Transcript
Erik Peterson: I'm going to talk a little bit about the bill. There was a lot of conversation about all the great things that we're building. I think we really have gotten to a place where we're building an enormous amount of great things, but the bill comes due at some point. I wanted to share some of the things that I've been seeing, my company's been seeing, and make some wild-ass guesses about where I think it's all going. You all can hold me accountable to that. I can tell you, quite frankly, that it's a mess. Who am I? I'm Erik Peterson. I'm the CTO and founder of the company CloudZero. I started the company here in Boston in 2016. Coming up in August, almost on 10 years. It's been a wild and crazy ride over the last 10 years. Nobody could have predicted what's going on right now, or maybe somebody did. I'm sure somebody did. CloudZero is the financial control plane for cloud and AI. I'll share some of the data. Six months ago, we noticed something interesting happening in the bill.
Rise of AI
We are here. Really, we are here. This is what is happening. It is an amazing time that we can live in that if I want a money-flaming meteor and pounding it into the earth, I can just have whatever I want to create in front of me. How much did that cost to generate? I'm going to say this a few times today. I used to say every engineering decision is a buying decision. We are now in a world where every decision is a buying decision. I need to do some research, I'm going to go to Perplexity. I'm going to write some code, I'm going to go to Claude. I'm going to build some images, maybe I'll go to ChatGPT. Before I send that email, before I finish that thought, I am putting that information probably through some LLM somewhere. That costs money. Somehow, we've gotten ourselves in a situation where every thought we have is now monetized.
It sounds a little dystopian. Maybe it's the evolution of the human race. I certainly hope so. We are here. It costs money. The bill comes due. The bill is a little crazy. We have amazing statements like this being made. How many people saw this? Think about that. Take whatever your salary is, and if you don't spend half of that salary by the end of the year, Jensen doesn't think you're a great engineer. He's going to lose his mind. I think this may have kicked off, or maybe it was right in the heart of the tokenmaxxing universe. Tokenmaxxing, what is that rot upon the world? This is single-handedly probably the most expensive vanity metric in the history of IT. It's really hard to estimate exactly what that is. It's somewhere on the order of $5 billion to $15 billion. How many people had a boss or a manager or a CEO who was looking at the AI leaderboard — they're calling it a leaderboard — to figure out who in their organization was doing what they hoped they were doing with AI.
Did they know? No. They knew for a fact that if you weren't spending money, something must have been wrong. This is the craziest thing ever. Here we are. This term, I think, was invented back in March. It was declared over in May. I think it's still going. I think we're still living this. What has happened over the past couple months is pretty indicative of what's to come.
I think AI is coming for your jobs, too. If that meteor wasn't scary enough. Last year, I would say this definitively is not true. I was wrong. Last year, I would have said, you're not going to lose your job to AI. You're going to lose your job to somebody using AI. I actually think what's happening is we are getting a promotion. It's a forced promotion. We're going to have to accept it and change. Nothing drives this point home for me more than actually a story from my past. One of my first jobs in IT where I was working at a computer support job and had a couple of nice ladies walk into my office. They said, we used to work in this office and then you people with your computers showed up. We were six of us on typewriters. Typewriters had a real feel to them, a computer, soulless.
You guys took our jobs. Typewriter has shown up in the AI era. We've got to go figure out what promotion we're going to get. I think next year we're going to be really wondering, what is our job now? It's definitely not going to be about doing the work. It's going to be probably about managing the work. Our taste might be the only thing that matters.
The Promise versus Reality
This is going to color the whole conversation we're going to have today. This is the promise versus reality. Don't worry, AI is not coming for your job. I think it's coming for your job. Don't worry, tokens are going to get cheaper. Actually, tokens have gotten cheaper but we're spending a little bit more. In fact, they've gotten a lot cheaper. AI makes us all more productive. How many people here feel more productive? I feel pretty productive. If I look at the number of lines of code, the number of PRs, the number of commits, it all is up and to the right. Some days I wonder, am I churning? We're still bad at measuring developer productivity. We haven't really quite figured this out. I think it's going to only get worse. Don't worry, the cost curve only goes down. Actually, our spend is pretty much tripled and only going up.
Storyline
Here's the storyline for today: confession, the eclipse, the inversion, the aftermath, and then hopefully some things that we can take with us after this that will help us.
