Amplitude's AI Playbook: How Wade Chambers Builds for the Agentic Future

Wade Chambers 0:00 When you get those three things right, clear alignment, cultural onboarding, empowerment, that doesn't mean that it's gonna be perfect, but I've seen a significantly better outcome when those things are all true.

Conor Bronsdon 0:18 Well, welcome back to Chain of Thought, everyone. I am your host, Conor Bronson. Today, we have Wade Chambers, chief engineering officer at Amplitude joining us. Wade, welcome to the show. Thanks for having me. It's our pleasure. In preparation for this episode, I had the chance to chat with you, and honestly, it got me so fired up for our conversation because you said something I really enjoyed among multiple things you'd covered, which was

Conor Bronsdon 0:42 the pace of innovation, how fast AI is moving. And you said that anybody that thinks they've got it figured out is probably wildly off. And honestly, I think that's just such a healthy perspective, especially in the context of what Amplitude does. You're not just providing a tool, you're helping companies navigate this evolving landscape to understand their users, to make better decisions. And Wade, you're in a unique position at Amplitude helping to lead engineering through this AI revolution, something we've talked a lot about on the show with recent guests like Charity Majors.

Conor Bronsdon 1:15 So let let's jump right in. How is Amplitude leveraging AI to solve its core mission?

Wade Chambers 1:22 Well, I mean, first and foremost, Amplitude, for those of you who don't know, is this digital analytics platform. We we help companies understand their customers so they can build better product experiences. And and you have to think about that in all the various aspects of it, right? Like you have to understand what's going on, you have to make decisions, then you have to be able to act on the other side of it. Each one of those is,

Wade Chambers 1:45 an entire thing we could talk about. But if if you think about AI, AI, considered the heart of each one of those things, whether it's understanding, deciding, or acting on it. We can use AI based insights to reduce guesswork. And I mean, like this brilliant person probably can use 20% of the data about a 100% of their brain. Well, maybe not even a 100% of their brain.

Wade Chambers 2:10 But imagine if you had something that could use a 100% of the data to give you more accurate insights that accelerate the decision making process and could even make recommendations associated with that. And then could allow you to act on that in a way that I may want to try something or I need to change the wording or, even that I need to put a guide or a survey or some other experience in place.

Wade Chambers 2:37 We leverage AI in a lot of different ways that helps accelerate, across all of those various areas for thousands of customers. Is there a particular area where you're seeing the most promise so far? I mean, if you just think about, history, right, like there has been so much emphasis over the last ten years or so on gathering up the data and trying to process it. And then comes the Herculean task of I need to make sense of this. Need to understand what it's telling me because it could be conflicting,

Wade Chambers 3:09 there could be dirty data in there, there could be a lot of different things. And so I think that the ability to accelerate the understanding of what's going on is really one of the key value propositions that early on Amplitude solved, and I think we've we've expanded beyond that. But I still go back to that core. I think anything that helps me understand what's going on then allows me to to move forward at at a faster pace.

Wade Chambers 3:35 And regardless of whether it's an insight or a chart that helps you understand what's going on, You may even need a lot of different things stitched together, but that ability to accelerate understanding, then the the rest of it becomes much more manageable.

Conor Bronsdon 3:52 I think this perspective speaks to your experience and the knowledge you've developed over the years, whether that's VP of Engineering at Twitter, at Proofpoint, Yahoo, all these other places that you have helped develop the engineering teams, develop their approach. And now this new AI enabled age has dawned, and you've obviously been involved with Amplitude since before then, with, you know, eight years now as an advisor before,

Conor Bronsdon 4:20 becoming the chief engineering officer. How have you seen the industry shift around you, and how has it shifted your perspective on the work being done by engineering teams as AI tools become

Wade Chambers 4:35 almost table stakes? I think we're still mid transition. Matter of fact, not even mid. I'd say we're very, very early stage, on a lot of that. I think that there's still a lot of organizations that understand the value of data to accelerate that understanding, deciding and acting, but they haven't figured out how to really tap into that. And now they're feeling a lot more pressure

Wade Chambers 5:00 to take and leverage AI in a real way. And so it's it's struggling with both of those things at the same time is pretty hard. I have seen a lot of my peers, you know, really struggle and same with me. I'm not saying that I'm I'm somehow not experiencing the same thing at the same time, but it's like, how do you help your teams both work from a historical point of view where they built up all these skills, competencies, capabilities,

