Rileytech

The Suit

Fri, 31 Jul 2026 19:00:00 Z

The Blank Slate, Part 4

"Find a restaurant near me."

It's the default search - whatever it is, near me. That's how most people are using AI, so it's where this starts.

Zero context, so the machine guesses your location and dumps random spots. Overwhelm and irrelevance. Level up - "American restaurant in Longmont" - still vague, still a mediocre list. Add timing and "top-rated" and you're getting there, but you'll still filter everything manually, because the machine still doesn't know what you're actually picturing.

Now watch the top of the ladder: "Suggest 3-5 top-rated burger spots in downtown Longmont under $35/person with an extensive bourbon selection and outdoor seating, this Friday evening, party of 6 - include ratings and why they stand out. Suggest parking within 500 feet, factor in any events between 6 and 10pm, especially live music. Suggest 3 after-party bars known for an evening-ending vibe. Cross-verify with recent posts. Check your work - and ask me 3 questions to clarify before making a suggestion."

Look at how that ends. The highest rung of asking isn't more adjectives. It's making the machine ask you the questions. You are now the LLM.

Hold that. We'll come back to it, because it's the whole post.

Which rung did you hire?

Part 3 built a ladder out of people - fan, enthusiast, hobbyist, professional. That restaurant search is the same ladder compressed into a single text box. And it exposes the question nobody asks when they open the app:

Not which rung are you. Which rung did you hire it to be?

Because here's the pattern, everywhere I look: people take the most capable machine ever put in their hands and hire it as their enthusiast. Fast, agreeable, confident, free. And we already priced that rung. Part 3 repriced it to zero - which matches the mental tax you paid for it. The free answer is fast because it's worthless - it cost you nothing to ask, it cost the machine nothing to guess, and it's wrong in ways neither of you paid attention to.

Here's what that hire looks like in the wild: search engine 2.0. Type a question, get an answer, close the tab. And honestly - as a faster Google, it's fine. It saves time. Nobody's mad at that. But if you use this thing for work, hear this part: it is not a search engine, and it is not an email polisher. A search engine finds things that already exist. This machine builds things that don't - and it builds them out of whatever you handed it, which, if you asked like a search, was nothing. Treat it like search and you get search-shaped results: confident, generic, vaguely right, specifically useless. And the email it "saves you time on" is the same trap wearing a collared shirt - you hired a suit and asked it to type.

The tool is a suit. It amplifies whoever's inside it. Put an operator in the suit and it lifts what they couldn't lift alone. Put nobody in it and you've got the world's most expensive machine doing donuts in the driveway. You can tell the difference in one sentence: the empty suit cites reality as a constraint. The operator treats reality as a draft with poor version control. [OPTIONAL ADD, your call: "— the scars are all in the history, somebody just has to go read them."]

So this part is the operator's manual. Not for the machine - it doesn't need one. For you.

Get it out of your head

One concept runs under everything else here, and it's a concept, not a prescription:

Everything you don't say, the machine invents.

You know things without speaking them. The budget you'd never exceed. The person you're actually writing for. The way "done" or "good" looks in your head. That knowledge is real, it's load-bearing - and it is completely invisible to a blank slate. Every unstated constraint gets replaced by a guess. The lazy restaurant search doesn't fail because the machine is dumb. It fails because you kept the entire dinner in your head and asked it to read your mind.

If you end up with a useless list of restaurants, it's annoying at most. Let me show you what it costs when the stakes go up.

The Internet and the LLMs Were Wrong

I've been working on an old Jag. Window channels specifically - the felt-lined tracks the glass rides in. The internet is exactly the mess you'd expect for a decades-old car: old-school guys say the replacement is one way, newer guides say something else. Bonus? Neither one is right. Pick either camp and you're doing the door twice - and this isn't a job you get to casually redo.

Here's the thing: the answer was never in the categories. It was in the millimeters. When I finally asked for the actual dimensions - width, thickness, the numbers - the whole argument dissolved. The felt channel is way thicker than what they installed new, on purpose: it's built to absorb decades of body-build variation. The old insert is thin and tight because it was made for a door that matched the drawing. The forums weren't wrong. They were answering for the same doors, at different times.

And the machine? It agreed with everybody. Of course it did. It has never done a window on a Jag - and the people who actually have? They never wrote it down (or posted it on the internet at least). So it trained on the argument, not the answer. Ask it cold and it doesn't amplify wisdom; it amplifies whatever the internet said loudest, with better grammar and more confidence. The internet's wrongness didn't get corrected by the LLM. It got a spokesperson - and a spokesperson's job is to close, not to counsel. A salesman sells you what you walked in asking for. Order two Big Macs, three fries, and a Diet Coke, and nobody behind that counter is going to ask about your heart. You get exactly what you ordered, served fast, with a smile - unless you make the counsel part of the order.

The deciding detail was in my head and my garage the entire time: the dimensions of my door. Nothing on the internet could pick my fork, because the fork wasn't on the internet.

And notice what had to happen: I reached for the dimensions. Nobody asked me for them. Left unprompted, the machine would've picked a camp, insisted it was correct, handed me that confident answer, same as the forums did - and I would've been confused when I did the work, asking more questions with the panel already off. "AI sucks."

The Inversion

So stop relying on yourself to remember what you forgot you know. Delegate the reaching. This is my favorite hack, and it's one sentence:

"Ask me 3 questions. One at a time. Use each answer to inform the next question."

That's it. That's the inversion - the top rung of the restaurant ladder, generalized. You flip the machine from answering to interrogating, and every question it asks marks something it was about to invent. Each answer narrows the next question. Three exchanges later, the thing in your head is on the table where the tool can actually use it.

And the number is a dial. The number of questions is a unit of risk. Dinner gets three. A door panel gets three. An architecture decision gets ten. The number is your bet on how much you haven't said out loud - how expensive it would be to let the machine guess. Low stakes, let it guess. High stakes, make it dig.

The catch

When you get good at this, it takes longer to get an answer.

The tool sold as a time-saver pays out to the people who spend time on it. The free rung is instant - that's search engine 2.0 again, confident vagueness on tap. The operator's rung costs you three questions, ten questions, the dimensions, the intent — it costs you getting it out of your head, and that was never going to be free. Precision, context, and intent win. Ask like you're explaining to someone who does not know what you mean - because you are.

