I know, it’s been a while. For anyone wondering if I’d given up the blogging habit, I haven’t. I just forgot how to read for a bit.

Luckily, however, I have a 4-year old that loves Dr Seuss, so that’s gotten me back on track and no worse for the wear, except for my new penchant to follow people around like an absolute maniac, trying to get them to eat eggs and ham.

Instead of returning to form with one of the many productive tutorials I have in mind, today I rant. But I think it will be productive and even help some of you reading.

I’m going to do a deep-dive on why I think getting ‘good’ at ChatGPT (my stand-in for all LLM techs) isn’t the flex you might think, and why it’s quite likely actively bad for your career. But I’ll also offer my take on what to do instead, that will be good for your career.

Before that, however, we’ve got a lot of ground to cover about who, exactly, this advice is for (digital technicians) and how, exactly, commoditization works in the form of a commoditization lifecycle.

Caveat 1: “Life-Good” vs “Career-Good”

But before either of those caveats, let me caveat the idea of “don’t get good.”

In a vacuum, being good at something is better than not being good at something, and ChatGPT is no exception. But career development doesn’t take place in a vacuum.

To understand the distinction, ask yourself whether you’re good at shoveling dirt. Are you completely inept? Okay at it, you guess? A shoveling craftsperson?

In a vacuum, if you could wave a magic wand and be one of these 3 things, you’d obviously choose the latter. Who wouldn’t?

And that skill might even matter to your life. If you have 15 minutes before the police arrive and you need to bury some critical evidence, then being the Michelangelo of shoveling may represent the single most important skill you ever acquire in your life.

But that doesn’t mean you should try to define your career around it, or even involve it in your career as a first-class goal.

Caveat 2: Technicians and Their Meritocracy Mythology

Speaking of careers and goals, let’s define the term “technician.” I’m using this term, as coined by Michael Gerber in his book, the E-Myth, Revisited, about entrepreneurship. Here’s a longer read about the personalities, but briefly:

• Entrepreneur is the visionary that looks at the future, imagines the possible, and strikes deals on behalf of the organization.
• Manager is the planner, who minds the P&L and looks to maintain a stable and sustainable status quo.
• Technician is the doer, who values craft and tends to live by the motto, “if it’s worth doing, it’s worth doing right.”

Gerber’s book is a fascinating and eye-opening read (if a little woo-woo at the end for my personal taste) and I recommend it. But the tl;dr of the early chapters is that most people who start businesses or freelance practices aren’t really entrepreneurs; they’re technicians who have an “entrepreneurial seizure,” usually of the form “you idiots are all doing the thing wrong, so I quit and I’m going to go off on my own and do the thing the right way.”

For our purposes today, the manager and entrepreneur aren’t relevant, mainly because neither archetype is in danger of LLM-flavored commoditization. But the technician — especially the digital technician — sure is.

To make it concrete, technicians are, broadly, individual contributors (ICs) that sell labor in the market and create concrete deliverables or, at least, billable services. Think software developers, content writers, graphic designers, accountants, etc.

Another way to think of technicians is as people with a (digital) craft. They may or may not celebrate (or, arguably, fetishize) the idea of themselves as craftspeople, but it’s generally their mental model for their work.

Busting The Meritocracy Myth: ‘Better’ is Just “Cheaper, with Extra Steps”

This mental model gives rise to a pervasive, understandable myth about the nature of their work and its value. Here’s the myth:

Being good at your craft is economically valuable.

Yes, you’re reading that right. I am calling that statement a myth. (I’ve written about this for years, at length in articles like these, if you want a deep-dive).

To demonstrate, rather than lengthy explanations about diminishing marginal returns or game theory around fungible labor, here’s a realistic hypothetical conversation. These days a lot of my readers are marketers, so that might go over better.

Client: why should I pay you for {blog post, code, graphics, etc} when I can find someone on Fiverr to do it for half the cost!?

Technician: well, you see, because I’m better than they are at the thing!

Client: who cares?

Technician: you should, because if they do it badly, then you’re going to need to hire me anyway to do it right, and it’ll take longer and cost more.

Client: Oh, so in a plot twist, you’re actually the cheapest option from a total cost of ownership perspective — sold!

Technician: Uhh… wait a —

Client: Pro tip, next time just say immediately you’re the cheapest.