Wade Chambers 5:37 and know that that's changing in real time. Right? When your source code base can talk back to you and tell you what's going on, or you might want to accelerate your understanding of a problem and potential solutions and how quickly can I get to an answer leveraging AI? That's a lot to sort of take into account and I think that there's a lot of companies going through that same process right now

Wade Chambers 6:06 and the amount of data that is going to be available to them is only just going to multiply in the years in front of us and yet the pace is going to be moving faster and faster. How do you take all of those very skilled engineers that you've got in your organization and use them to their highest potential while all of this is going on? It it is a very big challenge in in today's,

Wade Chambers 6:32 market. It's exciting. It's fun, but it's challenging all at the same time.

Conor Bronsdon 6:39 This is also where I see Amplitude as really well positioned because of the the data that you provide to your users and the ability that Amplitude has to help identify friction points in funnels. So this feels like a great opportunity given where AI is going to say, hey, look, we have this already built data funnel, this analytics platform. We're helping you unlock your data already. Let's just take this next step with it. It's exactly right. We feel very fortunate.

Wade Chambers 7:11 I mean, a lot of it is what are people doing on their site? They are voting with their actions. But the more that you can understand where there's frustration in your platform, like who's rage clicking or who's having a lot of frustration on a single page, where are there multiple mistakes being made over and over and over again? You know, Amplitude has put together a lot of products to complete an entire platform

Wade Chambers 7:38 that allows you to engage these users where they're at, from session replays to experimentation to even activating things outside of the platform that I want to go and market to users moving forward. There's a lot of different places that we can help accelerate the understanding and then the action on the other side of that by using data. I mean, we've got years worth of understanding the value of both qualitative and quantitative

Wade Chambers 8:07 data in all of this and and how it can help you make better product decisions.

Conor Bronsdon 8:12 Do you see unlocking that customer data and the years of experience Amplitude has around building that data infrastructure as a competitive advantage compared to other companies that are more so building thin wrappers on top of LLMs. How are you going to position in this new era?

Wade Chambers 8:33 I mean, I I think you really have to think about differentiation in what sort of sustainable advantage do you have and what proprietary data do you have. I mean, we understand a lot of how users are engaging with the product. So those usage insights, and we've established feedback loops that we can take advantage of and so that you understand the behavioral data inside of your system, not just the stats on one side or the other,

Wade Chambers 9:02 but like what active cohorts do you have and how are they behaving different and where do they have friction and what can you do about it? We have the ability to take all of that data and unlock it for you. The advantage of doing it for a long period of time is you find the the low hanging fruit, and then you start to look beyond that and you start to discover deeper patterns that you can use to unlock it.

Wade Chambers 9:28 And so as we can leverage that domain expertise, and we have those data sets and we continue to improve and build upon that and we've used that iterative learning on top of that, we've we've built this deeper intelligence, I think is is pretty hard to replicate.

Conor Bronsdon 9:46 Tell me more about this. How does Amplitude incorporate feedback to refine its own AI and Identical AI offerings? And then how are you doing that for customers?

Wade Chambers 9:55 We do it in a bunch of different ways. There is no substitute substitute for customer interaction. And so we spend a lot of time making sure that we understand our customer pain, more friction, or where they're trying to go. It's commonplace that you will find Amplitude engineers deeply embedded in an account, making sure that they understand. It's not an abstraction for them. They they actually can talk about what Jill is doing

Wade Chambers 10:25 on the customer side and the challenges that they're having. So therefore, they they can kind of work through that. We dog food a lot internally. So we're using our own products where we have a bunch of metrics that we set quarterly goals against annual goals against, and we're tracking it on a weekly basis just to see how we're moving against those goals and objectives.

Wade Chambers 10:51 We go out and we talk on a weekly basis around the theses that we're seeing in the market and like how we should be responding to them. And then we set up customer panels to go and talk to them about those same things. And so we'll have executive advisory boards. We'll have customer boards, all to make sure that, like, it's just not a inside of Amplitude echo chamber, but it's actually accurately reflecting what we're seeing in the market.

Conor Bronsdon 11:20 This speaks to that qualitative and quantitative combination that you spoke to earlier. There's still this challenge around, as you push the boundaries of AI, as you try to leverage your data more, how do you ensure responsible implementations and effective implementations in production and not just in testing?

