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Screaming in the Cloud with Corey Quinn features conversations with domain experts in the world of Cloud Computing. Topics discussed include AWS, GCP, Azure, Oracle Cloud, and the "why" behind how businesses are coming to think about the Cloud.
SITC-Eric Anderson
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Eric Anderson: I think you have to be as good at the AI game as these frontier labs, but I think that's possible. Like they clearly don't have a lock. Hold on. Talent, you know, talent's just leaking everywhere.
Corey Quinn: Welcome to Screaming in the Cloud. I'm Corey Quinn. My guest today is one of those rare breeds we don't see a lot of as guests on this show. Eric Anderson is a partner at Scale, which is a VC firm, Eric. Thank you for joining me.
Eric Anderson: Thank you, Corey.
Corey Quinn: This episode is sponsored in part by my day job Duck. Bill, do you have a horrifying AWS bill?
That can mean a lot of things. Predicting what it's going to be, determining what it should be, negotiating your next long-term contract with AWS, or just figuring out why it increasingly resembles a phone number, but nobody seems to quite know why that is. To learn more. Visit dot. Bill hq.com.
Remember, you can't duck the duck bill.
Bill, which my CEO reliably informs me is absolutely not our slogan.
Usually we talk a lot more to folks who are the engineering type, the founder type, occasionally the marketing type who weasel their way through, but we've only had a handful of VCs in the years this show has been running. So for those listening in the audience who might not be entirely clear on what the role of a general partner at a VC firm is and only be able to gather it contextually and badly from the platform formerly known as Twitter, what is it you'd say?
It is you do here?
Eric Anderson: We fund and support startups, it's a lot of trying to find what's the next big thing, who's building it. Uh, convince 'em to take your money and then make 'em successful to the best they can.
Corey Quinn: It always seems counterintuitive for that to be the framing because like, please, please take my money.
Sounds like it's, it doesn't sound like it's a real problem, if that makes much sense, but I've, I have a bunch of friends who've raised and talking to them about the process and seeing folks go through it. It's weird. It's it's feast or famine. It's either no one will fund you or everyone wants to fund you.
And how do you decide which of the various economic suitors you decide to go with? So a lot of it comes back, channel references, track record history, similar to the same way that VCs wind up trying to pick the founders that they want to take bets on these days. It seems like it is difficult to separate out the world of VC and funding and startups from the monstrosity that has become ai.
But you've been doing this longer than AI has been a thing. Historically, you ran a product team, I'm not sure which one, over at AWS, which I will accept apologies for in a moment. Uh, then you were at GCP doing similar things for a while and then decided, you know, building things seems hard. Let's go instead do the corporate version of betting on the ponies, on the horse track.
Uh, what was the progression there?
Eric Anderson: Spot instances was the, was the AWS thing.
Corey Quinn: Ah, yes, yes, yes.
Eric Anderson: Yeah. Everyone's favorite, like intellectual product to, to, to tinker on. And then it was. Uh, kind of BigQuery, but mostly this thing called data flow. But I, I say BigQuery just 'cause people know it a little bit better.
And the progression was really, I don't know, it was incidental at the time. I was just, uh, I was interested in startups and I wanted to prove my, my metal in Silicon Valley. And so I was, I felt like the best way to do that was I going to Amazon or Google and working on the most technical thing. I didn't study cs, I started mechanical.
And that, that was always a bit of like an uphill battle with these like hiring. Firms. I was like, oh, just stick me on EC2 and I can show you. I, I can, I'll survive.
Corey Quinn: It kind of feels like that's almost the problem we have at Google as well, where you have a cash cow that is advertising and everything else is almost incidental to that, oh, you wanna build a moon base?
Fine. Go build a moon base. Good luck. We're still selling ads primarily. I, I've always gotten the sense that the AWS world, that EC2 was kind of that 800 pound gorilla.