Act 1: The Confession - You Can't Trust Your AI Bill, Neither Can I
I got a confession to make. I built a company that built the category, and I can't actually fully trust our bill either. I spend all day long looking at the data that comes from the cloud providers, the AI providers, random people on the street sending cost data into our system. It is a mess. Anybody who tells you that this stuff is clean and easy and it's just data is forgetting something. We all know that just data is there be dragons there. When we look deeper into the AI bill, actually, like what's behind that? Is it just inference? Is it just tokens in and tokens out? There's a lot going on inside of there. A lot of it is buried and hidden and not even ever revealed to us. It's just charged to us. At least we have the benefit when we look at the Amazon or the Google bill to see that I spent this much on EC2 and this much on S3 and this much on who knows what.
At least I have an itemized list. We have somehow reverted to the world where right now I get a bill that is the equivalent of what I've been getting from my power company for the last 100 years. You spent $500 on 10,000 kilowatt hours. Doing what? Getting what? Providing what? Did I leave the lights on? Was the oven on? AC? I don't know. Somehow, we're back to where we were 100 years ago that hasn't changed, 10,000 kilowatts, a million tokens. There's a lot to try to unpack behind the invisible, so much so, actually, that folks at the University of Maryland had to go come up with an entirely new approach to get at it. They call it CoIn, the cost of the invisible. They found that there's just a ridiculous amount of invisible spend happening behind the scenes. What you get shown on the screen isn't necessarily what you're paying for. Sometimes it's built around changes in the model, changes in the weather, changes in things that aren't revealed to us. It's 10,000 kilowatt hours. Is it because a tree branch hit the power line and suddenly the power got a little weirder? We don't know. It's actually gotten a lot worse.
Nobody agrees on the unit. If we try to look at the data that's actually coming in, nobody can agree on exactly what it is or what it means. We've got different formulas for code, for images, for audio. Some of this stuff charges us for silence. Some of this stuff charges us differently. It's all a mess. They use different terms, different formats, different schemas, different everything. It causes huge problems when you try to bring it all together. They're all random vendor implementation details. We've rolled back 100 years. The prices themselves also don't make any sense. I really want to know why o1 still exists. It's 7.5 times more expensive. There's zero reason for you to use it. There's vastly superior models for vastly less cost but it's still there. Somebody, some enterprise somewhere has an agent running in a basement that is consuming tokens that's probably keeping OpenAI afloat.
They thank you for your service. Other providers, I think Google turns off models after a year. Maybe they're doing everyone a favor. OpenAI is leaving stuff around for a really long time. Or maybe that was Microsoft. Pick a region. You'd think, I'll just keep it in the U.S. That'll be cheaper. Instead of multi-region. Multi-region sounds expensive. No, pick a region that's more expensive. Don't pick a region, you're going to spend more. That's a feature. They change how they tokenize things. Token costs go up 35%. All this stuff changes and none of it is really under your control, except maybe the model you pick. The APIs themselves, the ones where we get this data, they're broken. We don't need to tell a story about uptime and availability these days, which is fascinating how unimportant that number seems to have become if you've been a GitHub customer for a while.
It's happening everywhere. It's like the old days, "AWS is down. Let's all go out for a bite to eat." "Claude's down today. I'm not going to get any work done." When we're trying to get the cost data, daily 500s. When we're trying to get information from OpenAI, daily 500s. Cursor, one bad record in there, the whole thing just blows up. It is a mess. This is just what happened in the last 90 days. If you think that this is happening over some long period of evolution, no, it's not. It's happening in real time. This presentation actually was the hardest presentation I think I've ever had to create, because I'd write something down. Then I'd look at the information the next day, and I realized, new stuff out. It's wrong already. We didn't even have a proper API to pull Anthropic Enterprise billing data down, until March. If you're on claude.com, you could get your billing data. If you're on claude.ai, two vastly different platforms, you could not. Except screenshot it, and download a spreadsheet from their website. All of this churn, just in the last 90 days.
