I had an awesome 2003 at IAC.

I started in March as a Systems Administrator, and got promoted pretty quickly (to SENIOR SysAdmin). In early 2004, I received a largely positive review (my first corporate “performance review” ever) from Evite’s head of systems. He was a smart, innovative guy and a nice person, but was not particularly interested in communicating (at least with me). I got a couple of notes about my performance that I found opaque, didn’t take particularly seriously, and didn’t remember later.

I had an even better 2004, and in early 2005 I got promoted again — this time to Director of Operations, reporting directly to John Foley, head of the Evite business unit. When we had our review meeting, John seemed to take the “process” about as seriously as I did. I mean, I’d gotten promoted twice in less than two years, right? In the little conference room, John was just breezing through the whole thing. On the printed HR rubric, John had checked the boxes: 5s for this-and-that; couple of 4s (because hey, they can’t all be 5s, right?). His written comments were sparse (“Email delivery up 40%”). Easy, breezy, collegial. Ten minutes, max.

Among the sea of high marks, John had also ticked one single, solitary “2” for me. Being the competitive psycho that I am, that 2 received my full attention. I got a 2 on Leadership? But I’d just been promoted to a significant leadership position? By you? So confused.

In the written comments box, there were three words and a period: “Know your influence.”

John Foley, ever the master of the moment, let the 2 hang in the air for a few seconds. Finally, I asked, “What does that mean?” John went on to explain in his kind-yet-direct, avuncular style, that I probably didn’t realize my promotion had changed me. Not the “me” that I knew — but the “me” that others saw. I had established a bit of a personal brand centered on fun, jokes, sarcasm, occasionally pranks. I was the funny guy (I thought I was a funny guy). You need to know, Foley explained, when the sysadmin says something biting to a product manager or customer service rep, it can be heard as funny or, heck, ignored. But when the Director of Operations makes the same remark, it can ruin someone’s day, or make them wonder if their job is in jeopardy.

Whoa. Know your influence.

At all times, it is incumbent upon leaders, John went on to explain, to be aware of their impact on others. Eyes are watching. Ears are listening. Even when you think you’re just having a normal conversation, humans are deeply wired to interpret social interactions through the lens of hierarchy and status. It’s a completely unconscious instinct that cannot be defeated or re-wired. And when you’re a leader, you can leverage these dynamics as sources of strength for you and those you lead — or you can diminish your impact by unwittingly squandering or abusing your influence.

Later that night, I realized the real mindfuck of it all: John had taught me this most important of leadership principles by his literal example. He knew I would focus on the one negative mark in a highly positive review; he was aware of his personal level of influence on me; and he knew no lesson would so quickly and comprehensively increase my impact. Like a matryoshka doll of leadership lessons.

I wonder if Foley knew I’d remember this moment for the rest of my career. Every time I had a boss; every time I was a boss; whenever I interacted with a CEO, from an entrepreneur to a Bob Iger; whenever I stood at the front of a large room, whether or not I was speaking; certainly every time I gave (or received) employee feedback.

Know your influence.

When you understand influence, you measure leaders differently. The best ones are extremely aware of their impact. Bob Iger, Barry Diller, Scott Flanders, Jimmy Pitaro — I witnessed each of those four CEOs wield influence in ways both subtle and direct, leveraging wildly different personal and communication styles to generate similarly far-reaching organizational impacts. And when I’ve seen leaders failing, self-awareness has almost always been among their blind spots.

John Foley was the perfect first “real boss” for me. I’m so thankful I got to watch him work before he became “the” John Foley — though I am pretty sure he’s still the same guy. Foley taught me so many other lessons I carry with me everywhere, like:

• Lead from the front (versus from “the pack”).

• Don’t give people too much feedback all at once. (Even the most growth-minded people can only work to improve one or maybe two personal qualities at a time.)

• Remember that everyone thinks they’re a good person, doing the right thing, and they are not purposely trying to block your progress. (If you treat every interaction this way, navigating corporate obstacles can be a lot less frustrating.)

• Develop techniques to gently end conversations when productive time is tight. (John kept a toothbrush at his desk. It was amazing how often he decided the current moment was exactly the right one to head to the restroom to work on his oral hygiene).

I’d arrived at IAC in March of 2003 after years of bouncing through dot-bomb cycles at entertainment-adjacent companies — desktop support, server admin, UX, front-end coding, every job imaginable. I had never used the word “career” before. That’s what IAC gave me. There is no doubt in my mind that working at IAC permanently and positively changed my life. And I have John, and my colleagues on the team he curated and led, to thank for so much of that trajectory-altering change.

Whenever people ask me for career advice, I stress the importance of finding leaders they want to work for. Leaders who lead from the front. Leaders who know their influence and use it to enrich employees’ perspectives, careers, and lives.

Leaders like John Foley.

Somewhere in 2007, Jay Herratti, my new CEO, freshly sent from corporate, was shopping for a new CTO. Obviously, I thought, it should be me. I told him so directly: I’ve hired this great team, Jay. We pulled a backend and data migration program out of a death spiral, and delivered a fully new stack built on tech from this century. I’m getting invited to speak at conferences. The team and I are generating major open source commits and getting noticed across the company and the community.