The key

How do you know you've climbed? Same test the whole series has been running, compressed: you've earned the key when you can do three things with the work you're about to ship. Teach it : explain what you're doing to the blank slate, plainly, no jargon armor. Predict it : say where it'll break before anything breaks. Defend it : argue the strongest case against yourself before the mirror does. Explain, predict, defend, every pass. Teaching is the proof you're a mirror and not a tollbooth: if the only thing you can do with your knowledge is charge admission to it, you never had the key - you had the door.

Full circle

Part 1 opened with the sentence this whole series has been walking toward from the other side: the model was never the thing being tested. You are.

Four parts later it should land differently. The suit amplifies whoever's inside - so the only variable worth working on is the operator. Get it out of your head. Make the machine ask. Spend the questions the stakes deserve. And ship your thinking sooner, so the mirror can correct you sooner.

The blank slate was never grading the machine.

Some people do

Wed, 29 Jul 2026 19:00:00 Z

Part 3 of The Blank Slate

"Nobody really knows what they're doing." It's the most comforting sentence in the industry, and this post is about the people it erases.

Start with a body on the table, because I promised you this autopsy last post.

Run the mirror on Agile, same move as before: one sentence, load-bearing idea, no box vocabulary. Ship sooner, so reality can correct you sooner. That's the whole thing. That's the wall. Every shop that "did the Agile" and hated it bought the ceremonies and bolted them onto a building that refused that one bet. Two-week sprints feeding a release train that leaves twice a year. Standups for a team whose PRs get rubber-stamped at 4:55 on Friday. Then the pain showed up, and they blamed the framework.

And that's not an Agile story. That's the house style of almost every org on earth: say one thing, do another. The plaque says Agile; the releases ship twice a year. The all-hands says quality; the roadmap says the date. The gap between the stated method and the actual behavior is the single most expensive thing in the building, and it's invisible on every dashboard, because dashboards measure what you do, not what you claim.

But the gap isn't just organizational. It goes person by person, and the smallest room in the building is where you can watch it happen live.

Thirty seconds at standup

The ceremony had a why: say your work out loud so the room can catch it. And in every shop I've been in, most of the room did the same move: "Yesterday I was working on ticket 32574. Today I'm continuing on 32574." Ritual complete, box checked, and not one human at that table knows a single thing they didn't know before, because nobody memorizes the ticket queue. Attendance at the ceremony, refusal of its point.

Now listen to what it sounds like when the point survives: "I'm trying to get the data from the claims field to display properly, and I'm not quite done. It keeps coming back empty." Same status. Same thirty seconds. But that version is legible, and legible status has a property the ticket number never had: somebody across the table goes, oh, I know what's going on with that, I hit the same thing last quarter, grab me after. That meet-after is the entire return on the ritual. The ticket number spends the same thirty seconds and buys none of it.

Same ceremony. Same thirty seconds. Two different species in the room, and we don't have words for the difference, which is exactly why orgs keep hiring one and expecting the other.

So let me give you the words. They come from sports, because sports is the one arena where we've never once confused the tiers.

The ladder

The fan shows up and watches. Owns the jersey, knows the chants, never misses a game. In your building he badges in, attends every ceremony, and recites the ticket number. Participation is the entire contribution. The fan isn't a villain; most fans are lovely. But nobody has ever confused watching football with playing it. Except, apparently, us.

The enthusiast can tell you the stats. Every player's name, every draft pick since 2003, the coach's tendencies on fourth and short. This is the dangerous rung, because the enthusiast sounds like expertise. In your building he speaks fluent framework. He can name every pattern, cite every book, and tell you what the practice is called. What he can't tell you is what it's for, because his knowledge is about the game, not of it. Ask him why the wall is there and you get the wiki page, delivered with total confidence.

The hobbyist actually plays. Sunday league, garage projects, real contact with the thing. This is the honest rung: the hobbyist mostly knows what he doesn't know, because the ball has hit him in the face a few times. What he doesn't have is stakes. He can put it down whenever he wants, and so nothing he knows is load-bearing.

And then, on a level the ladder metaphor barely reaches, there's the professional. Anyone who has ever shared a field with one will tell you it's not a bigger number on the same scale. It's a different scale. The professional's knowledge is tied in: every why is attached to a consequence he personally paid. He doesn't remember that the wall matters. He was there when it fell. He's the second guy at standup, on reflex, because saying the work plainly is how his work has always been caught before it cost him. He can explain what he does, defend it under pressure, and improve it in public. And once you've watched one operate, you go a little quiet, because you become afraid of them in the best possible way.

I've parked on every rung of this ladder, sometimes in the same year. Last post I showed you my own bar-stool claim getting dented in public; that claim was enthusiast material wearing a professional's badge, and it held for years because every room I said it in nodded along. So no, this isn't a post about them. There's no them.

The lie

Which brings us to the sentence. "Nobody really knows what they're doing."

Understand where it came from, because it started as a kindness. It's imposter-syndrome first aid. Somebody's drowning on day thirty of a new job and you hand them the sentence like a towel: relax, everyone's improvising, nobody has it figured out. As first aid, fine.

But the sentence didn't stay first aid. It metastasized into amnesty. Because if nobody really knows what they're doing, then the enthusiast's stats are as good as anybody's game. The fan's attendance is as good as the hobbyist's reps. The ladder collapses into one rung, everyone's an imposter, and the tier at the top stops existing. That's what the sentence is for. It's a flattening machine, and the people it flatters most are the people with the most vocabulary and the least contact.

Yeah. Some people know exactly what they're doing. You've met at least one. You went quiet, remember?

The enthusiast machine

Now install AI in every seat and watch what happens to the ladder.

The blank slate is, among everything else, an enthusiast machine. It has all the stats. Every player's name, every pattern, every book, on tap, in seconds. And watch what happens rung by rung, because everybody hires it to do something different. The fan hires it to sound like the enthusiast, and it delivers. The enthusiast hires it to sound like something else entirely: fluent whys, structured tradeoffs, a risk register, generated on the walk to the meeting. The ticket-number guy pastes 32574 into a box and reads out a status that sounds exactly like the second guy at standup.

For decades, orgs hired and promoted by sound, because sound was expensive and the interview was an hour long. The enthusiast owned that market. And the blank slate just repriced him to zero. When everyone has the stats, the stats differentiate nobody. The fluent why is now the floor, not the ceiling, and the only scarce thing left on the ladder is the one thing no seat license mints: tied-in knowledge. The record. Reality only corrects people who were exposed to it, and there is no API for that.