Wade Chambers 11:37 How are you addressing that? There's a few different things that come to mind just just as we're talking through that. One is we've tried to establish guidelines for ourselves. And so we've said we need to maintain transparency just around model decisions and data usage and allow our customers to say what we can or cannot do with data. Then we've tried to put guardrails in place to prevent harmful or unintended outcomes and we're constantly measuring to make sure that

Wade Chambers 12:08 the thesis matched the results on the other side of it. And then we do a lot to make sure that we have to have long lived relationships with our customers to be able to do this. So we need to demonstrate ethical standards for the long term around what we do with users and make sure that they're completely on board with that to do that. So we've tried to make sure that we're setting guidelines,

Wade Chambers 12:37 we're behaving responsibly associated with that, and just act with full transparency

Conor Bronsdon 12:44 as we move forward. How are you evaluating these outcomes and ensuring that there's not this challenge that comes in with a nondeterminism from AI tooling of hallucinations, mistakes that are made. Of course, we also, I should add, do have mistakes from humans as well, but we already have mechanisms in place to address those. What do you do with AI? Inspection,

Wade Chambers 13:07 a lot of inspection internally. So we have a thesis on what should come out on the other side and we're constantly internally using the product to make sure that we're seeing what was intended associated with that. We've got an AI agent internally that we can use ask Amplitude. And so you can ask it a lot of different things and we're constantly monitoring to see what it's being asked and the sort of responses that it's creating to make sure that we're not seeing

Wade Chambers 13:36 hallucinations. Do you have an evaluation platform in place or how are you approaching this? We do and we have tried to measure against synthetic results as well. And so we'll go through and generate synthetic results and then compare and contrast to that as well as previous norms and what we've seen coming out of that. And so between the two, you've kind of got a historical view and one that's been generated on the other side. And so then you can compare to the two models.

Conor Bronsdon 14:07 I think this speaks to something we discussed a couple minutes ago, which is this incorporation of qualitative and quantitative, where you both have, in this case, automated evaluations happening through elements judges with synthetic data sets, and then continuous learning from human feedback. Talk to me more about how you're incorporating these approaches into

Conor Bronsdon 14:27 your evaluation and testing process.

Wade Chambers 14:30 It's a variety of different ways that we do that, but each team is, the way that we've built the organization is to make sure that organizations feel like they have ownership around long term goals. And so then they are able to sort of build inside of that domain expectations of what good looks like or where you might be off base. That can go both from an output perspective, but also from a cost

Wade Chambers 14:59 or performance or latency perspective as well. And you wanna make sure that you've got the right frameworks that can measure all of those things and so that each and every rev that you've got going out. I wouldn't say that we're golden across the board on every dimension. I don't know any company who's absolutely perfect in all of it, But we are using more and more frameworks

Wade Chambers 15:21 to make sure that we know the delta from one version of the product from the previous.

Conor Bronsdon 15:29 So if I'm understanding correctly, depending on the organization within Amplitude and the goals of that part of the product, you're actually setting different KPIs around what you're looking for from your evals, from your observability, from your AI tooling, whether that is, you know, speed and low latency, as you brought up earlier, reducing cost, or hitting actual outcomes against a ground truth dataset that you've kind of established from the start. That's exactly right. And you you can imagine infrastructure teams

Wade Chambers 16:01 having very different goals and ways of measuring it, like uptime availability, even down to, like, disk utilization and are we getting ready to run out to data teams throughput performance? What's the latency from receiving a record to it being live on the site? You want that as as fast as possible to the cost of processing all of that to platform capabilities

Wade Chambers 16:29 to even end user features. Each and every one is gonna have a slightly different way of looking at it with different frameworks in place to to test for it and monitor against it. This is a really interesting example because

Conor Bronsdon 16:43 I think there's still a lot of organizations that are largely building internal AI use cases, And Amplitude's been aggressively saying, no, we're going to be one of the leaders in externalizing these use cases for our customers so that we can actually deliver additional value to them and not just speed up internal processes. And we're gonna take the time to ensure they're accurate,

Conor Bronsdon 17:04 ensure that we evaluated them, ensure that we understand ground truth and are are tracking how these can deliver for our customer base. What's Amplitude's perspective on continuing to grow this and building more with AgenTik AI, as in the Ask Amplitude agent that you mentioned earlier?