This understanding is critical framing for the rest of what I’m going to go on to talk about. This “hey, wait a minute” fusion of “cheap” and “good” is one of the main tells that your labor is approaching the event horizon around the black of hole of commoditization. And you, dear reader, are being spaghetiffied without realizing it.

Context: The Commoditization Lifecycle

You’re in trouble, but the beauty of you sitting at the event horizon is that you’re absolutely not going anywhere (literally, physics-wise, from an observer perspective). So let’s add one more bit context before diving into the problem with where you’re positioned with respect to the great commoditizer, ChatGPT.

Going a bit meta, here’s an AI-synthesized definition of commoditization that works well for the purposes of this post.

[A] process where products or services become increasingly similar, interchangeable, and price-driven, losing their unique features and value.

With digital technicians, we’re talking specifically about digital services and labor. And those don’t become immediately commoditized. Instead, it happens gradually over the course of time in a process that I’ll call the commoditization lifecycle.

Here are the stages of that lifecycle, with respect to the nature of the work done by humans, thus producing labor and services.

| | Nature of Work | Who | Example | | | ––––––– | — | —–– | | 1. | Innovation | Entrepreneur | Founding “Uber, but for Socks” | | 2. | Skilled Labor | Technician | Programming | | 3. | Unskilled Labor | Virtual Assistant (VA) | Situational Data Entry | | 4. | None | A Computer | Wix/Weebly/WordPress |

Website Construction: A Full Lifecycle Example

To really understand how this plays out over time, let’s consider the evolution of work from innovation all the way down to complete automation. And for my example here, I’m going to zoom in on the Wix/Weebly/Wordpress (Webflow — why do all these things start with ‘W’?) example.

1. In the late 1990s, when the internet was a baby, building a website for commercial purposes was the wild west, with no playbook for success and tons of risk.
2. By the mid 2000s, building a website was something a skilled software engineer, like me at the time, was doing. Barriers to entry were high — I had 2 CS degrees — and the labor required a good bit of expertise and judgement. Not for the unskilled or faint of heart.
3. By the 2010s, CRUD frameworks like Rails and DIY options like WordPress had dramatically lowered the barriers to entry and allowed self-serve options, increasingly commoditizing the labor of building a website.
4. Today, I have no idea why anyone would “build a website” in the way they used to in the 90s and 2000s, unless they were nostalgic.

Over the course of roughly a generation, the skillset and labor around “build a website” underwent the entire commoditization lifecycle.

Interestingly, programming itself stayed mostly in row (2), with a dash of (3), as this took place. But this is because programmers stayed one jump ahead of the commoditization breadline by moving on to solve other, distinct problems. This programmer-breadline dynamic is going to be very important to remember later, when I’m explaining the exact problem with getting good at ChatGPT as copium.

Good business, by the way, is what drives this cycle. If you run a business or an ops group, your charter should always involve moving work down the ladder, innovating, SOP-ing it, and then making your SOPs reliable and predictable enough for automation.

The Great Commoditizer: What ChatGPT Actually Represents

Now that we have the lexicon to look directly at the problem, let’s finally talk about ChatGPT.

Going back to the physics metaphor around black holes, think of historical commoditization as a star with a gravitational pull. As a category of work becomes increasingly mainstream and SOP-ed out, that work slides down from (1) to (4) in the lifecycle, subject to the gravitational pull of commoditization.

ChatGPT has turned that star from a source of gravitational force into a much more powerful black hole of commoditization from which it’s harder (and eventually impossible) to escape.

Crucially, the black hole can reach WAY further up the skill chain, insta-commoditizing knowledge work tasks that used to be 10-20 years away from commoditization at any given time. The moat that had persisted around traditional digital technician skillsets was vaporized, and, with it, the traditional tactics for staying in the relatively comfortable stage 2 of the lifecycle.

What ChatGPT really represents is the smashing together of stages 2-4, leaving only stage 1. (At least, on the surface, and in current public perception. This ignores the current, glaring weakness that these techs aren’t actually very effective in a lot of stage 2 work, currently.)

An Own-Goal: What Getting Good at ChatGPT Actually Represents

So let’s think, then, about what becoming “good” at operating ChatGPT represents, given that ChatGPT is essentially a massive, rapid technician-commoditization engine that (theoretically) allows anyone to self-serve at what used to be your skilled labor.