The professional was never competing with the enthusiast anyway. Now the org can't pretend they were the same guy, because the costume is free and everyone's wearing it. The gap between about and of was always there. AI didn't create it. It just turned the lights on.

The diagnostic

So here's what to steal, whether you're holding a badge or a P&L: stop interviewing for sound. Sound is free now. Interview for the record. What broke. What it cost. What they'd never do again, and why, in their own words, off the wiki page. The enthusiast has an answer for what the practice is called. The professional has a scar for why it exists. One of those can be generated.

And the next time someone hands you "nobody really knows what they're doing," hear it for what it's become: not comfort, cover. Some people do. The whole point of this series is that, for the first time, there's a mirror in every seat that can show you which kind you are, before reality invoices you for the difference.

One question left, and it's big enough to be the whole last post. Everyone in your building just got handed the enthusiast machine. Watch closely what rung they ask it to be. What you wear to that contact: the suit. See you there.

This is Part 3 of The Blank Slate, a series on what happens when your thinking finally has to stand on its own.

The Only Load-Bearing Letter

Fri, 24 Jul 2026 21:09:22 Z

Part 2 of the Blank Slate

Every framework is one idea wearing a costume of ceremony. Here's how to find the idea, and what happens when you can't.

Last post I held up the mirror, the empty slab, and told you what most people see in it: the readout comes back and they can't say why it's wrong, because what they were carrying was jargon with good posture. And that's the problem with jargon: it's vocabulary, rarely mental constructs. Nothing behind the words holding weight or meaning. It exists to make you feel smart for saying it and the room feel smart for nodding along in understanding. Acronym and jargon bingo, some keynotes, and for good measure - throw in some certifications. Let celebrities rise and it comes from the same place every time.

Every framework you've ever been certified in, evangelized, or forced to sit through a workshop about is one load-bearing idea wearing a costume of ceremony. One wall holds the building up. The rest is drywall, wallpaper, and a gift shop. The industry sells the costume, because the costume is billable. The idea is free - want to know more?

I've been inside the gift shop and worked the booth. I beta-tested the Professional Scrum Developer exam. Not took it, tested it, the actual test before it shipped. It's the only certification I got. Now, being that close to the machinery was a properly useful experience - but there was a bit of a problem. They weren't checking whether I could think and do any of the concepts, much less defend them other than "that's not scrum". That was my line. Every other certification I saw after that I gave them a load-bearing test. I also worked at VersionOne for years, which meant a front row seat to every method our customers were dying for. (Also, safE still sucks. Fight me.)

So about that load-bearing test

Here's the test that matters, and it's the same mirror from Part 1: name the load-bearing idea of the thing you're defending right now, in one sentence, without the vocabulary that came on the box or as a conference headliner. If you can't, you're not practicing the framework. You're wearing it. What does load-bearing mean? Take it away, and everything else about the framework falls apart and cannot stand on its own.

Watch me run it. Three frameworks: one deep, two fast. The deep one is SOLID principles, a great framework (no, really), because it's the one I had to tear down to its one-liner. Ok, really it's 3 but stick with me.

(Non-coders: skim the letter walk if you want. The point isn't the letters. It's the move. Pick it back up at "The speed round" and you'll have lost nothing.)

The deep walk: SOLID principles

I ran this test on SOLID because I noticed a pattern after using it as a strong guiding principle for years. What I found wasn't five principles. It was one load-bearing idea, some drywall repeating it in different rooms, and a couple of beams the box never shipped. So I stopped carrying SOLID and shaved it down to the S - but brought along a Y and a D. SYD: Single responsibility, plus YAGNI and DRY, two principles SOLID never included (they're XP and The Pragmatic Programmer) and badly needed. That wasn't knocking SOLID down. That was an audit: keep what holds weight, name what's repeated, import what's missing.

The bar-stool compression went: "do SYD and the rest of SOLID just... happens." Great line. Gets nods. Fits in a tweet. So I put it on the slab, and the mirror handed back "that's great!" Of course it did. I gave it the compliment, not the recipe. Grandma's cookies are the best, everyone agrees, and nobody can bake them, because the recipe never got written down. The glaze wasn't the mirror failing. It was the mirror accurately reflecting an empty slab. So I went back with the receipts: why the other OLID got shelved, which patterns lean on which letters, where "just happens" stops being literally true. What came back is the version below. Not my bar-stool line. The load-bearing walk it turned into once there was something on the slab to test.

S is the only load-bearing letter. Not because the other four are wrong. Because every one of them is either downstream of S or dead weight without it.

Interface Segregation falls out of S. ISP is single responsibility wearing an interface costume. If your interfaces each do one job, no client gets forced to depend on methods it doesn't use, because there are no kitchen-sink interfaces left to depend on. You don't practice ISP. You practice S and ISP shows up.

Open/Closed mostly falls out of S. Small, focused units plus DRY pushing shared behavior into composable pieces means you extend instead of edit. Composition is what S forces on you, and open-closed is what composition looks like from the outside. "Mostly" is doing some work in that sentence, and I'll own the asterisk.

Liskov and Dependency Inversion don't fall out of S. Worse: without S, they're inert. This is the part the certification slide skips. You can satisfy Liskov's letter perfectly and improve nothing, because substituting one god class for another god class is substitution theater. The contract is "everything," so honoring the contract means nothing. Same with DIP: inject a kitchen-sink interface and congratulations, you've abstracted a monster. The wiring diagram looks like the slide from the workshop and the codebase is still spaghetti. L and D aren't principles you can apply to a mess. They're principles that only mean something once S has given the words "contract" and "abstraction" something real to point at.

Here's the receipt from the shop floor: when S isn't a design consideration, you can't even test your way out - looking at you vibe coders. Writing good tests (various flavors of TDD) assumes you can get a seam around a unit, and a god class has no seams. There's a name for what happens next, and I've watched it in every shop that skipped the S: GDD. Guilt Driven Development. You should have written the tests. You didn't. Now you're writing them at the worst possible moment, under duress, or you're not writing them and hauling the guilt around instead. Call it debt, guilt, whatever, either way, you end up doing strangulation on the legacy mess just to earn the right to start doing S properly, so that testing can work, so that the rest of the letters have something to hold on to. The whole stack of practices rests on one. single. wall.

That's the upgrade to the definition I gave you up top. Load-bearing isn't just "take it away and the rest falls apart." It's this: everything built on top of it gets cheaper. Tests get cheap. Change gets cheap. The other letters go from workshop vocabulary to things that quietly happen. Knock out the S and it doesn't matter how loudly you recite the other four. The building is coming down with the certificates still on the wall.