Wade Chambers 17:21 Yeah. I I love the question and I love where AgenTik is going. And I think we're big fans of its possibilities. I mean, if if you think of it, it turns it from a passive or reactive to a very proactive capability in inside of this. If you can take and break down your product into all of its various pieces, And it's almost like having a PhD or a group of PhDs working on each

Wade Chambers 17:49 isolated part, of your problem. AgenTic, I think applied to this space gives our customers the ability to accelerate their understanding, deciding and acting and actually have an active participant in so doing. So anytime that we can provide our customers that sort of active partner for their product teams or marketing teams, you've got a dynamic system that can not only flag friction but can also suggest,

Wade Chambers 18:21 test, refine solutions in real time. So instead of simply waiting for analysts to sort of dig through these dashboards, these intelligent co pilots, for lack of a better term, can proactively surface insights and tailor next steps based on both qualitative data conversations, experiments, things like that you've seen in the system as well as qualitative feedback

Wade Chambers 18:49 inside of a customer reactions, product usage patterns, etcetera. And we feel like if you've got those agents doing those sort of things on a customer's behalf and you've got the humans still remaining in control because of guardrails, we preserve the judgment and strategic thinking that only people can bring to this while letting AI handle a lot of the heavy lifting of pattern detection and rapid iteration.

Wade Chambers 19:16 I think that creates an awful lot of real power in the future that emerges, you know, from this domain expertise that Amplitude has built up over time. Our years of analytical experience should fuel agentic models that understand where to look for friction and why it matters and I think that result is a platform that grows smarter with each and every interaction and evolves from a reactive data tool to into a trusted ally for shipping better products, experiences

Wade Chambers 19:47 faster.

Conor Bronsdon 19:49 I love the excitement I'm hearing from you about this idea of an agentic future where humans are managing teams of agents to extend their capabilities and let them be more strategic. What's convinced you that this is where we're going as, I guess, a tech industry, but just broadly within the way we work? I mean, so one, listening,

Wade Chambers 20:13 hearing, seeing. Would say that largely, But I would say I was on the cynical side of things for a while, and yet I can look out there and experience entire companies that have remade themselves. And so it's, and then as you dig into those companies, mean, one of the benefits of being around a while is you've got a pretty wide network that you can talk to, hey, what are you doing and how are you seeing it?

Wade Chambers 20:43 And it's not a toy anymore, right? Like people are actually able to do all the things that we're talking about. So for me, it's not a leap of faith. It's more of a recognition of a truth. And so when you can see it applied in action and as you dig into it, can see lots of people being successful with it. Then the real question is is like, how can I better understand it and harness its abilities in much the same way?

Wade Chambers 21:10 And so I think that over the last year, especially, right? Like the speed and the clarity and transparency of decision making, doing research and able to build the genetic solutions on top of it has broken through from a novel idea to, no, it's ready to do some things in production.

Conor Bronsdon 21:35 And I know part of Amplitude's strategy to succeed in this new era has been to acquire AI talent, both through hiring and through some acquisitions. How has Amplitude's experience been with acquiring AI talent, particularly given the Command AI acquisition, and how has it influenced Amplitude's AI initiatives internally?

Wade Chambers 21:59 Anytime you can infuse different thinking, into a company, right, I think you get to benefit that. And if you can get enough of the AI genetics together in a group, like I think it multiplies. The Command AI team is, you know, just amazing. Like their leadership down to every single individual inside of the group, great talent inside of there, highly motivated.

Wade Chambers 22:28 Now when you can take that and overlay it with amplitudes mission and where we're going, when there's high alignment and there's high ownership inside of that, you find that, like, the the glue forms and, like, they're able to come in and do great things. Then it's really, you know, can we help set them up for success? Can we give early wins? Can we give them true ownership

Wade Chambers 22:54 in the company moving forward? And so they feel like part of it and they feel like they're not subordinate, but they've actually were better together. And we're winning because we have a lot of benefits to provide to the team and they have a lot of benefits to provide to the greater organization. And we've seen that be very true even in a short period of time. The Command AI has already

Wade Chambers 23:19 both embraced and extended the culture internally. They've had a real influence on the roadmap. And those leaders are, you know, future leaders in the organization and already showing up that way.