Jay listened to all of this, and he very calmly responded: “I think you’re confusing achievements with results.”

I was so mad.

I was flustered and frustrated by this take on my and my team’s hard work, late nights, and inspired innovations from the past two years. How could he not see the progress we’d made?

Jay Herratti and I never really clicked.

It’s not totally fair of me to say that. In 2007, Jay was sent in from the corporate leadership team at IAC to replace the unit CEO who had hired me and taught me a lot over my two years at the Citysearch business. And Jay was sent to improve growth and profitability of a business that hadn’t shown much of either, in a market that had recently seen a ton of competitive disruption. In the past couple of years (the time I’d been with Citysearch), Yelp had grown massively — eating our consumer lunch, so to speak. And the merchant (i.e., revenue-producing) side of our marketplace/media business had struggled to compete with new entrants who were much more aggressively performance-oriented, and much less concerned with the consumer experience. We were stuck in the middle, which is a tough place to be as a marketplace business unless you’re executing at a very high level on both sides.

In my mind I was a leader, driving change and improvements across the business. I was really proud of what we’d delivered in my two years running the software engineering team: a near-complete reboot of the team and its previously somewhat toxic culture; faster innovation through a rollout of Agile development; closer partnership with the product and content teams; a backend migration with a fully-modernized data model; and a full website redesign on a brand-new, modern technology stack. We’d moved from a legacy mod_perl environment to the latest and greatest Java Enterprise stack.

To Jay, on the other hand, I must have been yet another inherited executive to evaluate at a business struggling to deliver growth. I was in my first “head of” engineering job and quite high on my own exhaust. Jay felt like he needed to bring in more of a proven CTO, which drove me absolutely crazy. He brought in a consulting CTO from another sister company to meet with the team (i.e., me) and help him interview CTO candidates. He picked one; not surprisingly, perhaps, we didn’t click, and I found another job (my most fun job ever, but that’s a different story!).

Twenty years on, that one line — I think you’re confusing achievements with results — has stuck with me more than just about any other. Because in that moment, even as I sat there flustered, I kinda knew he was right. I HAD confused achievements — the team, the code, the features — with the lack of results: the business wasn’t growing. Traffic was declining. The business model in our market was changing rapidly, and we were losing — and here I was trying to brag to the new general about all the weapons systems I’d developed.

This conversation with Jay is one of a handful that led me to move more into product and the management of the P&L and away from pure engineering. I needed to develop an understanding of the business from the outside in. I needed to connect improvements in technology to business outcomes. I needed to learn that every dollar we spend, every action we take, has to either save money or (preferably) make money. (In my later career, I’ve gravitated toward roles that grow revenue rather than optimize costs).

So, while Jay and I were not set up to get along famously, I think about him pretty often. Any time I’m enamored with some piece of my vibe coding, or a clever new product idea, or even a successful Big Launch — I stop and consider, “Am I confusing achievements with results?” This question is more relevant than ever in the era of generative AI; it is easier than ever to create dazzling achievements, but the signal-to-noise ratio can be staggering. Even when using Claude to create insights and dashboards at blinding speed, we need to ask, “Did this AI output have a measurable business impact or did it just look impressive and give me something cool to show at the next meeting?”

* This article has been updated to reflect 2007 as the date of this conversation. I had mis-remembered it as 2005. (The hazards of getting old!)

With apologies to Ben Thompson, it’s easiest to think of the evolution of the “computer” (intentionally vague and hand-wavey classification by me) industry in terms of the relative importance of specific actors in the buy-side food chain:

Apple and Microsoft are still in pretty good positions relative to their respective markets and buyers; but for purposes of this story, I’m happy to entertain the idea that the GenAI companies and large hyperscalers have become the dominant sellers in this market era. They are certainly the most talked-about by the tech-and-business media-industrial complex. (Including little ol’ me).

I love great products that feel well-made and well-considered; and that’s almost never been the driving force at Microsoft. (My favorite IT dad joke is “if Microsoft made a product that didn’t suck, it would be a vacuum cleaner.”) But Microsoft has been extremely good at pleasing their target buyers: IT departments who are so often over budget and under-staffed. If it’s explainable to the CFO and easy to manage, it wins. Consumers (and people of taste) are simply not part of the program.

This is why they lost to Apple in the war for the next era: actual users chose the iPod and then the iPhone, much to Steve Ballmer’s bewilderment. These customers didn’t mind paying more for a better product. Apple’s care for and vertical integration of not only the physical product, but of the user experience, were now the defining benefits for the target buyer. Mediocre, half-implemented features that probably never even sniffed a designer on their way to market — those were no longer enough to win.

What is therefore interesting about the current era is that the buyer profile is shifting again. It’s closer to the old “IT department,” but with a broader set of stakeholders. IT still needs to coordinate, govern, secure, and sign off, but the Gen AI purchase is often being driven by other teams: software development, marketing, sales, and others. This generation of buyers has a lot of experience with technology in the workplace, and exposure to Gen AI products as consumers, so they are very comfortable pursuing these tools. (And we’ve learned they’ll use them insecurely and without permission if we stand in their way).