Act 2: The Eclipse - All Cost is Eclipsing the Cloud Bill
What is happening? It's pretty simple. AI is going to eclipse the cloud bill. Cloud and all its growth, all its craziness, all the billions trending towards trillions, if we look at just what's happened in the last couple months, that was the warm-up match to what's coming. Anthropic's like up and to the right is truly insane. Nothing like this has ever occurred before. This is the warm-up match. I believe all cloud spend is going to be absorbed by AI. There's only going to be one thing, it's going to be AI. Just days ago, all these crazy things happened. We're talking billions if not trillions of dollars here exchanging hands. Flowing, who knows where it's going? People making huge claims about how compute is going to be spent. It is an entirely different ball game. We thought cloud was expensive. No. That is a rounding error to what is getting spent right now.
I think that is going to lead to a disruption timeline that is moving faster than any of us here are prepared for. I thought I was crazy. Actually, a lot of people thought I was crazy. I started committing myself to only using AI to create code in January of 2025. By the middle of the year, I was convinced that all code is going to be written by AI. If you talk to anybody in California, they were convinced too. Everybody outside was like, I don't know. How many people think that all code in the future is not going to be written by AI? We'll come talk about that in a year. It's all going to get written by AI. I think it's going to happen faster than anyone thinks. I think that what we'll end up with is something I call the fully autonomous cloud, which is AI writing the code, AI deploying the code, AI managing the code.
It all is running in an autonomous fashion. The cloud as we know it is going away. It is going to disappear. My bet is that it's all done and figured out by 2028. We'll see. You can take the safe bet, but I don't think I've been aggressive enough. It won't be the financing mechanism. Interesting point of fact is that every AI startup combined is still eight times short of the total AI CapEx spend of all the cloud providers. There's still this huge gap. Where's that gap getting made up? I mean $80 billion here. It just seems like $80 billion is such a small number. What is going on? They're both burning cash if we look at both of the giants out there. They think about their numbers drastically different. Anthropic says that they're profitable 5% return based on how they built their numbers and built their books.
OpenAI has got a negative 122%. Crazy. They're both looking at about 80% margins on their API calls. They are making money. This AI cost crisis feeds the narrative as well. This is probably the most profitable supply chain in tech ever. These are real numbers. What you get charged and what we're paying. We're so driven to grab this right now that we stop paying attention at some point. We've seen the circle chart a few times. The circle is real. Every time I turn around there's a new box to add to it that's feeding the circle. I think as long as it just keeps flowing and spinning, we're going to be ok. Just keep spinning. Just keep spinning, we'll be ok. I hope. Otherwise, it's sticks and rocks and stones.
Act 3: The Inversion - The Cost to BUILD is Eclipsing the Cost to SERVE
The inversion is this magical thing that some CFOs have started to notice which is the cost to build is now the most expensive thing, not the cost to serve. Cost to serve was what I was spending to deliver cloud computing and deliver services to my customers. The cost to build is what we're spending to build this thing, to maintain this thing, to deploy this thing. Somehow the cost to build became more expensive. I know a lot of you have probably heard of Jevons Paradox. I don't think a lot of people actually stop and talk about just how freaking old this thing is, 1865. I love it. We're talking about a power bill that looks like what Westinghouse would have given me 200 years ago. We're talking about Stanley Jevons worrying about coal. Just really internalize this, because Jevons Paradox is at the crux of it all.
The more efficient we make a thing the more we consume of that thing. We're making it very efficient, or at least attempting to. This is what it looks like in reality. Cost per tokens are down by 1000% but our enterprise spend is up by 222%. That's the inversion. This is the actual numbers that we're seeing. This is the impact, the result of this. It's happening. It's happening right now. What CloudZero is seeing is pure evidence that it is very real. Fourteen times growth in GenAI spend in the last five months. Eighty percent of that seems to be overhead based on all of the crazy requests, systems, R&D, humans, Claude Code spend. You mix it all in there. A new model comes out, we see, customers go bananas. One customer, 0 to 2 million in a month, just a new model appears. Nothing else really changed, just that.
Then, who's using the cheaper models? Less than 2% of you. We all rush out to grab the new thing. Haiku still does some good stuff. Actually, Haiku is the only one that can answer the question, how many days in the week have the letter D in them? Go ask Opus 4.8 that question. Yesterday, it did not give a good answer. I preface it with yesterday because somebody is probably hard-coding it as we speak. The CFOs are doing the math. This is what we have to think about, tokens or humans. I have caught a couple of CFOs with spreadsheets that literally compare your paycheck to the cost of tokens. Don't believe me? This is why we have to think differently about our jobs. NVIDIA is talking about it. CFOs are talking about it. We're seeing it happen. I want us all to enjoy this future. It should be a very happy future where we all get promoted. We got to start thinking differently now.