Conor Bronsdon 23:32 I feel like the topic of avoiding the, I'll call it, organ rejection, when you're making these acquisitions, to follow your metaphor here of, accelerating the company's AI genetics, when you are making this adaption, often you'll see people that thrash out after time. They're saying, you know, this company, I I joined this much larger company. It's not what I expected or it's not the the work style I want anymore.

Conor Bronsdon 23:56 That can be a challenge that it's hard to avoid. You've obviously had to do this at multiple points throughout your career. What strategies are you applying today to ensure alignment and make sure that these incredible talents that you've brought into the company, these amazing engineers, are able to do their best work and are excited about Amplitude.

Wade Chambers 24:17 Yeah. I mean, it it I feel like it's a truism that, you know, belief systems strive behaviors and behaviors help develop competencies, whether it's cognitive, personal or social capabilities in there. So I I always pay attention to a lot to the belief systems. And so step one for me is their clear alignment. Are there shared objectives and success metrics that everybody believes in? Whether you're on the acquiring side or on the being acquired side,

Wade Chambers 24:53 first and foremost, do you believe and align with those shared objectives and goals? Secondly, then you have to like almost do a cultural onboarding. You have to clear lines of communication, clear ownership, clear wins in the early stages, ensure new teams under understand existing processes, move as fast as possible to a system where everybody can execute as fast as possible on shared code bases, doing those sorts of things.

Wade Chambers 25:28 And then really it's around empowerment. It's like can I grant them autonomy to execute on the vision that they were brought into advance and also give them the resources to be able to do that? When you get those three things right, clear alignment, cultural onboarding, empowerment, that that doesn't mean that it's gonna be perfect, but I've seen a significantly

Wade Chambers 25:49 better outcome when those things are all true, over my career.

Conor Bronsdon 25:54 Often, it seems like the most challenging part of this three step recipe you've provided is that empowerment piece of making sure leaders and individuals who come into an organization actually have responsibility and ownership, and are truly empowered to go out there and make the results happen. How are you fostering an environment where not just folks who are coming in from acquired companies and but any new talent

Conor Bronsdon 26:25 are able to thrive and contribute to Amplitude?

Wade Chambers 26:29 I think that you're gonna find similar themes. It's like you're constantly looking to set people up for success. Give them a chance to win, but then give them the ownership. Like, there's a difference between ownership, accountability, and responsibility, and I think you just need to be clear. I it's a cheeky way of saying it, but I oftentimes talk internally about like a a point system. You get one point for flagging a problem.

Wade Chambers 26:56 It's important. Right? Like, if you don't know about it, you can't do anything about it. And so the absence of that information means it it will go unnoticed. But if you get one point for flagging a problem, you get 10 points for getting to the root cause of a problem. You get to a 100 points if you can accurately, from first principles, define a solution that maps best.

Wade Chambers 27:20 And then you get a thousand points for actually delivering the impact associated with that solution. The reason for saying that out loud is that the further you get into that stack, right, like you just wanna continue to bet over and over. So first is just giving people access to get as high up in that chart and then coach and train, provide context, help make sure that they're talking to the right people

Wade Chambers 27:47 and also help make sure that other people know that you're holding somebody accountable or you've given them ownership of a specific area. And I think that when you can also act in accordance with that, it no longer feels performative. It doesn't feel like, oh, this was a thing. It feels like, no, we are actually trying to onboard people, give them opportunities

Wade Chambers 28:10 to excel and then remove roadblocks from them. And when that works out, new people that have just joined see that happening and like well if it can happen for them, can also happen for me. And once they've done it a time or two, they're gonna tell their friends, hey, like this is a place that actually believes in empowerment and ownership, come do something cool.

Wade Chambers 28:34 Slowly but surely, that's the culture that, you build in internally, and that's kind of culture at Amplitude.

Conor Bronsdon 28:41 I'm a big believer in the idea that this social system has to be integrated tightly into the technical systems, the sociotechnical system theory in order to be truly successful. And I think you've done a great job throughout our conversation here talking about both the data and metrics side of like, okay, we're setting goals, we're finding places of impact, we're creating this feedback loop, and then now bringing in, here's how we're building a culture where people feel unable to actually go out and solve problems and encouraged to do so. How do you meld those together

Conor Bronsdon 29:17 so that everything actually works in concert, and so that leaders and individuals feel enabled to actually go out and solve problems?