Eric Anderson: Yes, yes. That was like, like you build products and then you monetize them via EC2. You know, when I was first there, it was before they broke out revenues.
You know, so it was kind of, no one quite knew how interesting this thing was.
Corey Quinn: Everyone thought the thing was losing money hand over fist and then one day they make an announcement and oh my God, those are damn near SaaS margins.
Eric Anderson: And I would get this mini announcement, right? I got an email every Friday that told me how many cores we had sold.
Like a little team summary, and I would get out my calculator and be like, this is crazy. They're. Printing cash.
Corey Quinn: Yeah. And what I love about Spot is that from, I've heard this from multiple folks who were there at the time and afterwards, that it really is just unused capacity. It's not like they wind up building stuff specifically to shore up their spot.
It's just stuff that would otherwise. Be going to waste sitting there as more or less air conditioner ballast. Suddenly they found a way to monetize this and they managed to do it in a way that doesn't completely destroy anyone ever paying for on demand anything. And I think that's kind of a neat approach.
'cause there are sub use cases for which it's phenomenal. Others for, which is terrifying. Uh, you were there back in the days when it was inter, our wide swings in pricing before they, they stabilized it significantly, which frankly was for the best. I didn't really want to become a high frequency trader in this one incredibly niche thing.
Eric Anderson: Apparently this was Bezos's idea. I mean, I never spoke with him, but
Corey Quinn: I have no trouble believing that.
Eric Anderson: Yeah. The banker guy was like, why aren't we doing this kind of marketplace? And yeah, the wild swings. I didn't appreciate the fact that there was this, you, you kind of imagine like unused capacity is this nebulous, singular blob, but they carve up all the instances into all these instance types, into all these regions availability.
Suddenly you're like, we have 400 SKUs of EC2, right? And each one is a little tiny spot market. It's a mess.
Corey Quinn: Yeah. You, you're definitely dating yourself with that reference. There's over 700 now in US East one alone. It's, I, I did the math on all of this where I wind up tracking a lot of, I, I, I had Claude build me some nonsense because why not?
Where it tracks the, uh, the pricing pages for everything that gets dropped out. It's multiple gigabytes for all the pricing information broken down by service. But the EC2 specific one, I had to refactor some of the code because it kept timing out. Lambdas. There's no way you can grab the whole thing.
IOOM killed an EC2 box a couple of times because yeah, that thing's enormous and it's, and I'm also on bad at programming, but that's okay. Gonna fix that particular problem for me rather nicely. And just being able to track all of this, it, it is a monstrous surface area. And not just tracking the pricing, let alone actually making the thing work.
Eric Anderson: So, so keeping stock, you know, like, like basically a spot is like an inventory problem, right? And keeping inventory of one product is a lot different than 400. I mean, it's like.
Corey Quinn: Right. My, my customers all tend to be extraordinarily large scale, which kind of puts the lie to a lot of the historical way the cloud was positioned and sold even in 2018.
I had a client when the I threes came out like, okay, we're gonna spin up 1200 of those in Ohio. And the response from eight OS was, can you give us about six weeks on that, please? That would be great. There's the cloud does not scale. Infinitely, uh, source tried. It didn't go so well. Doing. The capacity planning comes back around at significant scale.
It starts to resemble a lot of the old school data center stuff. It's, oh, just turn this thing on for an experiment and turn it off. That's still there. That's incredibly powerful. I think it has been a tremendous boon to getting companies from idea to start up to success, but also from idea to, oh wait, that won't work.
Nevermind, turn it off, and I owe 24 cents at the end of the month. Both of those are incredibly powerful. Things. Uh, but as you continue to succeed and, and grow and grow and grow it, it starts to resemble multi-year capacity and contractual planning. So these days, what are you finding that's exciting you?
What is it that you are, that you're looking at and saying, yes, that is something worth paying attention to?