To get “good” at using ChatGPT to execute your tradecraft is thus to get good at commoditizing your own labor and your craft. You’re becoming an expert in reducing the value of your own labor to $0.

And, while that might be an absolutely savage thing to do if you intend to do it, I don’t imagine that most technician-crafter types flip from “I want to be a writer” to “I want to automate writers and writing out of existence.” To illustrate the own-goal, let’s do another hypothetical conversation between Achilles and the tortoise.

Technician: check it out, I’m getting REALLY good at ChatGPT!

Client: I don’t care about that even a little, but thanks.

Technician: you should, because with my new skills, I’m writing blog posts for you twice as fast!

Client: Sweet! Why didn’t you just tell me you were reducing your prices by 50 percent?!

Technician: Wait, no —

Client: I was going to fire you anyway, since who pays $100 per hour blogging labor anymore, amirite? But now that my $100 for your hour gets me 2 blog posts at $50 each, I’ll fire you a little later. Making your work half as valuable was a great move! I mean, a great move for me, but still.

(Admittedly, part of the problem here is attributable to the absurdly perverse incentives created by hourly billing, but the commoditization issue remains. Read more about hourly billing on Jonathan Stark’s site, if you want to go down that rabbit hole.)

Think back to the earlier red flag of your labor’s commoditization, wherein “good” and “cheap” fuse together. For increasingly commoditized labor (e.g. participating in RFPs), the “good means cheap” paradox has always existed.

But adding the great commoditizer, ChatGPT to the mix, you take that dynamic, put it on skis, and shoot it down the mountain with a missile launcher. You’re proudly showing off how easy it is for anyone to do your erstwhile job themselves with just a smidge of “prompt engineering” as the only, tiny barrier to entry.

Getting “Good” Won’t “Save” You, Either

20 years ago, when I was a fresh-faced software engineer, and before years of management consulting eradicated every last bit of humanity from my soul, I was the engineering lead on a piece of pre-Workato software that connected mail sorting billable data to back-office accounting systems. This was a traveling act, with sales engineering responsibilities included in my role.

I can recall going out to client sites all over the US and supporting the installs, including helping train customer data entry personnel in using the software. Gradually my professional innocence died as I realized that these people were all going to be laid off. But I do recall that they reacted in one of two ways:

1. Probably 75% of them were completely checked out, either realizing they were going to be laid off or not really caring about anything that happened in their day to day.
2. The other 25% were absolutely dialed in and committed to learning the tech. Their jobs were also going to not exist anymore, their enthusiasm notwithstanding, but to this day I like to hope that they at least landed somewhere productive at the shops.

The lesson here, dear reader, is that the great commoditizer is going to eat you, whether you defiantly flip it the bird or offer to help round up others to toil in its sugar caves. So if you’re going to go out, you might as well go out like John Henry, dying with hammer in your hand.

Why LLM Proficiency Superficially Seems Like a Marketable Skill

Aside from the anthropomorphic appeasement angle embodied by Kent Brockman, there is another, much less obtuse, reason to think that proficiency at the great commoditizer is a good career hedge. At this point I’m going to fire Chekov’s gun and call back to when I said programmers staying ahead of the breadline would be important.

Your mental model for today’s knowledge worker and ChatGPT is likely the programmer. But where the programmer’s canvas was “geek stuff” today’s “prompt engineer” has a canvas of their own tradecraft, or, I guess, of English language.

Today’s “prompt engineer” likely views their role with the tech as similar to the role of a programmer with a programming language. And this understandable parallel is doubtless buoyed by the rise of the concept of “agentic AI,” wherein the user becomes a sort of sorcerer’s apprentice, flailing their arms around casting spells and hurling agents at assorted workflows in a symphony of… something.

So, the logic goes, today’s LLM operator is the 90s programmer. And, just as the 90s would have been a good time to learn software engineering, the 2020s are a good time to learn prompt engineering.

Why LLM Proficiency Isn’t, Or at Least Shouldn’t Be, a Marketable Skill

I’m using “prompt engineer” a bit tongue-in-cheek, since, if it hasn’t already, the world is almost certainly going to figure out that this is kind of a terrible idea when you actually unpack it. And that’s why, broadly speaking, ChatGPT proficiency in general doesn’t actually turn out to be a good idea, even if you set out to commoditize someone else’s tradecraft rather than your own.

