• GPT (Generative Pre-trained Transformer): Great for help with coding, writing docs, and brainstorming ideas, some examples are ChatGPT 4, ChatGPT 4o (my personal favorite in the ChatGPT family), and most recently ChatGPT o1.
• LLaMA (Large Language Model Meta AI): Built for research, some examples are Llama 2 7B and Llama 3 8B (which are both local models that you can access through Pieces). One thing that’s cool about these local models, is that you can use them even when you’re not connected to wifi!
• Claude: Known for long-form writing and creative tasks. Claude 3.5 Sonnet probably is my favorite LLM just because of the way it writes compared to other LLMs.

Since LLMs are focused on language-based data and tasks, it makes them ideal for anything text-related (think editing articles, code generation, content creation, language learning, etc.).

Fun fact: Pieces for Developers gives you access to 25 distinct LLMs 🤯.

Don’t like the output one LLM gives you? Just switch to another (you can even switch mid-conversation!).

With Pieces, you’re able to easily move between models like ChatGPT, Claude, and Gemini until you find the response that works best for you.

What are the limitations of GenAI & LLMs?

While GenAI and LLMs can be super useful, they’re not perfect.

They rely on the data they’re trained on, so if that data has biases or incorrect/outdated information, it can affect their output (or the responses you get back).

Another problem is that If you ask them a hard question or just a question that they’re unsure about, they might not admit they don’t know and could just make up an answer instead. This can be especially annoying when you are trying to learn something new and end up going down the wrong path due to these “hallucinations”.

What’s the difference between generative AI vs large language models?

Now we know a bit about GenAI and LLMs, but what’s the real difference?

Generative AI is the umbrella term covering everything from text generation to images, music, and more. LLMs are a specific part of GenAI focused on creating and understanding language.

Here’s a simple way to think about it: LLMs are generative AI, but generative AI is not always an LLM. Generative AI is the broad category for any AI that creates something new, while LLMs are a type of generative AI focused specifically on text.

That’s why earlier in the article we mentioned ChatGPT and Claude in both the GenAI and LLM sections. ChatGPT is both Generative AI and an LLM. On the other hand, DALL-E, which is used for image generation, is Generative AI but not an LLM.

What is the hierarchy of artificial intelligence?

Now that we understand a bit about Generative AI and LLMs, how do they fit into the bigger picture of “AI” as a whole?

To make sense of it, think of AI as a set of layers (like an onion!), each getting more specific as you get deeper.

The image above breaks it down like this:

Artificial Intelligence (AI)

This is the broadest category and includes anything that mimics human intelligence. This could include conversational AI (ChatGPT), Image generation (DALL-E), the AI that powers self-driving cars, and so much more! This is where it all starts.

Machine Learning (ML)

An essential part of AI that helps systems learn from data and get better over time. The more data the system processes, the more accurate its predictions and decisions become.

Deep Learning (DL)

A type of Machine Learning that uses neural networks to recognize patterns and handle complex tasks.

Generative AI (GenAI)

Built on Deep Learning, this is where AI starts creating new things, like images, music, text, and code.

LLMs (Large Language Models)

A specific type of Generative AI focused on language. LLMs power tools like ChatGPT, Claude, and Pieces!

Integrating generative AI and LLMs in your workflow

If you’ve made it this far, you’re well on your way to understanding AI (congrats!). But you might be thinking, how can I actually use AI in my work or daily life? 🤔

Here are some practical ways to get started:

Create engaging content

• Tools like ChatGPT or Claude help you come up with ideas, draft blog posts, and create outlines quickly.
• If you enjoy writing your articles/notes in Obsidian, the Pieces Obsidian plugin is super useful. Its long-term memory engine keeps your workflow context accessible, while Pieces copilot is there to answer any questions as you write.

Leverage developer tools

• Use code generation tools to save code snippets and generate code directly in tools like VS Code, Chrome, or Obsidian.
• Combine Pieces with GitHub Copilot—GitHub Copilot autocompletes your code while Pieces has access to all of your workflow context to answer any questions that you might have.