Eric Anderson: Certainly the coding agents. This is, I mean, there's all this talk about a GI, this, which is, is a poorly, it's an unhelpful phrase, right? I mean, what I, I, when we get there, does anything change?
Probably not. And then the overlap between better than human or less than better. But regardless, whatever it is, I think coding agents are, maybe it, uh, yeah. Software has forever changed and it, I feel like it, it happened more. In the last three months than, than I guess before that
Corey Quinn: I, I think that even looking at something like Claude Code as a software, as a coding agent is a bit of a misnomer and a bit of a weird approach.
It can integrate with effectively everything, and the interaction model is human language, where. You can tell it to go out and grab a bunch of different APIs. Research the best way to do this, construct a research report. You can treat it just like you can the, the Claude Chatbot expression. When you have access to the entire CLI, when you have access to every API out there on the planet, suddenly it's starts to look a lot less like a coding agent and a lot more like an orchestrator where you can tie together all sorts of things with a, we're still at a point where you need a little bit of coding knowledge to make things work, but.
Software is no longer the bottleneck for an awful lot of stuff.
Eric Anderson: Yeah. I don't, like, I don't use slides anymore or PowerPoint. It's actually, I think, easier to just ask Claude to generate a presentation and it does it in like an HTML, you know, webpage ish thing, which is like, how would you ever edit it? You don't, you ask Claude to edit it or, or your, your agent of choice.
Corey Quinn: Yeah, I, I do much the same. I use a slide dev theme that for my company branding and the rest, but I built an entire custom plugin that has a multiple, uh, different skills for how I do slides, how I think it should work. And I'll give it the, I'll give it an outline and Great. Turn this into a slide deck.
Suddenly all the problems I had as a presenter, I, I. I'm a public speaker probably too much. I have this ongoing love affair with the sound of my own voice. He said on his own podcast where this became, or my biggest challenge was I would work on a part of the slide deck here, then part of the slide deck here.
Then I'd go and give the thing, and I'm circling the same 0.3 different times at different points throughout the presentation. It is a terrific editor for, okay, now go back and fix the narrative flow. Make sure that it does the things in the right order. It's almost, but not quite. At a point where I can have it just build my slide deck for me.
It's great for a first attempt at that, but it'll just make things up. But it turns out, if you say things with a straight enough face, people will believe you.
Eric Anderson: Yeah. Slop through the mouth of a human is like all the, all the content and all the credibility in one.
Corey Quinn: Exactly. Now it's I, I think that it's an assistant.
I think human in the loop is still gonna be required for the foreseeable future when it comes to most of these things. I think that as soon as you take. That judgment piece out of it and let it speak for you. There are problems. You are risking your own credibility every time you do it. Like I have a ea style bot that I built, Billy the Platypus, uh, whatever I wind up, uh, turning it loose on various pitches that people send me.
It's technically professional, technically, but it, he is just basically a total jerk. That's sort of the entire persona that's built into it. There's a reason he sends as Billy the Platypus and not as me. The first time that gets even slightly wrong. I suddenly have a serious reputation problem.
Eric Anderson: Things that get me excited along those lines are like, we won't look at code.
I mean, I, I'm excited about this. Like there was a time when I thought we used the coding agents and then you review it and someone else does the code review. Like as long as you do the code review, you're safe. Right? And now we have the agents doing the code review, and now maybe the risk is like, well, what about like performance?
You know, you get these like terribly, you know, no one's refactoring the code is just slop on top of. But I think we, I think we'll have agents refactoring the code. And so I'm excited about the idea, like, what, what ha what does the world look like when no one looks at the code anymore? Like, what, what emerges, what are the opportunity?
And so I think there's some, maybe some cool concepts around like, yeah, you know, performance improvement bots or you know, someone that goes through and kind of. Refactor optimizes deploys this thing to, you know, constantly keeps it updated with latest libraries, patching, I don't know.
Corey Quinn: Yeah. That sort of maintenance bot on it on some level.