Notwithstanding superficial similarities, “prompt engineering” or ChatGPT operating, is actually nothing like programming, now, or ever.

The AI Companies Won’t Like the Optics

First of all, the AI companies themselves would probably be passively hostile to you touting this as a skill set. I mean, think about it. This would be like you standing outside of Starbucks, telling people that you’re a coffee ordering engineer, and you speak the secret in-group language about Ventis and Double Mocha Whatevers, and you provide a valuable service helping bridge the gap between baristas and consumers.

Before we even get to this being an incredibly weak value proposition, don’t you imagine Starbucks would have something to say about this?

“Yeah, that’s not a thing, our baristas can communicate with our customers thanks.”

As a prompt engineer, you would encounter a two-faced channel partner, who would want you to be a power-user and evangelist, but who would hate the implication of your existence: that its product needs some kind of translator when the product is intended for the end user.

Programming Is Translating, Prompt Engineering… Isn’t

But let’s now dive into the weak value proposition of this skillset compared to the programmers of yore.

Programmers, at their core, are translators. They translate messy natural language into precise constructs in first order languages and boolean/propositional logic and vice-versa. You tell them in English that you want the computer to go beep-boop, and they translate that into the Javascript and/or eventual assembly code that makes the beeps and boops.

This sort of translation doesn’t happen with LLM operator “skillsets” or prompt engineering. You’d just be translating English into… other, slightly different English, and vice versa. If any value proposition exists here at all, it’s the weakest imaginable sauce. OpenAI isn’t designing ChatGPT to need you to be good at it for other people; it’s designing it to be good at itself.

2010s Zeitgeist Aside, the World Tolerated More Than Celebrated Programmers

It’s understandable to confuse programmers and ChatGPT operators, especially now that programming itself is becoming commoditized. But you need to recognize that, historically, the world tolerated programmers more than wanted them.

They were Poindexter, and Wall Street finance bros would keep Poindexter around to make trades happen faster because they didn’t know how to do it themselves.

They would yell at him, “in ENGLISH Poindexter,” and make fun of him and hire project managers to deal with him so that they didn’t have to. Eventually, as this labor became indispensable, a certain geek chic took over, and programmers became the zeitgeist and eventually kingmakers and entrepreneurs in their own right. But at their very core, they were always Poindexter.

Now, with wholesale commoditization of programmers at large and with “vibe coding,” the Wall Street finance bros are free of Poindexter, and they can say what they’ve been wanting to say to Poindexter for a generation: “$%&# off, Poindexter.”

I promise you, nobody is looking to replace Poindexter with you, a far, far less necessary Poindexter.

Escaping the Commodification Event Horizon

There is, however, good news. Being good at ChatGPT and going on LinkedIn to be performatively good at ChatGPT aren’t your only path forward. Far from it. There are PLENTY of things you can do that don’t involve participating in your own commoditization or feeding your own tradecraft to the beast.

Instead of any of that, figure out how to be complementary to it, or, at the very least, orthogonal. And that’s what I’ll focus on in the last section of this post.

ChatGPT and its brethren are frighteningly and astonishingly good at a lot of things. But they also can’t count and keep telling people to eat a few rocks each day, so they’re hardly the Utlimate Intelligence of the Hyperion universe. There’s still a place for you, along side these techs, doing things they aren’t good at or don’t help with.

1. Be Strategic

Your first option is of the “simple, not easy” variety. And that is to become strategic in terms of your role within your organizations, or others’, as a consultant.

And I’m talking here about *actually *participating meaningfully in organizational strategy. This is not to be confused with being “strategic” in the LinkedIn sense, where you declare yourself a “strategist.”

ICs have a tendency to do this, and IC work has a tendency to drift in this direction via developmental titles and a desire to reward seniority. A software architect is a software developer, but more “strategic” or something. In the content world, people just lazily slap “strategist” onto the end and become a “content strategist,” who, presumably, can not only write blog posts, but also brainstorm titles for them.

I’m being flippant to draw a distinction. Strategy, these things are not.

If you want to see whether you’re strategic, there’s here’s an incredibly simple heuristic:

Does anyone pay you, or would they pay you to tell them what to do, with that advice as the sole deliverable?

If the answer is yes (and your advice is actually valuable), you’re actually a strategist. As I said, simple, not easy. An exercise for the reader is to brainstorm how to move toward that goal, if you want to get there (though I do have two YouTube channels with all kinds of advice on that topic).