The speed round

Same move, two frameworks you've lived through even if you've never written a line of code.

LEAN. Strip the kanban boards, the Japanese vocabulary, the value-stream-mapping offsites. The load-bearing idea: stop doing work that exists to make the org feel busy. That's it. Every artifact of LEAN is a device for making waste visible so you can stop lying to yourself about it. And notice what most shops did: they adopted the boards, kept the waste, and now the waste has swimlanes. The costume, without the wall.

XP. This one's fun because XP marketed itself as the rebellion, the return of the Jedi. Lightweight! No heavy process! No rules! Bullshit. Strip the ceremonies and XP is the most disciplined regime this industry ever produced: pair every day, write the test before the code, integrate constantly, release small. Monks have looser schedules. And the load-bearing idea under all that discipline is embarrassingly simple: talk to people. Every practice in XP is a conversation on a timer. Pairing is talking in seconds. The planning game is talking in weeks. The on-site customer is talking as a permanent fixture. Slow the loops and the shop degrades. Stop the talking and the loops go dark, and you're shipping fast into a void. "No rules" was the sales pitch (really it was fear from people who wanted control). Discipline enforced through humans instead of documents was the product.

(Agile gets no paragraph here. It gets Part 3)

The pattern you just watched

The Blank Slate now turns into the load bearing test - run the test yourself before your next standup, retro, or architecture review. Whatever you're defending: one sentence, load-bearing idea, no box vocabulary. If the sentence comes out clean, you've got the load-bearing wall. If what comes out is the ceremony described in different words, the mirror just told you which one you own: the wall, or the wallpaper.

And notice something before you go. Strip these three down to their load-bearing members and they start to rhyme. Single responsibility is legible code. Cutting waste is a legible workflow. Talking on a timer is a legible team. Disciplined, honest feedback, pointed at code, at work, at people. Almost like the industry has been selling the same key for thirty years with a different grind on it, in a different gift-shop box, at a different conference.

There was a guy at every shop who carried the whole ring. He knew which wall held each building up, and he could open every door. Most orgs fired him, relabeled the chaos, and called it a transformation.

Next post: Flattening the Ladder.

This is Part 2 of The Blank Slate, a series on what happens when your thinking finally has to stand on its own.

The Blank Slate

Tue, 21 Jul 2026 21:09:22 Z

AI didn't break your workflow. It read it back to you.

Here's the thing nobody posting "AI changes everything" wants to sit with: the model isn't the test. You are.

When you sit down with a capable model and a real problem, something quietly brutal happens. The model has broad knowledge and zero context on your little corner of the universe. It nods along. It will happily fill every gap you leave ... but it fills them with the internet's average, because your context is the one thing it doesn't have. Your coworker papers over your gaps with shared history - years of it. The blank slate papers over them with everyone else's.

I wrote about this in 2009, before any of this existed: ask a vague question and you hand the other person the option of giving you a wrong answer - and someone will always take it. Well, now the someone is a machine, it takes that option every single time, and it hands the wrong answer back polished, confident, and formatted like it belongs in production. Give it specific thinking, you get your thinking back, amplified. Give it mush, you get beautifully formatted mush.

Most people discover, right there, that everything they hand it comes back generic. Sort of right. Useless here for what they're doing, on their problem. And that's the moment: the model never asked them a single hard question. It didn't need to. The output IS the question. They're staring at a plausible, polished, wrong-for-them answer and they can't say why it's wrong - because saying why requires exactly the thing they never built: a legible model of their own work. "AI sucks" is what it sounds like when someone reads a printout of their own vagueness and doesn't recognize the handwriting.

Not because the model is bad. Because they were never operating where they thought they were. They were parked at Remember and Understand on Bloom's ladder, reciting jargon they never stress-tested ... and thinking it was expertise. One look at what the model built from their instructions and the Illusion of Explanatory Depth cracks wide open - every gap they never knew they were leaving, filled in by a stranger, in writing.

That's the Blank Slate.

I've been calling this out for years - that 2009 post is one of many receipts - but I only just now gave it a name. What matters is what it does: a real tool hands you back what you actually do - not the vibe version, not the one-shot-screenshot version, not the version you rehearsed for the podcast - rendered by a brilliant stranger who only had your words to work with. The people who can survive that readout ... get that magic you've heard about. The people who can't get frustrated, and they'd rather blame the tool than admit the gap.

We have seen this exact movie

Agile is dead, they say. No. It isn't. It's just how good teams work now - the framework was always scaffolding to figure it out. Learn the ceremonies, internalize the why, get everyone on the same mental models and the same rigor, and then you throw the scaffolding away because it's now fully integrated. That's the whole point. It always was.

Scrum, Kanban, Lean, XP, Design Thinking, Systems Thinking, all of it - some you try, look around, realize that's not what you need and move on. Others you practically live in. Eventually, knowing what each one is actually for turns into how you work. It makes you better. The catch is the part everyone skips: walk in a place that does it better ...and it's painfully bad. The reverse is also true. More on that in part 3.

But that's not what happened in most shops. That kind of change is hard, so someone read a blog post they agreed with already, declared "Agile sucks," and the team - drowning in standups-that-are-status-meetings and retros that change nothing - echoed it back. Leadership felt decisive, killed the framework, ignored the culture and everyone happily returned to ad-hoc tickets, death marches, and big-bang releases: the exact chaos Agile was invented to fix. No hard questions. They never defended the why. Declared it doesn't work ... and blamed the tool.

Same script. New tool. Here we go again. Now the barrier to entry is way lower.

The half-truths, conductors, and the slot machine

The hype-train conductors - some paid, some just clout-chasing - keep inflating the gap between "noticeably better" and "holy shit magic." The vibe coders who spent three weeks, limit free, in Cursor, are now "building a company." No. Those are pitch decks and LinkedIn clips. You're parroting the same shallow buzzwords your predecessors recited about using blockchain (for the wrong things), NFTs (for the wrong things), and "Web3 will replace everything" - and you couldn't defend the mechanics, trade-offs, or failure modes if someone made you explain it to a system that's never heard the concept. Ignore these clowns.

Now, the iteration itself isn't my problem - because this is where people get it backwards. The pro iterates too. Forty-seven loops, a custom system prompt, real money in credits - that's not half truth. That's the work.