Generate unique images

• Tools like DALL-E, Midjourney, or Grok let you create custom images for presentations or social media.
• If the AI-generated graphics aren’t perfect (it is pretty difficult to get them exactly the way you want them to look), you can use Canva to edit them (they even have some AI-powered editing tools available now).

Build interactive chatbots

• Chatbots can act as your coding assistant, answer questions about your portfolio, act as a virtual therapist or astrologer, or even help diagnose medical issues (which is probably a terrible idea!).
• You can integrate chatbots into your coding projects using APIs like OpenAI’s API (for models like ChatGPT) or Anthropic’s Claude API. Or, you can use one of our SDKs to call your preferred LLM through Pieces OS—for free.

Hopefully, now you have some ideas on how you can integrate AI into your workflow! Honestly, whatever you need “AI help” with, there’s probably something out there for you (if not, then you could even build it yourself).

That said, GenAI and LLMs have quite literally changed everything. And not just for developers.

People who in the past could barely draw stick figures are now creating amazingly detailed works of art (If you don’t believe me take a look at Midjourney’s Explore page).

And those who never thought they’d try coding are now building their own simple websites and games.

These are just a few examples. GenAI and LLMs are making it easier than ever for anyone to create, code, and bring their ideas to life. The tools are here – what will you do with them?

Quitting caffeine

The Decision to Quit

Eight months ago, I made a significant decision: I quit caffeine. It wasn’t easy, as caffeine had been a part of my life for as long as I could remember. My use varied, increasing during stress and decreasing when I tried to cut back. At times, it reached excessive levels. I disliked the anxiety and confusion that caffeine caused. Caffeine let me work with intensity. But I often found I hadn’t accomplished much.

I had attempted to quit before, but it was challenging. I’d abstain for a few months, then return when motivation lagged.

This time has been different. I find myself in a better position to live the life I desire. It’s hard to credit changes to quitting caffeine with so many other things changing in my life. Still, if my performance stays the same or improves, it’s proof I can manage without it. Let’s explore how quitting caffeine has affected various aspects of my life.

Sleep Quality and Quantity

Sleep Duration

After quitting, my sleep increased. I’d sleep 12 hours daily, with regular naps. This initial period of increased sleep helped me feel more balanced and restored.

Now, I average seven hours of sleep per night, even with the chance to sleep longer. I suspect that, with better sleep hygiene, I could sleep for more than eight hours and feel even more refreshed.

Sleep Disturbances

Some believe that recovering from caffeine dependence only takes a few weeks. Yet, the sleep disturbances I’ve had argue otherwise. For at least two periods during this process, I’ll wake up in the middle of the night, unable to fall back asleep. This problem occurs less often, now happening only a few times a month.

Increased Dream Vividness

Caffeine suppresses REM sleep. Since quitting, I’ve noticed more vivid dreams. Dreaming helps to process thoughts, giving me clarity when I’m awake.

Energy and Motivation

Morning Energy Levels

In my caffeine-consuming days, I’d often wake up energized, even before my first drink. I suspect it was due to the ever-present caffeine in my system or the anticipation of my first drink of the day.

Now, I wake up refreshed on most mornings. But sometimes there’s a tiredness that is hard to shake. A bit more sleep resolves this, when I can get away with it. Otherwise, I move forward with my daily routine and soon feel fine. Either way, my morning energy is more calm, which is perfect for most of what I need to focus on anyways.

Consistent Energy Throughout the Day

Maintaining optimal energy levels to live my best life is a top priority for me. Yet I was so tired of caffeine’s artificial energy that I didn’t care how much energy I lost. The good news is that my energy is not only better than ever, but also consistent throughout the day.

Improved Focus and Flow

While on caffeine, I associated feeling wired with productivity. If I didn’t feel like I was a rocket taking off, I believed I needed more caffeine or a nap. In the first few months after quitting, I had to retrain myself. I had to stop confusing that feeling with motivation.

I’m pleased to report that my energy and focus are now at their best without caffeine. The right task can put me in a flow state, immersing me in my work and making it hard to disengage. I rarely had this experience with caffeine, but it has become more common since quitting.

However, caffeine can make boring tasks seem interesting. This can help make a tedious life tolerable, which can be a trap.