2. Pivot Away from Technician Work

As kind of a corollary, and perhaps a tactic for becoming a strategist, you could simply stop doing technician work. Like the first item, this would function as a voluntary creative constraint and as a forcing function.

If digital technician work is subject to commoditization and you don’t want commoditization, stop doing the thing subject to commoditization.

Years and years ago I was subcontracting for a firm that did strategy consulting but was also an app dev body shop. I was onsite at a bank, as a management consultant, helping them answer the age old question “why isn’t our agile, agile?” Also there was a team of software engineers consultants.

In an exchange that seemed flippant to me at the time (at least my part of it), one of the software engineers asked me essentially, “we’re both consultants, so why do they listen to you and not me?”

My response at the time was something like:

Because you write code for them. As soon as you write code for them, you’re not a consultant (player-coach philosophy notwithstanding). You’re a developer with an opinion. And they already have an entire department of those.

Like becoming strategic, simple, but not easy. Stop technician-ing. Figure the rest out as you go.

3. Be Genuinely Interesting

Switching gears a little here, the third thing that I’ll offer is probably most helpful to people in the marketing org chart, but could help anyone stand out. (I’m really looking at you here, accountants.)

When creating content, you’re almost invariably trying to do some combination of two things: educate and entertain. Being interesting, or creating interesting content, tends to heavily focus on the entertain concern, but it can make educational content much stickier.

ChatGPT isn’t interesting, at least, not unless the user is getting their jollies by prompting it to sound like John Wayne, or whatever. ChatGPT is basically just the synthesized, median human on the internet, stripped of personality and retrofitted with a different one, artificially. The lift for interesting is entirely on its user.

Not true of you. You can carve out a place being interesting alongside it in the same way you can cultivate a readership in a world full of 101 definitional and guide SEO content.

And you don’t need to be a marketer for this, or specialize in content creation. Simply being personally interesting and having novel insights may go a long way for you interpersonally as well.

ChatGPT is only going to answer the questions you ask it. Go forth and answer questions people have yet to know to ask.

4. Be Precise and Detailed, Maybe in Regulatory Fields

Or, you could go in the complete opposite direction. (Now I’m REALLY looking at you, accountants.)

LLMs are fun and sloppy. Sure, they’ve got their quirks and might randomly tell you to drink bleach when you ask what to do for indigestion after working out, but it’s about tomorrow’s vision, not today’s bugs, amirite?!

Well, I mean, unless you work in a regulated field. I pity the foo’ that asks ChatGPT how to handle HIPAA compliance in their customer onboarding and then just does it, or that vibe codes up something on top of a database with PII.

You simply cannot trust ChatGPT to do important things unsupervised. So, position yourself as that supervision. Find a niche where stakeholders depend on you to get it right 11 times out of 10.

5. Cultivate Deep, 10x More than Median, Knowledge

As I probably mentioned earlier once or twice, at its core what these techs are really doing is synthesizing the median knowledge of the internet. And that’s a killer application for a lot of things (DIY home improvement, recipes, etc), a mixed bag in a lot of fields, especially with lots of hokum (SEO, wellness advice, etc), and limited in other areas (e.g. cutting edge nuclear physics).

This can be refined somewhat, with smaller models, trained on more highly curated data. But you’re still just getting the median of whatever they have available for their training.

So if you become far, far more knowledgeable about a niche topic that’s in demand, you’ll have a fairly well-defended career fortress. Granted, amassing and maintaining this knowledge may be tough. But presumably you’ll start with something about which you are already knowledgeable.

As a simple example, this would apply to me and the ins and outs of staffing content programs. If I were to ask ChatGPT what to bear in mind when starting up a content operation on a $15K per month budget, I’d read through going “yes, okay I guess, yes, nah that’s stupid, yes, yes…”

That’s your heuristic. Build a knowledge store in which you’re confident enough to decide whether ChatGPT is right or whether it’s telling people in your field to eat a couple of rocks.

6. Be Reliable

This is similar to the one about being precise, but with more emphasis on the dependability angle, from a delegation perspective.