Act 4: The Aftermath - Alerts Can't Help You if the Money is Already Spent
What's the aftermath of all this? We've heard about Uber. Everybody's talking about Uber, spent so much money. They're not alone. JPMorgan did it too. Microsoft just literally days ago said, stop using Claude. Of course, they got plenty of reasons why they want people to stop using Claude. It's real. People are starting to freak out. Although interesting enough Uber is still spending because maybe they're getting stuff done. I had one story that came to me. Somebody said, we're going to spend about $4 million this year. We just in this quarter spent about 40. Who does that and survives? My reaction was, who got fired? Said, no, I think some people are getting promoted. What is going on? Uber's CEO though stepped in and said, wait a second, what's the connection between all this money we're spending and the outcome? This is the important question to be asked.
This is the question I want us all to think about. How do we connect the money we're spending with the business outcome? Love vibe coding. I was out at SaaStr, I heard Jason Lemkin actually say these words up on stage. He was talking about how he had rebuilt his whole organization. He had a staff of like 20 or 30 people, and now it was just two people and a dog, and they used Replit for everything. He was like, a dollar a minute. Then people got up to ask questions and said, this vibe coding slop is just driving me absolutely insane. He said, yes, but we're all here, aren't we? In fact, this is the most successful conference I've ever run, two people. It's scary. We also are packing more and more, at least trying to, into the context window. I have a million context window in Claude now, that's fantastic. Let me pack more into there. Let me link up 30 different MCP servers into that system. Let me link everything and let me just dump it in there. Wait, why am I spending all day long fixing the bugs that I just created? MCP tax is real.
There was just days ago, again, another thing, on what Netflix was working on trying to compress the token consumption on the input, try to break this down. If you're not spending time in front of whatever system you're using and regularly sharpening the saw, you are absolutely burning through tokens. Not everyone's token spend is equal. It's fascinating. I've been watching every single one of our engineers use these tools and looking at how much they spend and then looking at what they produce. Wildly different spend, similar outcomes. Some people are doing things differently than others. A lot of it is in how you pack that context window and how you think about planning, starting tasks, or just vibe code the one-shot wonder wagon to value train, whatever you want to call it. It's not just the coding that we're doing, it's also the systems that we're building.
I've seen so many loops, things that break, that just keep going for days and days and days spending money. This is an example taken out of one customer where I saw this. I gave a talk at QCon last year about million-dollar lines of code. I think I'm getting closer to billion-dollar lines of code in some of these things. Security is not to be forgotten either. The first QCon talk I ever gave I think in 2018, I coined this term called Denial-of-Wallet. It is alive and well. I think the next attacker is going to come to us through our own systems, get access to our AWS environment, go find Bedrock, and then use our AI tokens to then absolutely own us from the inside. When we walk away, we'll have no data and even less money after the fact. That attack is coming. The attacker won't even have to pay for it, they'll bill us.
Every company that we've looked at, they had plenty of dashboards. Check out this amazing dashboard I built in Grafana, or Datadog, or wherever, or even CloudZero. They had budget alerts, but nobody was paying attention to them. In fact, a lot of people when they get a budget alert go, I don't know, can I turn this thing off? Will I get in trouble? The CEO said tokenmaxxing is a thing. I've talked to friends who have literally watched hundreds of thousands of dollars go out the door over a weekend, and they felt like if they said anything they were going to get fired. That's terrifying. We've got to have the conversation about what is too much. There's no per call, per user, per anything limit out there. We used to be afraid of this in the cloud, but how much damage can be done? Multiply the ability for every engineer in your organization to spend $5,000 in a 12-hour period and then start to think about how important a limit actually is.
It's very easy for any company of any size to spend the total of its capital in a couple of weeks if they let this thing go. There are no limits. Everyone here is absolutely convinced they're secure as well? Denial-of-Wallet is coming. There's going to be some companies that are going to be put out of business by that.