Wade Chambers 29:26 Yeah. It's not one thing, probably a system of things. But first and foremost, it it always starts with the customer. You you have to be clear on where the pain or the friction or the the gain is, And it can't be about ego, right? It has to be that the customer is greater than the team and is greater than the individual and all of your behaviors, reward systems,

Wade Chambers 29:53 everything needs to kind of start along those same lines. As you get into it, then you can start decomposing that into where's there the biggest opportunities internally. And I like the concept of NCTs, narratives, commitments, and tasks. But on the narrative part, three key sentences are very important for me. Number one, today, comma, visceral painting of problem.

Wade Chambers 30:18 When we deliver this, comma, visceral painting of solution that highly contrast from problem so that anyone can look at it and go like, ah, I get why we're doing this, and they get what the it comes on the other side. And then the third sentence is, to get there, comma, you must crawl then walk then run. And if you can paint that, that's not so baked that it's beyond the ability to debate and discuss. And so then you actively engage in that debate,

Wade Chambers 30:48 to say, where are we off? Who has the con on this being the the most visceral problem or this being the right solution. There's a a thing that happens as you go through that debate. People still start to feel ownership in this. And when they feel ownership, they'll they'll use discretionary effort to go figure out new ideas, and they'll be thinking about it in the shower the next day and best ideas should win. And so as they come back and you start thinking about it, right, you'll see more and more people's

Wade Chambers 31:18 DNA show up in the results. And as you get to that, right, like you have this sense of, you know, I have ownership in this solution. And so the cultural sort of blends the technical and the human aspects of this in a way that everybody's able to show up as their best self contribute. But it's assumed that like we're going to debate and inspect ideas, no one gets a free pass on this. It's gotta be best idea wins.

Wade Chambers 31:48 And so we've done a lot to try and build systems that encourage that and have people show up and celebrate when when people, do do that. The data, qualitative, quantitative can help you figure out where there's an error in judgment or the debate is not set up well, as well as on the other side. Let's go move fast. Let's ship something quickly to figure out whether it's working or not. And the data should should also help show you that you were right,

Wade Chambers 32:18 as well. And so it really is building like like that sonar inside of all of this that that allows you to call your shot, but also, debate it and and test it in increasingly shorter periods of time.

Conor Bronsdon 32:34 So this is an interesting part of the conversation because I think there is this idea that the best idea should always win as you bring up. But very often, a good enough idea with great execution wins. I Strongly about to enter a new era with these agentic systems that you're mentioning, where execution is gonna become less of a differentiator for this. And actually having the great idea, and then being able to have strong enough execution because you are enabled by these agentic systems,

Conor Bronsdon 33:09 and you're familiar enough with them to basically execute the technical side of a sociotechnical system, will hopefully lead to better ideas rising to the top. I don't think we're quite there yet. There's still this big gap between maybe even a larger gap right now while people some people are leveraging agents and getting doubling down execution advantages, whereas others aren't quite yet. But hopefully, we're gonna get to a point where this is a broader

Conor Bronsdon 33:35 suite that people are able to apply that they're trained to use. How do we actually kind of move from crawling and some people running because they figured it out to everyone running and beginning to leverage this suite of technical tools? And how do we retrain or or or teach the the next generation of team members to take this on? I wish there was an easy answer to that question. I was hoping you'd have it, Wade. Yeah.

Wade Chambers 34:02 No. I I I found that it's again, it's a kind of a system of things, but, like, I one, I strongly agree with you. Right? It's like how quickly can you test a thesis and iterate on it is going to determine the quality of the solution that comes out out the other side. From a belief systems perspective, right, like if you can change the way that you work, you have a much better chance of just, like,

Wade Chambers 34:27 going through it much, much more quickly. And so I think that you need to build that at the top. Right? Like all leaders of the organization, you need to build ownership behind the idea, buy into it, they need to practice it, they need to actively engage in it. So as a leader at the top of the organization, like you have the responsibility of creating a structure like that that exists

Wade Chambers 34:54 and that you can test against and you can see who is truly aligned versus kind of going through the motions. You want to coach those people and you want to help them move through that as quickly as possible or you know, change them out if you have to, but I I I prefer to grow people, if at all possible. So if you do that, what you'll find is that kind of layers through the organization more and more, as you build a belief system,