If Microsoft can communicate a clear AI value proposition (Are they competitors or friends with OpenAI? Frenemies? Agnostic? Is “Copilot” just 2020s-speak for “Clippy”?), they are the biggest potential beneficiaries of the SaaS-pocalypse. Microsoft knows how to create value for corporate buyers, and most buyers I know would rather get their just-good-enough SaaS software from one place / on a single bill. (The rise of Microsoft Teams is the canonical business case for this). If they can adapt to the broader stakeholder set on the customer side, and integrate the proper amount of AI, Microsoft can be very successful at this game.

“I can just whip that up with Claude,” you’re saying. Yeah, maybe. Maybe you, dear reader of this post, can. But Microsoft can do a lot here.

But what about Apple, you’re asking? Apple needs to deliver AI capabilities that are valuable to their core buyers: consumers of taste, and creatives. Their best AI I can see with my own eyes is in the Photos app and isn’t even really “AI” branded: they’ve made it really easy to find what I’m looking for with search. The challenge here for Apple is going to be creating really powerful tools that don’t allow users to damage the Apple brand. Genmoji and Image Playground both show what can happen when they prioritize brand considerations over utility. They need to find ways to manage these trade-offs, or obviate them by just making AI work transparently.

The smartest thing Apple has done is wait out the capital expenditures boom. Yes, a lot of capacity-building is necessary right now, but the net present value of these investments in this generation of GPUs and data centers is probably pretty low. The parallel story that leaps to mind from dotcom 1.0 is Global Crossing. The investment thesis was eventually correct; but the ROI on these specific investments was horrendous. The Mag 7 today have enough capital to blow a ton of it on capacity; but bets of the size they’re making won’t pay off for more than one or two of them — if that.

But “waiting out capital expenditure bubbles,” while wise, is not a strategy. What will matter is what Apple does after the bubble pops.

Now, who would I not want to be for the next 5 years? Salesforce. “I can just whip that up with Claude,” indeed. Let’s see, Salesforce’s moat is workflow lock-in, and workflow is exactly what agents dissolve. Pretty good use case for Claude and a pot of coffee.

Why did I start with that nugget? To let you know it’s been a while. (I mean, that reference was current at the time). I started my career in IT (desktop support and, soon after, Windows NT —> 2000 upgrades), and now people read my resume and don’t even think I’m technical.

The contrast to the era in which I’m starting this blog…er, Substack…is staggering. The levels of abstraction and the thinking power available at our fingertips…I’ll never not be impressed by the degree of technical progress in my lifetime.

I’m writing these entries on an M4 iPad Pro. This first one, I am writing on an airplane with actual good WiFi. To think: I went to college in 1994 — the public web was pretty much brand-new; started out in “IT” in 1999; my studio apartment got my neighborhood’s first DSL connection (Pacific Bell had to send three guys out); had to switch off of Mac Classic to Windows NT and Linux in order to do real work; ran back to Mac after OS X came out; witnessed the invention and popularization of smartphones, Web 2.0, the cloud, AWS, SaaS and PaaS, social media, and now the generative AI revolution. I use a laptop daily that has 64GB of RAM; my first computer had 64K.

All that to say, I’ve developed some pattern recognition.

On this Substack, I’ll share some thoughts on where we are, plus the occasional lesson I’ve stolen from very smart bosses. I consider myself really lucky, but man, I’d love to have known some of this stuff a little earlier.

There are great tech writers out there, and great business writers — I’m not trying to be them. I hope I can make my unique perspective - an IT guy who grew up through just about every functional role imaginable to become a “P&L guy” and enterprise leader - interesting enough to read once in a while.

You might be familiar with the Gartner Hype Cycle.

Right now we are passing the very Peak of Inflated Expectations of the gen AI hype boom. It’s a little harder to recognize this time as “Inflated Expectations” — large majorities of Americans consistently say they hate and fear the technology, as companies laying off 25% of staff blame “AI” (rather than management profligacy), and Dario Amodei and Sam Altman stoke fears (of job losses and of China) in order to raise trillions in capital.

Why is it hard to see? Because, really, very few businesses have deeply adopted the technology in productive ways. And those who have - many of them are swimming in internal AI slop, created by corporate creatures who simply want to get recognized for “using AI” and simply churning out more work, more prototypes, more vibes. When the credits get used up, and the value hasn’t been created, the slide into the Trough of Disillusionment will begin.

It’s also hard to see because this is all happening against a very challenging geopolitical backdrop. And, whatever your views on policy, the domestic political environments in the US and China are trending in a direction as autocratic as they’ve been in some time. Conflict over Taiwan could fundamentally alter the AI trajectory in ways I don’t think we’re talking about very much.

From past hype cycles, I can tell you the most interesting outcomes won’t be visible to most of us until well into the Slope of Enlightenment. The defining rivalry of the Rise and Peak phases, OpenAI vs. Anthropic, will be a fun memory in half a decade, I think. And losers of one phase can always become winners of a later one (see: Microsoft, Apple).

Thank you for reading. And I hope you’ll watch this space.