What isn't? The screenshot that says "in one shot I got it to..." while hiding all forty-seven pulls. And the deeper tell is why it's hidden: they can't explain the loops because they weren't reasoning through them. They were pulling a slot machine lever until the cherries lined up, then photographing the cherries. The pro can tell you why each loop happened, what they expected, where it broke, and what adjustments they made and why. Same number of iterations. Completely different mindset. One is building. The other is gambling, getting lucky (the "you don't control it" kind) and calling it a "method" and running with what sounds good.

That's the whole difference, and it lives in the screenshots they don't post ... which is exactly why they don't post them.

Why it actually feels hard

This is the real reason AI feels impossible for so many people. Not the models, and not the interfaces either. The barrier is virtually zero now so there's no excuse. It's that they've never once seen their own instructions executed literally to the entire generic model of what's out there. They've spent careers protected by shared assumptions, hallway nods, and audiences who fill in the gaps with the right answer for them. Cheap signaling worked because the audience did the work. It also didn't help this shallow "knowledge" masked as expertise.

The model won't ask "okay, those words mean things so what do you mean - specifically?" It does something worse: it answers as if you had already told it, and shows you exactly what you actually said. Every gap filled with the average is a gap you left. (You can flip this on its head, by the way - invert the conversation and make the model ask YOU the questions, and watch it tell on itself: every question it asks marks something it was about to invent. That's a later post, part 4 probably.) A lot of people have never been shown their own instructions in their lives. And that's hard.

A few of them are reading this exact post as a three-bullet summary right now. What the model handed them is the average of every AI think-piece ever written, minus the one thing in here that was written for them. They won't notice. That's the point.

But what about the people who just do?

Here's the honest objection, and I'm going to make it for you before you make it at me: plenty of genuinely skilled people are terrible at explaining themselves. The master mechanic who diagnoses a misfire by ear and couldn't say how it was "obvious." The trader with the gut feeling that makes a million dollar bet, time and time again and wins. Real skill is often tacit - it lives in the hands, not the slide deck. So isn't "make it legible or you're faking" just a fluency test dressed up as a competence test?

It isn't.

I'm not saying you have to narrate your genius to deserve it. The mechanic is genuinely excellent and owes no one a lecture. What I'm saying is narrower and harder to wriggle out of: legibility isn't what makes you skilled - it's what lets you use a tool, supervise it, trust what it hands back, and have better answers than anyone else. Those are different things. The mechanic who works alone needs none of it. The moment he wants to hand the diagnostic to something else - an apprentice, a model, anything with broad knowledge and zero context on his knowledge ... he has to make the reasoning legible, or the answer comes back generic and he will certainly say "AI sucks."

That's the whole game with AI, and it's why this isn't about worth. You can be a tacit master and still get nothing from the tool, because you can't make your thinking legible enough to wield it, steer it, or catch it when it's confidently wrong. Legibility governs leverage, not worth. You don't trust the output because it's flawless - you trust it because you can guide it, correct its path, have it suggest things you have not thought of ... and know a bad answer when you see one. Sometimes the bad answer is the model telling YOU you're wrong. Of course it does - your best insight came from scars, and scars aren't on the internet. The consensus is the model's home turf. If you can walk it off that turf - real examples, real failures, the reasoning underneath - it comes around, and now you've got the average AND your edge working together. If you can't ... well, now you know which one you had. Take that away and the most brilliant tool on earth is just a slot machine you can't read.

So no - you don't get to be lazy. Blaming the tool because it contradicts how you feel it SHOULD work is about as useful as the loud parroting keynote. You go back to your desk, all jazzed up, and look around ... "wait, how ... can I use this here?" So how are people actually using it? Is it all just a bunch of bullshit?

It isn't.

You've met the blunt one - the real expert, not a parrot, not someone who hides their work. The one who'd tell you "yes, you are all wrong, and here's specifically why," in public, in real time. The one in your pocket won't even give you the attitude. It'll tell you "great idea" all the way down ... while handing you back the average. That should scare you more than the difficult one ever did: the readout comes wrapped in agreement now. The blunt one at least told you where to look. You can close the tab, sure. The gap doesn't close with it.

Be one of them. Or at least stop pretending the tool is the problem.

Easy for me to say, right? Fine. Next post, I feed one of my own favorite claims to the blank slate - a line I've been getting nods with for years. Spoiler: it doesn't come back whole from the LLMs. That's the point. It's also wrong.

This is Part 1 of The Blank Slate, a series on what happens when your thinking finally has to stand on its own.

Skills Over Seats: Why You’re Botching Your New Transformation Strategy with AI this time

Fri, 12 Dec 2025 00:14:47 Z

Your AI rollout has a structural flaw - and the window to fix it is closing.

You've deployed enterprise-wide licenses across thousands of employees, but six months in, utilization is stalled at 15% and renewal costs just jumped 40%. The pattern's familiar from previous transformation initiatives - but this time the financial exposure is higher and competitive implications are immediate.
You can still course-correct.

The Decision Point: Month 6

Timeline	Current Trajectory	Skills-First Alternative
Month 6	Public "AI-enabled" positioning Actual usage: ~15% Technical teams missing deadlines Renewal shock: 40% increase ($2M spent, minimal ROI)	Five experts complete focused pilot Documented wins distributed cross-functionally Measurable: 3+ hours saved per person weekly
Month 12	Escalating contract obligations Executive sponsor transitions; initiative orphaned Talent retention issues as credibility erodes	Original cohort upskilling 50 more 3-10x productivity gains on pilot workflows Documented revenue impact, justified expansion

This is the delta between your current path and what's achievable with a strategy adjustment.

Case Study: The $1.4M Adoption Gap

A technology executive recently documented a representative scenario: Microsoft Copilot deployment to 4,000 employees at $30/seat/month. $1.4M annual investment. Board approval in eleven minutes under "digital transformation" positioning.

Three months post-launch: 47 employees had accessed the tool. 12 demonstrated sustained usage.

The response? Expansion request for 5,000 additional seats.

The stated rationale: "Adoption means mandatory training. Training means a 45-minute webinar no one watches. But completion will be tracked. Metrics go in dashboards. Dashboards go in board presentations."

This pattern, spending as strategy, metrics as theater, is endemic.

Separately, J.P. Morgan's analysis indicates AI investments require $650 billion in annual revenue generation to deliver 10% returns on current buildout costs—equivalent to $35 per iPhone user or $180 per Netflix subscriber in perpetuity.

The disconnect: significant capital deployment without corresponding capability development or measurable utilization.

Organizations winning this transition aren't spending more. They're spending differently.