Wade Chambers 35:21 you will then want to coach others on the same and get them to buy into the same and especially if it's working and there's benefit and doing things along those lines. I also think that you can attack it from the bottom up. Right? Like if you're engineer, technically minded, like you want the best tools. You want to be on the leading edge of things. And so unlocking them

Wade Chambers 35:45 is genuinely just like giving them access to, giving them a little bit of training and then a chance to practice on it. I love the model of you know, you go from unconscious incompetence to conscious incompetence to then I get to declarative knowledge and then it has to become practice. Well, that's really just an opportunity to practice, hopefully with a believable, credible coach that can whisper in your ear and, like, help you understand how it actually works.

Wade Chambers 36:14 Twenty hours of practice, you get good at something. Maybe it takes ten thousand hours to be an expert or a master at something, but like just being conscious about working people through that cycle in the shortest period of time generally works. If you've got it coming a belief system from top down and then you've got skills that are being built up, that state of flow, right, is the how big is the challenge versus the preparation if you're constantly preparing

Wade Chambers 36:40 people and the leadership is believing more and more, there will be more and more challenge associated with that. Then you see the dry kindling catch fire and okay, that's probably a bad metaphor given, you know, what we've experienced in California in the last few years. But right, it does catch. And I think that as with most anything, anytime you can remove friction or increase the speed,

Wade Chambers 37:07 generally there's an embracing of the idea and the concept as long as it's ethical, to do so. So try and build systems that do that.

Conor Bronsdon 37:18 What other advice would you give to leaders who are listening right now as they think about how to grow their org's capabilities and grow other leaders within the organization, and then conversely, folks who are not looking to be people leaders, but are looking to have this upward influence, what would you advise them?

Wade Chambers 37:42 Let's start with the leaders first. The unpopular answer is I think you have to look in the mirror first. You have to put your own oxygen mask on first. And so, to that degree, right, like, you know, everybody's talking about vibe coding. Have you done it? Have you tried? Interesting. Which LLM did you like the best and and why? As you start to work through some of these things and feel friction associated with it and have to work through, you'll have empathy for other leaders and, like, what they might experience and and how to help,

Wade Chambers 38:17 coach them through their growth cycles as well. And then I would say, you know, as you start to think about each leader on on your team, where are they truly at on this? Can you have an open conversation with them that feels safe? Are they worried about their job? Are they worried about where this is all going? Or they're they they don't know that much about it yet and so they haven't learned

Wade Chambers 38:40 how to harness it. Right? Like all of these things are overcomeable, but you have to be able to to have those conversations with them. Everything's learnable. Everything's teachable. Right? It's just being clear on what the gap is between current state and desired state and then like building up that that criteria. And then pushing as many people through it as at the same time helps because you have a pit crew. You have others that are experiencing the same thing that you're experiencing. So I think the shorter window that you can go through with lots of people, right, like

Wade Chambers 39:17 everybody will have shared experience as they go through that, and that will be a culture defining moment in an organization. I would just put your own oxygen mask first and then be very deliberate about the way you're you're engaging your your leadership team.

Conor Bronsdon 39:35 Yeah. I think there has to be intentionality around actually creating space and influence and resources within the org for this up leveling to occur, because some folks are able to find the time to do it naturally or do it naturally through their work, but many more are buried in tasks and are having trouble, you know, getting their head above water, or getting their mask on, as you put it, in order to say, okay, like, how do I plan for this future? How do I build this next layer?

Conor Bronsdon 40:05 And I also think this is true of a lot of individual contributors who are building incredible things and are looking to take the next step of influence, but maybe may not be wanting to step up as people leaders. What's your advice to them as they seek to influence the sociotechnical circuitry of their organizations to be more enabled by AI tooling, or to have space to take a course, or whatever else it may be people are looking to do? I think there's overlaps in the answer here and the previous. It's like,

Wade Chambers 40:41 I think you look at the mirror first if you are an engineer and you truly There are a lot of people who get to a certain escape velocity, so to speak, and right? Like they learn, they become very competent, they become very good at something and then want to leverage that competence for as long as they possibly can. Which puts you at a disadvantage in that like you are trying to maintain

Wade Chambers 41:12 that thing that you think is your worth as opposed to, no. I can problem solve. I can learn things. I can apply new technologies based on new challenges and things along those lines. You think people get stuck and don't evolve as much as they need to? I think there is a large portion of that. I mean, look at me, I'm late 50s, right? And so like this new technology

Wade Chambers 41:41 that's in front of us, that could be very scary or it could be the most exciting thing. And I think you have to choose, which one of those those statements are true. As an individual contributor, I think that you need to understand this new tool. Right? Like you need to test it, you need to play with it, you need to see where its limits are. And what you'll find is that it's not everything.