Mental Clarity and Life Choices

Evaluating Priorities

As expected, my motivation bottomed out when I quit caffeine. Fortunately, I timed this to happen around Christmas, making it more manageable. As I began to recover, I saw that caffeine-fueled zeal had driven some parts of my life. After removing the caffeine, the excitement disappeared. This realization highlighted the potential dangers of relying on caffeine for artificial motivation.

Quitting caffeine may lead to one of the most significant changes in my life. It has allowed me to see what excited me and what didn’t, enabling me to choose the life I want to build.

Increased Calm

I now feel a calm, steady energy without caffeine. I am less reactive to small annoyances, which is a big benefit.

Caffeine’s anxiety-inducing effect has played a major role in this progress. A key change is the removal of nervous energy, the kind that makes people over-apologize. I suspect caffeine-related anxiety is a big, unrecognized problem. Many could reduce their anxiety by cutting back on caffeine.

It’s convenient that society normalizes caffeine. Not only does it make work seem more engaging, but it also prevents you from noticing that the work is boring.

Challenges with Exercise

Exercise is the primary area where I can’t tell if life without caffeine is better. Since quitting, my workouts have been less consistent and intense.

It’s challenging to disentangle these issues from other ongoing life changes. I perform best when I exercise in the morning, but that is also when I’m most productive in my work. I’m in a critical transition in my life, so I’ve decided to use my mornings for work.

Since I’m less inclined to exercise later in the day, I’m more likely to skip working out altogether. I’m testing new ways to boost my motivation and will update you on my progress.

I’m unsure if I’ll ever regain the energy that caffeine once gave me for intense weightlifting. Time will tell if my potential is truly capped or if there’s a way to fix this.

Reduced Soda Consumption

I made the switch from regular Coke Zero to the caffeine-free version. The taste is the same. But, the urge to drink it is less without caffeine. This shows the reinforcing effects of caffeine in action.

Caffeine makes you pee more due to various physiological mechanisms. Combined with cutting my fluid intake, I’m making a lot fewer trips to the bathroom. Which is useful for focused productivity.

Conclusion

I realize speaking ill of caffeine is not going to be popular. Everyone’s different, and it might be right for you. It was valuable to hear the stories of colleagues who have quit over the years, so I’m sharing mine.

I’d love to hear about your personal experiences with caffeine.

See you next week.

Three Sectors Leading SPY Back to Offense

KEY TAKEAWAYS

• The market came out of defensive mode after the election.
• Old resistance at 585 is now support for SPY.
• XLC, XLY, and XLF are all showing strength.

First of all, for those of you looking for a new video this week, I have intentionally skipped it because I didn’t want to make a video right before such an important event with much uncertainty.

After the elections, which were obviously eventful, I wanted to see what the market’s reaction would be and let the dust settle down before diving into any analysis, which might have been too preoccupied and presumptuous too early.

However, it’s now Friday, the end of the week, and we have a little more color on how markets have responded to the election results. It’s time to see what the sector rotation is telling us and how the chart of the S&P 500 has changed—because it has definitely changed!

The S&P 500’s Post-Election Reversal

If you look at that chart right now with the annotations, which were the cornerstone of my view, I have to say that it was a little conservative going into the elections. This has now pretty much turned around. On the chart, a very clear island reversal is now visible.

We have the gap down on the 31st of October, followed by three more or less sideways days, which took SPY to a low of just around 567. On November 5th, election day, the market closed at the high, followed by a massive gap up the day after. It was not only a gap up but also a move above the S&P 500’s all-time highs.

So we have a massive gap up. We have an island reversal, which completed just above pretty important support around 565, and we now already have two days of good follow-through. That is a strong sign. This market wants to go higher, at least in the near term.

If we switch to the weekly chart for SPY, those mild divergences between the RSI and price and the MACD and price are still visible, but the price action itself is so strong that it cannot and should not be negated.

So, at least in the near term, this market wants to go higher. For now, corrections holding above support around 585 (the former peak) should be regarded as buying opportunities.

Reversals in Sector Rotation

On the relative rotation graph for the 11 S&P sectors above, I have intentionally set the tail length at six trading days. That means that each tail has seven nodes, and the 4th node, so the middle one, is November 5th. This allows us to see the 3 days leading up to election day and then the 3 days after election day. As you can see, most of the tails have continued to travel in the direction they were already heading.