Uh, there's also, this, this is an early optimization in some ways too. Most of the stuff that I have it build and go nuts on only lives in my internal network. It's stuff that improves quality of life for the way that I do things. It improves my own workflows, but I don't. Make this public. I don't expose it on the internet and the performance issues of, for example, when I write my newsletter every week and I've, uh, got it the way I want, it goes ahead and does the rendering, the formatting, checks, all the links, et cetera, and they're small performance improvements, like, huh, you're checking 35 links.
Maybe you could do that in parallel rather than sequentially, but even it's not. Okay. I, it doesn't, I, I'm not sitting here with a stopwatch waiting for this thing to finish on my stuff 'cause it's saving me a fair bit of time. Checking those links manually. I can grab a cup of coffee while it does it at some point.
Yes, I'll do the easy optimizations, but performance on a lot of those back of house workflow style tools does not need to be. Top notch. In fact, one of the things I like with my own expression of how I think about things is I'll have, like all my development stuff with Claude Code now exists in an EC2 box where it has root, where it lives in its own AWS account where it has admin access and there's nothing of value in this AWS account.
Let be very clear on that. It's just a bill risk where it can do anything that it wants, but it doesn't have access to anything sensitive. And I'll just go and I'll tab over to it and kick it to the next step, and then I'll go back to doing whatever I was doing. It's. It's sort of a drive by and now do the next step.
And I'm sure that's that there's an orchestration story that's coming to, uh, as an overlayer on top of that anytime now everyone's trying to build one and get those funded, it seems this week, but there's gonna be something that emerges and is the next iteration of this, and we'll see how it goes. I like the fact that if you don't like how things work, give it a month.
Now that said, I think it's really hard to come up with a durable pitch in the AI space right now that is. That is fundable just from the perspective of that's a feature release from Anthropic or open AI before suddenly you have to do a massive pivot. Like we saw this historically. Oh wow. Suddenly ChatGPT can speak to PDF, and suddenly a whole bunch of companies had a problem.
But that was also relatively easy to predict that that was coming. How do you think about it?
Eric Anderson: The thing that has proven the most defensible is like, I mean, I, I agree with you certainly, but I'm impressed that cursor. The, the way open AI and anthropic became so big is like be, became so scary. It's just, it's just the sheer growth rate and, and like cursor captured a little bit of that lightning.
Right. And, and, and then became maybe threatening to Anthropics and Anthropics kind of. But like, I, I feel like when I talk to my portfolio, it's like. Yes, we should be afraid of them unless we can just grow faster than that. Like is there, is there a way you can kind of find the vein and shoot to like cursor scale to the point that, that you kind of can own something and, and some of these things are growing just incredibly fast?
Corey Quinn: Oh yeah. I used to use Cursor a fair bit and then I pivoted to Claude Goad and I haven't gone back since just because. Cursor was great when I was looking at the code and, okay, now make this section, do this other thing instead. But increasingly I don't look at the code that this stuff puts out. Also, again, this is all backend stuff that I'm building for ease of use in my stuff.
I suppose now is a good time to detour into Germane story that is, you know, our sponsor break. 'cause my own company sponsors this at Duck Bill, we have a history as a consultancy helping companies fix their horrifying AWS and other cloud bills. By a contract negotiation and diving into finops strategy.
Then now we're doing it with software as well. Our product is called Skyway, and yeah, we're using Cursor and Claude code and the rest to build this thing, but it is not itself an AI play directly. It's providing foundational, normalized data warehouse infrastructure for other things such as CPS to wind up talking to and getting that data out of it.
But by and large, that is still a place that is relatively not. Where AI excels. And it's not because I have a bias in this perspective that I'm saying that I've done a number of experiments and continue to do them. It's not there yet for data sets of this scale and this sensitivity. So if you're interested in learning more, duck bill hq.com, please give us a shout and you might even have to deal with me, should we have that conversation.