Wade Chambers 42:07 It's not one solution is not everything to you. You're going to figure out how to use Windsurf. You're going to use different LLMs because different ones are going to be good at different things. The context windows are increasing in size. What does that mean? And how are you going to leverage that? As you, get into it with a beginner's mindset, I think it helps you a lot more. And you should expect that over the next five to ten years,

Wade Chambers 42:37 you are increasingly going to be less and less competent because there's going to be more and more rapid change that you just need to catch up with. And as you come to to grips with that, those that can actually move through that fairly quickly, there's a whole new world of of capabilities and results that can be produced because of that. And so it it it's constantly

Wade Chambers 43:05 trying to identify that gap between your current state and the desired state and like how quickly can I learn and grow through it? And it is the testing and playing with and trying to use it in production as much as you possibly can, that's gonna teach you all those things.

Conor Bronsdon 43:23 What closing thoughts do you have about what an AI enabled future looks like?

Wade Chambers 43:28 I am truly excited about what I think this means. I think that up to this point, I am like, I I've I've talked about like, I I've worked with a bunch of intellectual bullies that on the engineering side, you know, use technology as a shield for just doing the things that they wanted to do. You know, they they would talk past people and make it sound intellectually

Wade Chambers 43:55 too hard or things along those lines. And I think what is happening more and more is product engineering and design are all coming closer and closer together and sort of the things that separated them over time are losing their hold. And so that ability for you to do market research, come up with an idea, be able to get to base level requirements, generate a design,

Wade Chambers 44:26 build a working prototype, you're still gonna have to have problem solving skills inside of that. But I think that's going to be more and more approachable over time by lots of different disciplines that come into it. So I'm really interested to see whether we just get, you know, a ton of new lightweight apps that are out there or whether we're truly going to get new innovation that happens at a very deep level

Wade Chambers 44:55 where companies are building or individuals are building SaaS solutions that are industry strength and can do really great things. My guess is it's all of the above but the technical barrier is going to be largely reduced as a result. So anybody that's out there, if you've had a great idea, I think your ability to bring that to market is going to get easier and easier.

Conor Bronsdon 45:21 I completely agree. I think that's a really exciting feature of what is coming and how the world is being transformed. We're already seeing this happen for many folks, and it just seems like that impact and that effect is accelerating. Wade, thank you so much for this fantastic conversation and coming on the show. It's been a distinct pleasure having you with us today.

Wade Chambers 45:41 Connor, I've I've really enjoyed it. Thank you so much for inviting me on. Hopefully, we get a chance to do it again sometime. I think we can make that happen. Absolutely.

Conor Bronsdon 45:50 For the moment, though, where can folks go if they wanna learn more about you and follow your work and or learn more about Amplitude? I would still point people at LinkedIn for for me specifically.

Wade Chambers 46:01 And then I would say that for Amplitude, we're pretty active on all the socials. And so if you want to know about culture or new products, LinkedIn, X,

Conor Bronsdon 46:12 others, like pick your favorite social and we're probably on it, and we're pretty active about it. Excellent. And we will, as always, be linking that all in the show notes. To keep up with the latest in AI and hear more from industry experts like Wade, be sure to subscribe to the podcast on your favorite platform, whether it's on YouTube if you're watching us, whether you're on Spotify,

Conor Bronsdon 46:35 Apple Podcasts, Stitcher, wherever you are listening to this, we would love to have you with us for future episodes and check out our back catalog. And if you wanna go deeper into the world of AI and check out how tos, demos, webinars, and much more, don't forget to check out that YouTube channel. IGalio YouTube has so much more on the podcast, and I think you'll enjoy it. That's all for this week. Thanks again, Wayne. Thank you.