Act 5: Think Different - Every Decision is Now a Buying Decision
We have to think differently about this. Every decision is now a buying decision. Everything. When was the last time anybody Googled something? No disrespect to Google, but seriously. Googling was free. When I planned my date night on the weekend, I went to Perplexity. I went to Claude. I didn't go to Google. When I needed to figure out the directions, I didn't go pop it into a search engine. I asked an LLM. I paid money for that. We're all paying money for that. Stop for a moment everyone here and think about how much time, questions, things you've done that you would have done for free that nobody would have batted an eye before, searching the web, but you've popped into some Claude, or ChatGPT, or Perplexity window. Then ask yourself, was that a company thing that I did or was that a personal thing that I did?
There's this report that comes out every year that talks about cloud waste. It says cloud waste, and it's been stuck there for the last decade and a half. It says about 30% of all cloud is waste. If we just all stopped collectively doing free Google Searches and just started pumping our every question that we have into the AI thing that we have now at work, what does that waste number look like? Is it waste? When the companies figure out how much money is being spent on that, you want to really wonder what Big Brother looks like in a corporate environment. How many people are ready to have their chat history shared with the world? Even if you try to use anonymous, maybe you're using a proxy. Every decision is now a buying decision. We have to think differently about this.
Let me walk you through a couple of things. We have to stop asking what we spent. I actually think this obsession with cost is costing us. When we think about just how much we spent we forget about the thing that was truly most important, which is, was it worth it? What am I trying to do? What am I trying to build? Why am I trying to build it? Who am I trying to serve? What is the purpose of this? I think that's also rooted in when we think about what our jobs will evolve to be. We have an opportunity to get way more focused on the outcome, way more obsessed with the outcome. If you are obsessed being a craftsperson, building some of the finest code that has ever been written, I have nothing but sympathy for you. Honestly, I do. I used to dream of writing some of the finest code ever written.
I have given up on that dream. It's not much different if we think about it, though, in terms of like, I'm not really after the compiler is done, going and looking at the machine code to make sure that it interpreted it properly. No, we're just going to speak whatever language we speak and we're going to let it get translated into code and we're going to stop looking at the code. I got a confession to make, I don't look at the code anymore. That's the easiest way to deal with it. I care about the outcome. I care about the tests and the validation and the proof that the stuff that came out of it met the demand or the use, but I don't care so much about the code anymore. All code that is produced will eventually be whatever the LLMs can produce in the most efficient manner possible.
That may or may not be assembly. Not a lot of LLMs really are good at assembly. They're good at JavaScript and Python right now, apparently, today. I think over time, the code produced will be some language that is super-efficient for the LLMs to write. That is inevitable, I think. We have to stop thinking about what we spent, just like we had to stop thinking about what was created because we need to think about the outcome. What did we spend? No. Was it worth it? Then us as builders, creators, we have to think, is the reasoning, the model, the stuff that I'm building, is it actually necessary? Am I getting to the right outcome? Did I really need to rush out and switch everything over to Opus 3.8? Can I mix some of these things together? What are these models individually actually really good for? It's not like a 286 and now I'm upgraded to a Pentium.
No. They are different beasts for different tasks. We're thinking about it wrong. What's our rollback plan if we just rushed out and actually burst all these things up? Did we go back and just look at the outcomes? I didn't talk enough about it, but I probably could have given a whole talk on just evals. People have been spending more money on evals than sometimes their production systems, which is a funny observation, particularly for people using LLM-as-a-judge stuff. How much money are we spending on that? There are different ways to achieve quality. What happens when these things loop and run off and explore the universe without us? Are we aware of that? Do we get an alert? What business outcome is this delivering? We should rejoice in that. It is a chance for us to get closer to the customer, closer to the value that we're here to produce. Closer to the businesses that we hope to see successful, hopefully. Or maybe even better, individually we can all start businesses that are much closer to our customers and be much more in charge of that outcome than we've ever seen possible. I'd like to see more companies started.
When we think about how we are going to change our jobs, I want us all to think instead of dealing with being the perfect craftsperson, to think about how we are going to drive that herd of agents, drive the AI employees that are going to be working for you or I. There's a funny joke about this, that's where this came from. There's a farmer explaining to a horse, "Don't worry, you're not going to be replaced by the tractor but you might be replaced by a horse driving a tractor. You better go learn how to drive tractors." We all need to learn how to drive the tractor. We got to also measure the right things. If we measure cost per token, your team is going to optimize for cost per token. This is Goodhart's Law in full force on display. Amazon had a leaderboard, they took that down recently.