The most prominent ones are consumer discretionary and communication services, which entered and moved further into the leading quadrant. On the other side is the utility sector, which accelerated further into the lagging quadrant.

Sectors with Notable Changes

I want to highlight a few sectors that really changed direction, where we saw a change in detail before and after election day. The two sectors with the most prominent changes are financials and health care.

This first RRG shows the tails for both sectors ending on the 5th of November.

Financials Sector (XLF)

If we zoom in on the tail for XLF, you can see that it ended November 5th just inside the weakening quadrant. It just crossed over from leading to weakening. Then, in the 3 days after November 5th, it completely reversed course and is now almost back into the leading quadrant.

Health Care Sector (XLV)

The same sort of move is visible on the other side of the chart for the healthcare sector, XLV. On November 5th, XLV had just crossed into the improving quadrant and was on a positive heading. In the 3 days after, the sector completely reversed course and is now back into the lagging quadrant at a negative heading.

XLP and XLRE Rolling Over

Other sectors where we see a change in the course of the tail include consumer staples, which was inside the improving quadrant but hooked back down, rolled over, and is now back into the lagging quadrant, and real estate, which was also inside the improving quadrant but rolled over and is now accelerating into the lagging quadrant.

The technology sector changed course a bit, but not as clearly as the other sectors. It is still right around the 100 level on the RS ratio scale and very close to the benchmark without a very clear direction.

The Big Winners Post-Election

I think the biggest winners from these election results with good potential going forward are consumer discretionary (XLY), and Communication Services (XLC).

XLY is obviously led by TSLA, which is distorting the performance of the consumer discretionary sector with an almost 27% gain in 3 days. But consumer discretionary stocks have picked up roughly between 3% and 7% across the board, which still indicates strength. The communication services sector is slightly more evenly spread out, and has a good base and a good foundation to move higher and push further into the leading quadrant.

Conclusion

All in all, the market as a whole seems to have reversed its course. After only a very mild corrective move, it has now started a new up leg in the existing uptrend. The sectors that have come out on top are consumer discretionary and communication services, followed by financials.

All 3 are on the right-hand side of the RRG, either already inside the leading quadrant or almost there, and traveling at a positive RRG heading. On the opposite side, the sectors with a less favorable outlook are health care, consumer staples, and utilities. Overall, the sector rotation has now shifted from defense back to offense.

#StayAlert, and have a great weekend. —Julius

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Julius de Kempenaer
Senior Technical Analyst, StockCharts.com
Creator, Relative Rotation Graphs
Founder, RRG Research
Host of: Sector Spotlight

Please find my handles for social media channels under the Bio below.

Feedback, comments or questions are welcome at Juliusdk@stockcharts.com. I cannot promise to respond to each and every message, but I will certainly read them and, where reasonably possible, use the feedback and comments or answer questions.

To discuss RRG with me on S.C.A.N., tag me using the handle Julius_RRG.

Different Approaches to Visual Editing in Headless CMS

This article outlines the benefits and potential downsides of different ways to edit content visually. Headless CMSs are starting to add visual components, from side-by-side previews to WYSIWYG inline editing and a lot in between. Some pure players, like Builder.io and Uniform, decided to start visually and work their way back to CMS-like functionality.

Now that all marketing is identical, it’s really hard to choose. In this article, I will explain the different approaches to help you make an informed decision.

Beware, the market changes fast. The vendors mentioned in this article might have changed their offerings since writing this.

TL;DR? Take the questionnaire

This questionnaire will help to figure out what you need in terms of visual editing in your CMS. If you want to know how to all works, read the rest of the article below.

The Four Categories of Visual Editing in CMS

Regarding CMS, the editing experience can vary greatly depending on the platform and the user’s specific needs. Let’s dive into the different categories of CMS editing experiences, their pros and cons, and some examples of platforms that fit into each category.

Category 1: Visual Preview

In this category, the CMS form fields and the website are displayed side by side. You can see your website update in real-time as you fill out the form.