The Core Issue: Scale Without Foundation

Conventional approach- broad licensing as adoption forcing function- delivers 15% utilization. Alternative: deep-skill focused team to prove value in production workflows, leverage organic demand for expansion.

Capital allocation: $50K to develop five experts with measurable outcomes vs. $5M in distributed licenses with uncertain adoption. One generates ROI data in less than 90 days. The other becomes a sunk cost you're defending in next year's planning.

A Fortune 500 logistics operator executed this in Q1 2025. Five supply chain analysts focused on route optimization.

Results by Month 3: 40% faster planning, $1.2M annualized fuel savings.

By Month 6: second cohort training.

By Month 9: CFO inquiring why other divisions weren't matching pace.

Current Market Performance

Recent research reveals stark bifurcation:

MIT 2025: 95% of enterprise pilots generate zero measurable P&L impact
S&P Global: 42% of firms terminated majority of AI initiatives in 2025 (vs. 17% in 2024)
Gartner 2025: Organizations prioritizing skills development show 2x+ likelihood of reaching mature implementation with sustained ROI

The pattern: high-visibility launches without capability development, followed by quiet shutdowns. Attribution shifts to "culture" while key talent departs for competitors who executed foundation work.

Six Strategic Adjustments

1. Target High-Impact Applications First

Identify specific operational bottlenecks. Define success concretely: hours saved, revenue generated, error rates reduced. Honestly evaluate team capacity to execute within 90 days. High performers need clear understanding of both AI capabilities (rapid iteration) and failure modes (confidently incorrect outputs). Without this, you're funding frustration and flailing of your top people.

2. Develop Prompt Engineering as Organizational Capability

Performance gap between basic queries and structured prompting represents the difference between marginal utility and transformative value.

Basic: "Summarize this data"

Structured: "Analyze Q3 enterprise software sales. Summarize: (1) deal velocity by region, (2) discount patterns above $100K, (3) win/loss themes. Format as executive brief—3 key insights with metrics, flag data gaps. For a deeper example, go here.

Organizations treating this as learnable skill - context + task + constraints + format + examples, achieve 5-10x output improvements, and more. Those approaching casually dismiss AI as "not production-ready" when the constraint is input quality, not model capability.

3. Diversify Model Selection Strategically

Single-vendor approaches create unnecessary constraints. Claude demonstrates superior performance in complex reasoning for articles and writing. Gemini excels at code and massive contexts. Grok is good at the latest and greatest ideas and concepts. Model capabilities vary significantly by use case. Test aggressively across vendors for your workflows. How you use it and the value you get will vary.

When DevOps develops a prompt saving three hours weekly, Product should know within days. When development can deliver 5x stories, devops and the business should know within days. Establish distribution channels - dedicated Slack spaces, demo sessions, searchable documentation or...ORRR accept each team independently rediscovering solutions.

5. Conduct Vendor Due Diligence

Many "AI-powered" solutions are thin wrappers around foundation models with significant markup. Investigate technology ownership, pricing volatility, exit costs. Critical question: What's our operational exposure if this vendor quadruples pricing or gets acquired?

6. Plan for Continuous Capability Development

Model capabilities evolve weekly. Six-month knowledge stagnation creates meaningful competitive disadvantage. Budget for quarterly refreshers, not just launch training.

7. Bonus. It's not just for software

Yes, the SDLC side of the house will be at the forefront of this, but that does not mean you cannot use the patterns and idiosyncratic knowledge of your organization to your advantage everywhere.

Implementation Framework

Identify Change Agents – Who's already maximizing AI quotas? First cohort identified.
Launch Focused Pilot – Fund agents, target single high-pain issue, surface blockers within weeks.
Enforce Rapid Win/Kill – Month one: measurable metric movement or project termination. No zombie initiatives.
Establish Metric Accountability – Demand 50%+ utilization. Require documented improvements within 90 days. Quarterly reviews, public scorecards.
Assess Organizational Prerequisites – Clear goal-setting and problem-solving cultures adopt efficiently. Political friction and risk-aversion amplify existing dysfunction.

Execute this and payback manifests in weeks. Miss the window and you're documenting failure for next year's planning.

Scale from demonstrated wins, not strategic assumptions. Then, and only then, go full send.

AI Retired

Sat, 19 Apr 2025 18:20:49 Z

From the Farmer Effect

Back in 2016, I coined “The Farmer Effect” after telling a frustrated dev team, “Let’s all quit and go be farmers.” The joke hit a nerve I wasn’t expecting. Even today, on occasion, I’ll get a message to the tune of “farmer effect hitting hard today man!” so that is still alive and well. But now I’m noticing something …different. And it’s AI driven. In tech, we have had a front-row seat to AI. When AI “burst onto the scene”, I would joke how terrible it is, being less than helpful, pointing out an extensive list of things it was missing. From glazing over proper patterns in code, grossly simplifying concepts and approaches, sometimes being outright dangerously wrong… It was easy to laugh at. Now? It’s getting better. A lot better.

So What? A lot. The amount of effort to find pretty damn good, deep knowledge has compressed down into minutes. What takes you a full day can be done better in under 2 hours. Even for me, it’s becoming way easier to have AI “do the thing” I want it to do. It doesn’t take much.

With this newly freed up cognitive load, the joke of “when AI takes our jobs” has shifted. It’s not about when AI takes our job, it’s what are we going to do with the spare brain power.

AI Retired.

The same draw that once made us daydream about farming now pushes us toward skills that can’t be promptly replaced. Looking in first, I noticed my own behavior shift. Instead of another AI conference, I signed up for a car detailing master class. Why? I have no (paying) customers. For me, it’s a 1:1 craftsmanship carryover - I have an eye for it, I’m good at it, I love the process, the science, the art of it, people appreciate it …and an LLM cannot detail your car. It also has a hard time explaining it incase you were wondering.

The original Farmer Effect was about digital burnout and a human need to do physical things. AI Retired is about finding your irreplaceable human value. Tap into the same primal need for tangible creation, completion, and craftsmanship—except now it’s not just about sanity and balance, it’s about what will you do next? The line between hobby and hedge bet is blurring fast — and that’s ok!

So are you AI Retired? What’s your AI Retirement plan? What physical, hands-on skill are you developing for when “AI takes our jobs”? Maybe it’s farming…powered with AI.