Good for them. I don't know how we explain this to our bosses that that AI leaderboard is a bad thing. I definitely still hear the questions. How much are people spending? Why is this person only spending $2? What are they doing? Do they even work here anymore? They only spent $2. That is not healthy. Hopefully we get better at thinking about the outcomes through all of this. A good friend of mine, a very senior engineer, worked with him for years dealing with this same thing. I asked him, what's the problem? He's like, "I got into this business because I love writing code. I don't want AI to write the code. I want to write the code. It's fun. I enjoy it." I got nothing but sympathy for you. I don't know what to say. You're going to be just like those friendly ladies who came into my office 20 years ago, 30 years ago, and said, there used to be six of us in here typing on typewriters, then you computer people came along. Change is inevitable.
The outcome driven metrics are better. They drive better outcomes. These are four that I think you should think about that you should internalize. I am a true believer in unit economics. What does it cost to do the thing that it is that you do? If you don't know this, you should know this. It's probably one of the most important performance metrics for any on-demand cloud-built system in the universe. It is the secret to understanding the 1 million token bill that you got that doesn't tell you anything about what you actually did. It is the most obnoxious, anonymized source of information that tells you nothing about what you achieved. You need to figure out how to break that apart. What feature does this drive? What functionality does this drive? What outcome does this drive? What's the cost for the autonomy in our environment, engineer plus Claude Code?
Are they producing 10x for 5x less? Great. You got to think about the economics. Your CFO, I guarantee you, is. I've seen a lot of the conversations lately move out of the engineering org. You've probably heard of the term FinOps. FinOps is a lot of times inside the engineering org. They care a lot about the cloud bill. I care a lot about the cloud bill still. It's big. The AI conversation has shifted to the CFO's office because it's so big. It's not a budging issue. It's a P&L issue. What that means is the person who also has free access to everybody's salary is also looking at all the other things side by side. Those spreadsheets exist. Get ahead of it. What's the efficiency for the model that we're using to achieve the outcome? That way maybe we can actually understand when the next model comes out if it's even worth upgrading in the first place.
What's going to be the margin yield or margin improvement for all this autonomy? Don't think about it personally. It's not personal. It's just business. I think we actually need to start thinking about that unit cost or that margin data flowing into the systems themselves as a signal for how the systems operate. Is this a top-tier customer? Maybe they shouldn't be using the most expensive models. Maybe they shouldn't be using exactly the same system. What's the lifetime value of this customer? Is this a free tier? Do we have the highest margin tier on the same model as our lowest tier? Route according to margin or your profit objective. It's just unit economics. It's not optimization really. This is just business. It's good business.
Stop Doing This on Monday - Five Defaults
Here's what I want you to stop doing on Monday if you take all this together. Stop thinking a dashboard is going to save you. In fact, in the future, nobody's going to be looking at dashboards. If you're still looking at dashboards, I don't even know why you're looking at dashboards. I don't look at dashboards. The number one user of all these systems is going to be AI anyways, and they'd rather look at JSON. They don't want to look at the dashboard. Yes, you can paste a screenshot into them, but it's way more efficient if you do it a different way. Dashboards are just post-mortems of a horrible event that occurred, because this stuff is moving way too fast. A lot of the CFOs are freaking out right now and actually starting to talk about something they never used to talk about, which is real-time data, which is crazy, because they think in terms of months and quarters.
Get out of this cost per token as your primary KPI. Don't waste time. Don't forget to think about the unit economics. What is the cost of the thing that it is that you do? All these things right now are just decisions that have been made for you. Nobody's thinking consciously about these things. You need to think consciously about these things or they will cost you, or they actually are, in fact, costing you right now.
Key Takeaway
I'll leave you with this. By 2027, I'm convinced that this is going to be true. Probably going to happen faster. The primary buyer of things, technology, cloud resources, stuff in your environment is not going to be humans, it's going to be an autonomous AI system. You remember that Jevons chart, cost of tokens going down, total spend going up? Right now, we're seeing that spend driven by the cost to build more so than the cost to serve. At that point, when this happens, the cost to build and the cost to serve will start tracking together again. We'll be looking at an even steeper curve, because we're spending tokens to write the code. We're spending tokens to deploy the code. The code itself will be picking and choosing what it runs on and how it runs and when it runs. We need to be prepared for a world where we can govern this reality.