Don't worry. We have people who are actually good at this stuff. But yeah, there, there are some areas where it seems like. Everyone's like, oh, you're really building a B2B SaaS. Isn't this going to be disrupted by ai? Well, when you're, when you're talking about things like normalized infrastructure spend across a wide variety of providers, yeah, AI can help build the tooling and whatnot, but telling Claude to go out and hit your billing data for all of your providers and put it into a database for you sure would be terrific if that were to work.
And it does in 80 to 90% of it. And then the edge and corner cases absolutely cut you to ribbons because that's why this is an area of enterprise concern. If it were simple, it wouldn't be worth doing.
Eric Anderson: Yeah. I think maybe an analogy that, that your listeners might appreciate. You know, we, we've been through this before, right?
When AWS was kind of in its early heyday, everyone was afraid of AWS. All the investors would go down to reinvent and. They'd announced this new database and a bunch of startups would, would die because of it. And, and so we all thought the cloud was gonna be vertical and, and Amazon was just taking all over all the things.
And then yet, uh, you know, come years later, like four or five years later. Kind of late to the party. We got Datadog, kind of horizontal monitoring across all the stack. We got eventually, just a couple years ago, Wiz security monitoring across all, all, you know, all the clouds. We get the proprietary databases, snowflake and Databricks and, and ClickHouse.
I think these are, these are the things people prefer to use. So I'm optimistic that, uh, and, and I guess I'm referring mostly the infrastructure stack. That, that it doesn't go off. Kubernetes was a big unlock
Corey Quinn: for this as well. I mean, back when I started doing this, I have of opinion this is game point and match to AWS, the end and there's gonna be a bunch of also ran.
I do not have that opinion these days. Uh, they're obviously not going away. They're not going anywhere, but. It's impossible to ignore Azure, GCP, and even Oracle Cloud, but all the value seems to be at just one level up the stack. Take Vercel, for example, for front end it, it does all the things that you can do on AWS.
Clearly, Vercel runs on AWS and about a 20 to 30% markup on top of it, but I have a lot of stuff running on Vercel instead of on AWS. Why? Well, because I don't know anything about front end, but that's what the LLM picks and Okay. I, I don't have a strong enough opinion to override it on that space, so. Okay.
I guess we're putting the front end there.
Eric Anderson: Yeah, so I think, I think there's a chance, you know, there's a way to compete against open AI or Anthropic. I think certainly the thing that they're weak on is just the diversity of like, they can go into Claude Code, they can go into Claude Bot, they can go into.
The Claude Cowork, they're fighting a battle on many fronts. And, and so if you can, if you can be laser focused, if you can fe realize what is the front that is actually the most valuable, like in the case of the cloud, it turned out to be like the data warehouse was the front to fight on. Um, that was the area to win where both Amazon was weak and the value would accrue.
So if you can figure out the right front and then just be laser focused and be good. I mean, I think, I think you have to be as good at the AI game as these frontier labs, but I think that's possible. Like they clearly don't have a lock hold on. Talent, you know, talent's just leaking everywhere. So yeah, you find great talent, you figure out where value's gonna accrue in an interesting space, and then you're just laser focused.
And if you can catch the growth. I think there's a viable path.
Corey Quinn: Yeah. There's also the question of what are the underserved niches? I've always liked finding the expression of these things that, that works. There is no amount of money I can raise from anyone that is going to mean that I am now the third massive frontier lab that's building this stuff out.
I'm discounting the ones at Google, for example, like the, that, that's not exactly the same thing here. Uh, but I, I'm not gonna ex, I'm not gonna outrun these players at that, but, and. The capabilities are growing by leaps and bounds. So where are the areas that I know well that I can bring some of these things to bear on, uh, industry specific expertise.
Uh. Opportunity passes everywhere, and I think that that is the way to think about it to, to no small extent. I also don't necessarily know that I want to be building the exact same thing that everyone else is building. I, I like finding a direction to take things in. It's weird because I find myself for one of the first times in my life being something of a centrist on this because I don't believe the doomsayers say that we're going to build a GI and we're going to.
