I hope everyone in the Midwest or Eastern seaboard in the US is staying cool. My son is at overnight camp this week with no AC, which means I've had unusual stretches of uninterrupted thinking time. One thing I've been turning over: how much people actually rely on physical swatch tools as part of color implementation, and whether that changes over time. Did you use a swatch book or fan heavily after your analysis in check for harmony or attribute matching? A few hypotheses I'm sitting with: -S types may hold onto physical references longer because a concrete comparison point is more reliable than an abstract rule. N types often internalize the framework earlier and drop the swatch sooner, which isn't always a sign of mastery. Sometimes it's just pattern-matching confidence running ahead of actual accuracy. -Si-dominant and Si-auxiliary types (ISxJ and ESxJ) may be the most likely to actually collect multiple swatches and fans, not just use them occasionally. Si builds detailed internal sensory libraries, and a physical reference collection is a very natural extension of that. -And then there's a completely different behavior I'm curious about: the person who decided the existing fans weren't quite right and built their own out of paint swatches. (You know who you are.) My guess is that's lprobably more of an NT one: the system has gaps, the available tools don't fully solve the problem, so obviously the answer is to make a better one from scratch. What's your type, and what's your swatch situation?

Hi all! I know I just threw out a bunch of new posts this morning. I've been missing being more active in here and finally had the time to get back in. In fact, I have been so engrossed that it is 11 am EST and I am still sitting here in my bathrobe happily typing away thinking about personality and color. With a slight break to discuss S corps and estimated taxes with my new tax accountant. I'm hoping to get some time today to continue my Personality Hacker's Profiler training modules. If so, I am sure I will be back posting about some new "a ha" moment in share here. Let me know what your IRL looks like right now!

Hi all! Slowing down today and, for those that know their best color attributes, thought it would be fun to share out favorite color to wear. Share your season or tonal combination and a swatch of your favorite color. I will go first. As a Dark Autumn who can borrow from Deep Winter, my favorite color to wear is a burnt orange. And yes, this is a proof point towards the idea you often subconsciously already know your "season." Burnt orange is a deep, warm shade that combines the vibrancy of orange with a subtle infusion of brown, giving it a rich, earthy quality. It's positioned in the red-orange side of the color wheel, exuding a sense of energy and enthusiasm while maintaining a cozy and inviting feel. https://www.figma.com/colors/burnt-orange/

The launch landed about where I'd hoped: useful enough to be worth people's time, with plenty of room left to keep building. @Kiersten Emmi put it well when she called the vocabulary section a goldmine and admitted she'd never heard of "toasted" as a color modifier before trying this. That's basically the whole reason the tool exists: most of the words people in color analysis use constantly (bright, muted, soft, burnished) get handed to you without ever being precisely defined. At the end of the day, that's probably a fair description of why this Skool group exists too. My ESTJ side has never been able to just accept a term at face value. I want to understand and implement the concept, not just have the word. Here's what changed in the few weeks since this landed in the Classroom: - Temperature slider. Nudge any selected hue warmer or cooler within its own hue family. A warm blue pulls toward violet, a cool blue pulls toward teal, same hue family, different temperature. - Hex code input. @Mary Molle asked directly for this: "I wish I could enter a hex code in the tool." Now you can, instead of being limited to the pure hues in the original picker. - Color analyzer. Enter any hex code, a garment color, a paint swatch, whatever you're trying to place, and get a breakdown of value, chroma, clarity, and temperature, plus a tentative season estimate. One caveat: this reads a garment color, it doesn't diagnose you. A few things are still in motion based on what's already come up in the comments, worth naming now so you can weigh in before any of it is locked in: - A glossary mapping the typical attribute ranges for each of the 16 subseasons is coming, so you can see roughly where a subseason tends to fall on value, chroma, clarity, and temperature instead of just seeing a name attached to it. - The vocabulary reference page is getting a few more entries, starting with luminescence. If there's a term you've run into that doesn't have a clean definition yet, this is the place to flag it. - The pure hue reference still shifts when you move the temperature slider. That's a bug, not a feature, and it's on the list to fix.

A month into beta testing the Best-Fit Personality Preference Lab, the feedback coming back wasn't really about polish. It was about what the tool needed to do that it wasn't doing yet, and that turned out to be more useful than I expected going in. Here's what changed because of it: - Hosting outage. The tool went down within hours of the original post. That one was Netlify, not the tool itself, and it got fixed the same day. - Personality and color intersection. This section was thin at first (@Amanda Owens conversation nailed her type clearly but left the color side underbuilt). It has more depth in it now. - Saving sessions. The save function wasn't obvious. Saving as a .txt file lets you pick up a session exactly where you left off. Downloading as a PDF gives you a copy to keep. - Typing vs. speaking. If typing out long answers isn't your thing, there's a microphone option. Several of you found speaking the answers more natural than typing them. - Enter vs. Shift+Enter. Enter sends your message immediately. Shift+Enter gets you a new line instead. This one cost a couple of you complete data on a multi-part question, so it's worth knowing before you go back in. None of this was about making the tool prettier. It was about closing the gap between "this technically works" and "this is actually usable," which is the same gap I care about on the color side. The whole point of building it this way was avoiding the "flourishy nothingburger" problem (thank you @Kiersten Emmi for that very apt description) most AI chat tools have (technically responsive, not actually useful), and that only happens by building around what real use revealed, not what looked finished in testing. If you haven't tried it: bestfitlab.netlify.app. If you have and hit something worth telling me about, working or not, drop it below or DM me.