Think about that. Those are the systems or thoughts or culture or ideas that we have to embed into our engineering practices right now, into the software development life cycle right now. The thoughts that will dictate whether or not I believe your company is profitable and survives or doesn't. That's what's at stake. The folks who master this, can ride herd over this, are going to be the ones getting a promotion. I want that for all of you.
Questions and Answers
Participant 1: I was checking if you have an MBA because a lot of this is economics. To what extent do you think the workforce needs to be educated in these basic concepts of unit cost?
Erik Peterson: Education, that's a whole other conversation. The cost of knowledge is rapidly approaching zero, but the cost of wisdom is going to go near infinite. My daughter is going into college in the fall. I don't know what that means for her. I don't know what that means for any of us. It's an odd place. If I could go back in time, I would have studied economics and not computer science. That's for sure. I think economics is at the center of everything. I think the path to applying our very technical mind to this problem is by understanding the cost to do the thing that we do, being focused on the outcomes. That path will set you on the right path ultimately. You should think about those things. If you're on that path, you will get better and get that promotion. Here's a funny thing. It's an odd observation, but it's true.
Finance people and technical people often seem like oil and water. They're actually just two different alien species that speak a completely different language. They're both actually highly technical, highly disciplined, highly geeky, in the weeds, detailed cultures. They have way more in common than you would think. Just ask a CFO to open up Excel and show them the cool thing that they've done. You'll be like, this person knows their stuff in front of a system. It's the same way you would feel if somebody said, open up your IDE and bang out a few lines of code. You have a lot more in common than you know. If you find yourself having that conversation, there's a bridge that you can establish there. Probably more so for the engineering side of the house with finance than any other part of the business.
Participant 2: AI seems to be one of the first technologies we see in tech that adoption is being driven partially top-down in a lot of ways. It's not engineering saying, there is this cool technology, let us all move to that. It's various types of C-level people saying. Right now, most of the companies are at the stage of, everyone, engineering, you must become AI native. The second step of how much this costs and why and prove that it needs to be coming, that's probably coming for most of them, but it hasn't come. My question is, from your perspective, what is it you are seeing? What are the trends you are seeing in C-level decisions and how people look at that?
Erik Peterson: AI is definitely felt very tops down. It's also felt grassroots at the same time. What I'll say is, first we did this to ourselves. A lot of technologists, myself included, have had that moment where we walk into the room with the business conversation going on and we say, Kubernetes will solve our problem. "Nobody knows what Kubernetes is in this room." They go, just keep running it on that thing that's in the closet or whatever. Why are you talking about this? I've worked with people where I literally took the whole proposal that they've just had on the table. Why can't we save some money? Why can't we do this the right way? I go into the room, I say, "If we build this Kubernetes pipeline data thing super containerized, yada, yada, yada, it's going to do wonders for our efficiency." I'm like, ok, let's dig into that wonders for our efficiency part.
What does that mean? I don't actually know how to articulate. Let's go figure that out. What is it going to do? It costs us 25 cents per transaction. It's going to go to 10 cents per transaction. Just walk in and say that. There is not a single finance business person in the world if you go and say, the thing that we do costs 25 cents per transaction. If we make this change that I'm not going to explain to you because you wouldn't get it anyways, it'll go to 10 cents per transaction. They go, why are you still standing in front of me? Get out and build it right now. That's the opportunity, get out and build it right now if you can talk in terms that the business understands. They really just don't care about Kubernetes. From a trend's perspective, the CEOs are still out there saying things that are wildly disconnected from the other parts.
The CIO and the CFO seem to be having a moment. CTOs are like, am I going to get fired? Did I do the right thing? The CIOs who are like, wait a second, everybody's building stuff internally again. Just because there's a small company, we're about 180 people, but we rolled out Claude Code and co-work to every single person in the business. A couple weeks later, my head of HR asked me for a GitHub account. What? I don't know. Claude told me I needed a GitHub account in order to do this thing. I was like, do you know what GitHub is? She's like, I don't know what GitHub is, but it said that I needed it and it said that I should ask my IT person, and you're the technology. My observation was everybody in the company became a developer, a very junior developer, in that moment. The CEO was like, this is awesome, everybody is doing stuff. The CTO brain was like, ok, I think we're getting better. Everything blew up.
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