At this point, trample everything out there because computers will think for themselves. We're not summoning God through JSO here. And I also am on the other side where I don't think it's just a jumped up auto complete because it is clearly far more than that. I'm, I'm between those two extremes. And it's a weird place to find myself,
Eric Anderson: right.
Yeah. To, because usually the world's just either really wrong or it's obvious. And in this case it's neither, it's, it's like. This thing is for real and it's, but you know, it, it's subject to to physical laws like, like everybody else. Yeah,
Corey Quinn: yeah. OpenAI alone has, RA has committed to do more infrastructure spend between now and 2030 than there is deployable global VC capital.
I have some questions about what that's going to look like because they're not the only lab that is doing this sort of thing. What does it look like five years from now? What is the economic story of this? We're clearly looking at something bubble shaped. What does the correction look like? It. I'll tell you what, it's not.
It's not, and now we're going to act as if LLMs never existed. You're not putting that genie back in the bottle. Maybe this price of inference is going to skyrocket. Maybe the ability to run things that are almost as good locally is going to be the approach. Even with having coding assistance build this stuff, maybe I don't need the top tier frontier, bleeding edge state-of-the-art model to wind up doing what is effectively a fancy, uh, said string replacement in a file.
Maybe that can be the local thing and the deep architecture planning is something attica's outsourced. These are all things that people way smarter than I am, are focused on. I'm just curious to see where it goes because the benefit as a developer myself is accruing rapidly and massively
Eric Anderson: a bubble is inevitable.
There's, there's no avoiding a bubble because the growth rates are so incredibly high and un like, like when, so anthropic went from one to 7 billion in revenue in a year, so they have to plan for another seven x increase. Or at least a five x increase. Like they can't just like, not buy the capacity they need.
And, and could it be higher, could it be They have no idea. So they have to, they have to, they have to procure the capacity to satisfy at least some portion of that expected demand. And until these crazy growth rates give, we have to plan. We, we have to overbuy, you know, over like, until, like eventually they give, we won't know when they give.
And, and then when they give, we'll have realized we have overbought, but until they give, we'll feel like we have under bought. So a bubble is inevitable, but I don't, and, and so I think in terms things, in terms of like bubble prediction isn't all that helpful. Unless you can kind of call the point at which we saturate,
Corey Quinn: right?
Economists have successfully produced, uh, predicted five of the last three recessions. I mean, this is always the problem. You smack into it. You can't timing the market. It can remain irrational longer than you can remain solvent, but there are, there are limits on this. I, I spend 200 bucks a month for the Claude Pro Max Plan with a smile on my face.
I'm not gonna spend $5,000 a month on that because at some point there is a limit and. It's, there has to be something that gives, you're into population limits. People willing to drop that kind of money on these things, but where is that boundary? I don't know. A lot of the funding sort of acts and the messaging has been around that your boss is going to replace you with AI and then split your salary with the AI company.
Like I, I don't think that that necessarily tracks
Eric Anderson: Yeah. This, this idea that all pricing holds and like whoever deploys the AI gets to keep all the money. Is crazy. Like there's certainly gonna be some amount of commodification where people are like, oh, I don't have to, like, I wanna keep some of my money too.
I'm not just gonna give it all to you. And you deploy the ai I'm expecting that all of the people I buy things from are deploying ai. They're gonna bargain, you know, they're, they're gonna compete in a marketplace where. Everyone lower lowers their prices because they can eventually, margins get to the point where they always were.
You know, there's a certain amount of money people are willing to work for and if you have monopoly power, you get, you get to charge a little bit extra. Like, like the lawyers today, there's a lot of talk that, like lawyers used to bill by the hour. They can't do that anymore because now AI is doing the work.