The Path of Truth Tellers is Littered with Dead Scapegoats

Fri, 11 Oct 2024 01:59:33 Z

Wildfire Labs posted an article a few days ago that directly encourages the need for someone to tell you, in my words, “that’s dumb, don’t do that”. The catch is, that comment may have years of reasons behind it. Reasons most people don’t want to hear, understand, nor believe. That’s completely fine! You probably already fired them anyway by now. Or dismissed them, forgot to respond, got busy …all the excuses I’ll cover. Ask me how I know.

Anyway, here’s a bit of a view from the other side.

Steps you will fail Embracing Truth Tellers

Self-Honesty is Lacking: It’s fashionable to say, “I have imposter syndrome” and be a victim. It’s an excuse. Change your language, be intimately honest with yourself …there’s your truth. Only then can you bring in someone else’s.
Ugly Baby: It’s not easy to be told your baby is ugly. It is. Good news -- it’s early and it’s time to find out what your baby is good at and turn them into an Olympian.
The Idea: In complete puppy love with your idea? How many people have you known they weren’t right for each other, and they wouldn’t listen because they’re in love? Now that’s you… and your idea.
Polite vs Honesty mismatch: “I love this idea, it’s SO great!” is polite. Honest is “This has at least 100 competitors, how and what are you doing differently?” We get it, it’s the comment you want to hear in a crowd …so plan accordingly and follow up.
The words: We tell you this because we really do care. Not about your feelings and short term strife, but you, your success and what you are building. Don’t forget that.
You are not ready for a Truth Teller: They come in, give you the beans and your response? Freeze, crawl back into the safety of the chamber of yes and pretend it never happened.
Ultimately, it’s up to you: It’s your company, your effort, your sweat, blood, sleepless nights and moments of euphoria.

All that said, one point they made on this, is spot on and if you’re a founder, you should do this, A LOT.__ Regularly seek feedback__. Not fake feel good “feedback” either. It’s invaluable, but you, yes you, must know where and when to ask for it… and prepare for what they have to say because you probably won’t like it, but need it all the same.

You Don't Remember Us

It's thankless and forgettable. I've seen companies pivot to success or dodge fatal bullets because someone like me picked up the phone and delivered an uncomfortable truth. Here's the reality check:

That investor call that made your Series A actually happen? The one where someone told you your pitch was garbage and helped you rebuild it at 11 PM? Yeah, that was three weeks before you "figured it out yourself."
Remember that "gut feeling" that saved you from that catastrophic partnership? Funny how you forgot the two-hour call where someone walked you through exactly why it would implode.
That brilliant pivot that saved your company? Somewhere, there's a truth-teller who got ghosted right after they forced you to see what you didn't want to see.

We're the antibodies to BS in the startup ecosystem - we do our job and get forgotten. That's fine. We didn't do it for the credit. But here's the truth about truth-tellers:

We're the equivalent of that friend who stopped you from drunk driving - essential in the moment, awkward to acknowledge after
Our value often only becomes clear in retrospect, long after you've written us out of the story
We measure success in disasters avoided, not credits received

The ultimate irony? The better we do our job, the more "obvious" our advice seems in hindsight. Because once you see it, you can't unsee it. And that's exactly why you forget us - the truth, once seen, feels like it was always there.

But ask yourself this: If you can't remember who told you the hard truths that saved you, how many are you ignoring right now?

Are You Parroting?

Fri, 04 Oct 2024 00:21:56 Z

Stop Parroting Leadership Advice

(You're Doing It Wrong)

'Leaders eat last!' they parrot enthusiastically, while shoving to the front of the lunch line, giving you a smaller cut, leaving for that 3 week vacation and don’t forget the holiday party you’re not invited to. Welcome to the world of leaderbullship (ahem) theater, where everyone's memorized the lines you’ll remember (I’m batman) but nobody's read the stage directions, much less know what the whole damn play is about.

With all the different patterns and “be better, do this thing!” out there, I’ve been noticing a …trend. It’s a trend that hits both sides, good and bad. The good being that people are reading, hearing, and observing seemingly better behaviors - "Leaders eat last!". What could possibly be bad about that you ask? The application of it is just …parroting -- the act of just repeating what was heard and dare I say, without much thought to what is being said.

I see far too many people skirting the effort it takes to apply, or at least dissect an idea into their own. Yes, it's a good thing to add more tools in the toolbox but blindly buying tools and throwing them in a box does not a craftsman create. Throwing these concepts into a drawer, feeling prepared when all they have is another hammer looking for a nail. No matter how hard you squint, those aren't nails ...and they're not looking for a hammer.

The 911 Problem

For example, and stick with me on this, I'd like to think during an emergency, everyone knows to call 911 in case of an emergency. Most will hear that, nod, and not give it another thought. However, there's a catch to this. During some emergency medical training I took (ok, I’ve taken it 4-5 times) there’s a phenomenon (bystander effect) when someone yells out “someone call 911!” …and no one does. Assuming they’re not on their phones, they look at each other, deciding who should call 911. We watched several videos showing exactly this happening, in REALLY bad situations. Situations I'd expect people to know that one thing to do - call 911. It doesn't happen.

Why it doesn’t work

Instead, it's instructed and practiced for us to call on someone, anyone, ideally looking at you and directly point them out -- “YOU, yes you, call 911”. Even if that person has no idea what is going on, giving a direct call to action is far better than expecting someone to act. This is on top of everything else happening around the situation. To be frank, there's a LOT to it, but that simple understanding is a big jump in being effective.

Parroting to Practice

What does this have to do with being better? Not only being able to parrot "call 911!" but adding the layer of "YOU call 911" ...it changes the actions, the outcomes and by extension, the experience when it isn't just parroting what you saw on TV.

We already took a shot at “leaders eat last” so let's take another example that every 'thought leader' loves to parrot: “Does anyone have feedback for me?” …and you get crickets.

Without question, it's good to get feedback (even HBR did a write up on how to not suck at it), but like saying "someone call 911" it doesn't work that well by itself and there's a lot more to it. Digging deeper into "call 911", it's a big jump to be more direct. “Scott, you’ve been at this for a while, where can we do better?”. Scott's been at this longer than anyone and I REALLY want him to call 911 ...me. If that doesn’t get the ball rolling, try the negative question – “I’m not feeling good about this, where will it all go wrong?” and be specific what -this- is and share your concerns.

Let’s Pile it on.

The more you look, the more of these are out there if taken only at the surface. “Move fast and break things” hasn’t been a mantra for a long time now. Does Spotify use the Spotify model? Spoilers. Target has removed the Dojos from their site. “Win friends and influence people” is a book on manipulation. The list goes on.