Personally, I find the concept of “agentic AI” to be kind of wild. Not that I think there’s no future in it, but “highly productive, but confidently wrong 10% to 20% of the time with no humility or self-awareness, and doesn’t learn from mistakes” is one of the worst imaginable traits in a report to whom you want to delegate anything that matters. Like, I don’t think you could engineer an employee I’d be less likely to hire.

So, be that, but without the wrongness. This might be one of the best ways to neatly coexist with the tech — deploy it for the productivity, and fix the 10% to 20%.

However, I’d like to point out in the broader theme of this post that being good at the tech isn’t actually the point, and it isn’t actually relevant to your stakeholders. It’s an implementation detail. They care that you’re both reliable and productive, however you happen to accomplish that.

So seek out situations where the work delegated to you and its correct, prompt completion is important, with no room for slop and hallucinations at the end of the day. High optic, PR type situations come to mind, among others.

7. Simply Be Human

Speaking of PR, there are situations in which simply existing as a human being is a differentiator.

A while back, someone in a Slack community I participate in posted a facepalm story about a CEO somehow being busted using AI to generate a fairly sensitive company-wide communication. I forget the details, but let’s just assume it was “In today’s fast paced world, you’re all fired, clean out your desks; do you like this persona?”

Think for a moment about why this outrages you. It’s not because the bot did anything wrong, per se. It’s because a bot was the wrong man for the job, in the same way that “some meetings have to be done in person” or “you don’t break up with a long term significant other with a text.”

There are situations where the use of a bot has bad optics. Find those situations and participate in them as part of your living.

8. Cultivate a Rolodex

Another option for those of you that favor the highly interpersonal is to think about navigating your career in a way that leverages your human connections. And I don’t mean this in a scheme-y sense, but rather in the “people person” sense.

For example, an interesting artifact of having spent more than a decade in business for myself, and the majority of that time handling my businesses’ sales is that I have an enormous rolodex. If I were going to embark on a market research listening tour for a new offering, I could fill my calendar for literally weeks.

There is no LLM on earth that could replicate that. And it’s highly commercially useful, either for my own ventures or if I were to hire on somewhere as an early stage growth or COO type or what have you.

So think about your own rolodex and professional relationships and the part you play in them. What kind of career arc going forward could you build that leans on being a relationship-builder and a people person?

9. Build Intellectual Property and Join the Investor Class

This is another of the simple, but not easy, advice points. Start a business venture.

And no, technicians, for the love of God, please don’t make an info product. Those have been bordeline useless commodities for years and there has absolutely never been a worse time to try than now, when a bot can slurp in and plagiarize the whole thing on demand if you setup your robots.txt wrong.

I’m talking about starting a value-driven business.

Technician concerns are the production, and a business is the means of production. To put it bluntly and cynically, when you found a business, the technician labor vs GPT labor goes from an existential career crisis to an implementation detail of your service delivery. I’m not looking to blunder into the political or philosophical here — I assure you my opinions on those matters are not interesting — but being the one who makes the decision is inarguably a less precarious position than hoping the day isn’t here yet.

There are three things that you can bring to a nascent business: capital, labor, and expertise. If you start with labor (e.g. a services business), you’ll generate the other two for yourself over time, and be in a position to spend the rest of your career entering and exiting businesses on your terms.

10. Don’t Panic, Ride it Out

Alright, as I bring this thing lumbering to a close, I want to leave you with one last piece of advice. And that is, calm down.

For all of the breathless hype, we’re really not at, or anywhere close to, the singularity.

• The idea of humans driving cars has been dying for 10 years, and yet I’m still about to drive to pick up a U-Haul.
• SEO has been dying for 20 years, and somehow we still have a thriving business delivering services around it.
• Mainframe computers have been dying for 50 years, and yet I still have no doubt I could go back to a consulting practice where I helped enterprises navigate risks around them.

If your job dies at the same rate as most things that hypsters and bleeding edge adopters proclaim to be dead, you may well be in danger of dying of old age before your job dies of hype cycle.

Don’t get me wrong. The commoditization is real, and it’s here, and you’d do well to prepare for it. But that 10% to 20% of details that will {waves hand} be sorted out in the next version often take a whole lot of years and decades worth of versions before they’re actually sorted out.

This gives you time to breathe, collect yourself, take a long view, and chart a path away from commoditization. And that is a good idea regardless, because the world itself tends to be a great commoditizer. In our world now, the great commoditizer just has very visible (and peculiarly sphincter-like) branding.

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