So they have to. Bill by the, by the project. And then they just keep the extra money, I think. I think we're all just gonna be like, no, you're not really doing any work, so I'm gonna pay you less. And then we get back to billing by the hour.
Corey Quinn: Everyone acts like this changes everything, and I'm not convinced that it does.
There are strong. Indications that this is, there are ways forward on this. Uh, take a couple. You're a board observer for Honeycomb. Uh, we've been working with them both with the client and other ways for a long time. I love the way that they do AI because they don't splatter AI all over their messaging and their marketing.
They have built it in useful ways. Their MCP is a thing of beauty. The fact that you can ask in plain language what the hell is going on in your environment and it will tell you is glorious. But when, whenever someone talks about AI to the exclusion of all else. I'm sorry to break the hearts of marketers out there, but as a customer, that's off-putting.
I don't care if you are using ai, incredibly smart if statements or just interns that type very quickly. I just care about the outcome that you are delivering for value. That's the important piece from where I sit and I'm not, I'm very far from alone in that it's similar to, I don't care how the sausage is made.
I care that it tastes good.
Eric Anderson: Yeah. Yeah. There's a kind of a second order. Wave, I think of AI use, like the first is the obvious, where we use it in the context of our current, what's a good example, you know, the, the AI workers. Like, oh, let's have an ai, SDR or an AI data scientist, because that's, that's like the current framework of our society, and we can plug them in in those holes, but presumably we should discover new ways of organizing society.
That weren't possible until we had ai. And once we discover those new ways, then we'll have products that take shapes. We don't, we can't really imagine at this point. And so I think you're right, like the way Honeycomb feels like a, a tease towards this future where like, hey, maybe not, everything's a chat bot, actually, uh, like a side panel alongside the traditional app.
Maybe it's like infused within applications in ways that we didn't really think possible before because it wasn't possible.
Corey Quinn: Maybe I don't wanna alert your dumb proprietary SQL version to get value out of your platform. Maybe I, maybe your robot can do that for me, similar to when I have a problem, I need to reach out to a company.
Don't make me talk to an AI bot. But have that AI bot provide valuable context to this human support agent that I'm talking to, to power through that a lot more quickly and provide context like, I had the last seven tickets. This guy either knows what he's talking about or is a complete buffoon, just accordingly.
And they can provide, they can get to answers a lot more effectively that way, as opposed to making me run the AI gauntlet before. Finally. Huh. It looks like you can't solve this problem yourself. You're gonna have to talk to a human. No kidding. Uh, all these companies have been talking about chatbots, like it's somehow the pinnacle of user experience.
No. People talk to chatbots or humans when the user experience has failed them. You're already starting a step behind.
Eric Anderson: Yes. Yes. What if the people in the call center were three times more effective because they just solved their problem three times faster rather than talk to three customers at once, which is what I feel like most of the time is.
They're like, yeah, let me check on that for you. Two minutes later. Like, how is it taking this long?
Corey Quinn: Right. Or they wind up asking you questions you answered three messages ago. It's like, I thought I had a short context window. It's awful. Ugh. I wanna thank you for taking the time to speak with me about all this.
If people wanna learn more, where's the best place for them to find you?
Eric Anderson: You can find me on Scale's website. I'm fairly active on LinkedIn. I need to get my Twitter, what do we call it now? Game up. But yeah, I, I, LinkedIn or uh, scale website would be a good place to start.
Corey Quinn: And we'll of course put links to that in the show notes.
Thank you so much for taking the time to speak with me. I appreciate it.
Eric Anderson: Thanks, Corey.
Corey Quinn: Eric Anderson, partner at scale. I'm cloud Economist Corey Quinn, and this is Screaming in the Cloud. You've enjoyed this podcast. Please leave a five star review on your podcast platform of choice, whereas if you've hated this podcast, please, we have a five star review on your podcast platform of choice, along with an angry comment talking about how your minor incremental feature to an AI foundation model.
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