The Price of Cheap Signals

Reading between the lines here -- when a new concept is heard, read, maybe the first paragraph isn't understanding a concept. That's called cheap signaling. Having those tools in the toolbox requires more than just buying it, the tools and a space to put them. Knowing those tools (concepts) and when to use them (applications) helps bring on the most important thing — when those can be combined with other tools… That’s when you make pure magic.

The Real Toolbox

Becoming a master mechanic doesn’t happen by buying a ton of tools and watching YouTube. You have to, ya know, actually go out and build, fix, maintain, bust your knuckles, screw up, break shit, find out what was missing from it all, and modify it with you know. Same goes for leadership concepts. Read the books, digest them, noodle on them for a bit, counterpoint it, find the flaws with the strengths… and certainly try them out and find the lines in between.

How to Not suck at This

I don’t care what the book says – I care about what YOU think about it and how you’ve applied it. Be specific. Go back to your toolbox and evaluate what tools you now how to use.

So next time you're about to repost that “inspiring” leadershit quote, ask yourself: Do I actually know how to use this tool, or am I just carrying it around to look important and sound like a parroting “thought leader”? Take what they wrote about (it’s outdated by the time its published) …and give us all a view of what’s next.

6 years.

Thu, 14 Sep 2023 12:59:08 Z

Early in your career? Wondering why things take so long to materialize and get better? Can I tell you a story about 6 years?

Last month, I had three separate instances where people/organizations I worked with directly, come to a conclusion I had pointed out 6-8 years ago. Not just pointed out at the time, but insisted, Mandalorian style, "this is the way". I used the data and existing feedback to guide us towards what I thought set us up for success. At the time, I was overruled - some more severely than others - due to other wants and needs. So what changed? What happened? I started to dig into this a bit.

This was new data to me, in a way I had not experienced. I mean really, when was the last time you heard about something you did 5+ years ago making any kind of impact or change? This was also a bit exciting and made a pit stop to look at which kind of trap I was experiencing. Was it:

Hindsight bias (see, see, I was right!)
Confirmation bias (my advice was dead on)
Actor-Observer (they didn't understand)
Mandela Effect (remembering it wrong)
Fundamental Attribution Error maybe? (making up a story)

In case you are wondering, yes, I have these biases written down with a short summary for times when I come across moments like these - like a cheat sheet …yet these instances felt different and didn't align with any of them. Being it was an outcome I had pushed for years ago, but wasn't until now that it was … understood? Appreciated? Internalized? Was this simply the time necessary for Bloom's Taxonomy to take shape? 6+ years? really!? That's the time it takes to get a doctorate or professional degree. What the hell!?

It would certainly be easier for pure cynicism to take over -- "I told you so!" … it can't be that, the time difference was so great and I'm sure the statute of limitations ran out for such lazy conclusions. And this was a call out, without a trace of regret or anything as petty as "I should've listened". Again, more questions.

Insert the cliché … and then it hit me. Ok, it didn't hit me, I ended up talking about it enough and sorting through the whole thing to finally come up with something that made too much sense.

The motivations had changed.

They had moved to different ...things, different culture, different environment, different goals. Therefore, their experience in approaching, dealing with, and solving the problems had changed with it. I've heard over the years companies being asked "Why are you here? Why do you exist?" Most of it is a spew of pure, total bullshit — a weak attempt to create a collection of words, lacking merit and any tangible meaning to have people smile and nod during speeches. It's no different than a player who is brilliant on one team be completely terrible on another.

Now, this is way clearer to me than ever in meaning, importance, belonging and seriousness. My mistake? I had missed the mark entirely on how to convey how fundamental this is. So now, selfishly, I don't want it to take another 6+ years for others to really appreciate ...which is something I have to work on. How far would they be along if I was able to get that message across? What would they have accomplished?

How do you price your product? A real example.

Mon, 31 Jul 2023 18:34:56 Z

Not long ago I was working with a very small company, maybe 8 people total, and the big question came up, very hard question to answer, especially when it isn't a thing doesn't exist...

What do we charge for this?

This is a huge problem, a good problem, and one that if you solve it incorrectly either leaves money on the table (they would've paid more) or lose a sale (too expensive) – both not great outcomes. So how do you know, really KNOW what the best price point is ...for something that hasn't even been sold yet?

Searching around the ole internet, you'll find a lot of strong opinions on this. From limits (never charge more than X) to steadily increasing (raise it until they say no!), make it a percentage (always xx% or more!) and this post is not that. It also won't solve everyone's product pricing dilemma although it should help. What this is -- a real example of how this small company not only landed on a price, it was backed up by actual data (and money changing hands!) and also solved for "what should we build first?" implementation of this product.

First off, we knew what it cost to produce the thing. Let’s say $25 each. So we knew we had to charge more than that. Also, due to customer interviews, our demographic was more niche so an assumption was we could charge a lot more than $25. But how much more? Could we charge 50, 100, 500? How many of them at a time? What could the market allow? What WOULD it allow? We went back to the customer interviews.

During several of the interviews a dollar amount came up. This was important because, unsolicited, the customers were giving us a range they expected. Bonus, it was above the $25 it cost. Way above. So that gave us very loose, almost subjective evidence our first assumptions were in the right direction (niche, and high value). Most interviews have a problem of leading the witness and giving the customers a range -- but this? This was a customer saying if it existed, right now, they would pay X.

This was solid gold, and we took the extremes, 50-1000 …and did another round of interviews with qualified buyers. The answer we got was around 6 for 250. Was this number real? Would people actually pay this amount or was it just a polite, courtesy number? The business side of the house pushed -- “People want this, they love it! We need it done so we can sell it!” So, I issued a challenge.

Call up the last 10 people and take their money.

Four (!!) people put their money down, each was completed via manual process, start to finish. Each of the 4 customers were beyond happy and started to tell their friends and introduce us.

We now had a real number to start with, knew exactly what to build/automate and the customers were on our side. Wins all around and stronger evidence we were on the right path! We ran with this immediately (actionable data!) and started looking into what almost everyone does, create tiers of offerings, which we did. 100, 250, and 500. With a bit of that anchoring, we expected customers to pick the middle one – and that was the assumption we were really testing now.

All of this took a few weeks, thanks to a highly engaged team that had no problems reaching out to potential customers, asking them some questions and reporting back. Oh, and as for the various tiers? We were wrong, an overwhelming percentage went for the top tier, signaling they wanted more. A wonderful problem to have.