Notes:

• For instant updates: Requires a front-end SDK
• For updates on save: Common in CMSs with strict schema validation rules. Can be done without SDK
• Preview links: Some CMSs provide links to a specific build of the front end that queries the draft API, opening in a new tab

Pros:

• Ideal for editing domain data
• Similar to traditional CMS editing but with a potentially better view of the content being edited

Cons:

• Can be pretty abstract
• Editing is not visually driven

Vendor examples: Hygraph, Directus, Amplience, Strapi, Contentstack

Category 2: Contextual Live Editing

This category allows you to click on an element on your site, triggering a sidebar with a CMS form for editing. Sometimes, this redirects you to your CMS interface in a new tab.

Notes:

• Requirements: A front-end SDK, Vercel’s Stega data, or HTML annotations

Pros:

• Clicking on an element in the preview website opens the corresponding CMS form for editing
• A significant improvement over side-by-side previews

Cons:

• Feels like a WYSIWYG, but isn’t
• Developers may need to put in extra effort to implement design-like features

Vendor examples: Sanity, Storyblok, kontent.ai

Category 3: Almost WYSIWYG

This category offers block-based visual editing, providing a more structured, pattern-like approach. It is based on a design system.

Notes:

• Requirements: A front-end SDK
• Additional Features: Some platforms offer external API data managing, mapping, and editing. Also seen are personalization and sitemap management

Pros:

• Native features for WYSIWYG-style editing with guardrails to stay within the design system specifications

Cons:

• Some vendors have complex setups
• Others are easier to implement but require a bigger buy-in as they handle external data ingestion and mapping

Vendor examples: Uniform, Contentful Studio, Sitecore XM, builder.io, Plasmic, Netlify Create

Category 4: Full WYSIWYG

In this category, you design like a designer, and a website is created. All CSS properties, animations, and other design elements are available.

Notes:

• The platform controls your codebase and hosting

Pros:

• Easy to get started; anyone can design something

Cons:

• Hard to scale
• A mix of design data vs. domain data
• Content not reusable
• Code and hosting are provided by the platform

Vendor examples: Wix, Weweb, Webflow, Squarespace

Understanding Domain vs Design Content

Let’s discuss the difference between domain content and design content and why it is so important in choosing visual editing vendors.

Domain Content

Definition: Domain content refers to structured, clean, and semantic data that defines the core information and properties of a specific domain (e.g., products, users, articles) without concern for its presentation. Domain content sits at the brand’s core and can be reused in many different contexts.

Characteristics:

• Strict data-focused schema definitions (no fields for presentation features)
• Focuses on the “what” (content and information)
• Reusable across different channels and platforms
• Maintains longevity and integrity over time

Real-world Example: You don’t expect payment providers to have data about credit cards that explain how big the logo of a certain credit card is shown on a user’s checkout screen. That’s the job of the designer and the front-end implementation.

Design Content

Definition: Design content refers to the specific instructions, order, and styles for presenting domain data in a front-end application.

Characteristics:

• Focuses on the “how” (visual representation and styling)
• Tends to be more volatile and subject to frequent changes
• Tightly coupled with the current design and presentation logic

Real-world Example: A banner component with an image, a title, and a description might look different in different contexts. Selecting which banner variant you want to show is design content; the content itself comes from a CMS and is domain content.

Making the Right Choice

The less you mess with domain-specific content, the more reusable it is and the longer it lasts. If you start mixing your domain content with design content, you will be working yourself into a corner regarding data flexibility and governance down the line.

However, focusing too much on the strictness of using only domain content will make it infinitely more complex for content editors who need to build a website with that content. Mixing domain content with design content could be your best bet to make everyone happy. Proper governance is a must here.

Conclusion: It Depends

Different categories offer different benefits and drawbacks based on your company’s approach to data management, your need for ever-changing pages, and your technical abilities.

There are factors other than how you want to manage your content, like how much complexity you want in your front-end channels (websites, apps, kiosks, etc). Some pure players like Uniform pride themselves on the saying: “more clicks, less code,” and they store a lot on the platform. Others, like Netlify Create, focus on code first and do not own any of your brands’ data.

The key is finding the right balance for your specific needs and use cases.