How Forward Deployed Engineering is done at Kepler — Vinoo Ganesh

It's kind of an emotional thing to hear It's kind of an emotional thing to hear uh series of folks who've kind of been uh series of folks who've kind of been uh series of folks who've kind of been talking about how Palenter used to do talking about how Palenter used to do talking about how Palenter used to do things. Um it's funny in the olden days things. Um it's funny in the olden days things. Um it's funny in the olden days and this what this talk will be about is and this what this talk will be about is and this what this talk will be about is largely uh Palin's focus of FTE became a largely uh Palin's focus of FTE became a largely uh Palin's focus of FTE became a go-to market strategy but it wasn't that go-to market strategy but it wasn't that go-to market strategy but it wasn't that in the beginning how we were figuring in the beginning how we were figuring in the beginning how we were figuring out how to build foundry was through the out how to build foundry was through the out how to build foundry was through the lens of a product strategy and so my lens of a product strategy and so my lens of a product strategy and so my talk is going to be how we used FDE as a talk is going to be how we used FDE as a talk is going to be how we used FDE as a product strategy in 2013 to make the product strategy in 2013 to make the product strategy in 2013 to make the data platform that enabled Palunteer to data platform that enabled Palunteer to data platform that enabled Palunteer to then become the thing that Kevin Nat and then become the thing that Kevin Nat and then become the thing that Kevin Nat and all these folks were able to build on all these folks were able to build on all these folks were able to build on and it ultimately comes from like the and it ultimately comes from like the and it ultimately comes from like the background of something pretty simple. background of something pretty simple. background of something pretty simple. So my background is uh I started my So my background is uh I started my So my background is uh I started my career at Palanteer as a software career at Palanteer as a software career at Palanteer as a software engineer um really focused on engineer um really focused on engineer um really focused on horizontally scalable and storage horizontally scalable and storage horizontally scalable and storage solutions at a high level. Uh when we solutions at a high level. Uh when we solutions at a high level. Uh when we say forward deployed um I forward say forward deployed um I forward say forward deployed um I forward deployed to places like Iraq and deployed to places like Iraq and deployed to places like Iraq and Afghanistan. That's me in Bram. It's no Afghanistan. That's me in Bram. It's no Afghanistan. That's me in Bram. It's no longer there anymore. Uh but the idea longer there anymore. Uh but the idea longer there anymore. Uh but the idea was how do we take software and build it was how do we take software and build it was how do we take software and build it in the most critical environments to in the most critical environments to in the most critical environments to make it actually work for people that make it actually work for people that make it actually work for people that needed it the most. So forward deployed needed it the most. So forward deployed needed it the most. So forward deployed is actually a military term and we took is actually a military term and we took is actually a military term and we took it very seriously.

it very seriously. it very seriously. Um my claim to fame from Palanteer is I Um my claim to fame from Palanteer is I Um my claim to fame from Palanteer is I built something called project frontline built something called project frontline built something called project frontline which was the rotation program that took which was the rotation program that took which was the rotation program that took our software engineers and made them our software engineers and made them our software engineers and made them forward deploy engineers. So the folks forward deploy engineers. So the folks forward deploy engineers. So the folks that you see at OpenAI, Anthropic, XAI, that you see at OpenAI, Anthropic, XAI, that you see at OpenAI, Anthropic, XAI, a lot of the FDs, about 350 of them went a lot of the FDs, about 350 of them went a lot of the FDs, about 350 of them went through a training program for how we through a training program for how we through a training program for how we got them to understand what we needed got them to understand what we needed got them to understand what we needed out of forward deployed product focused out of forward deployed product focused out of forward deployed product focused individuals. Uh built the same program individuals. Uh built the same program individuals. Uh built the same program at Citadel afterwards. So across the at Citadel afterwards. So across the at Citadel afterwards. So across the hedge fund, how do we build the right hedge fund, how do we build the right hedge fund, how do we build the right data products and software products to data products and software products to data products and software products to help portfolio managers generate alpha? help portfolio managers generate alpha? help portfolio managers generate alpha? Um this is a quote from the guy who Um this is a quote from the guy who Um this is a quote from the guy who named uh forward deploy engineering at named uh forward deploy engineering at named uh forward deploy engineering at Palanteer. It's from a couple days ago Palanteer. It's from a couple days ago Palanteer. It's from a couple days ago and um Sham is the CTO of Palunteer and um Sham is the CTO of Palunteer and um Sham is the CTO of Palunteer right now and I think this captures the right now and I think this captures the right now and I think this captures the entire essence of where my difficulty entire essence of where my difficulty entire essence of where my difficulty came from in the last talk which is the came from in the last talk which is the came from in the last talk which is the first fundamental truth of FTE is that first fundamental truth of FTE is that first fundamental truth of FTE is that this is not a role this is a product this is not a role this is a product this is not a role this is a product strategy how we discover the things to strategy how we discover the things to strategy how we discover the things to build are through the lens of forward build are through the lens of forward build are through the lens of forward deploy engineering. So looking at market deploy engineering. So looking at market deploy engineering. So looking at market caps of companies for how do we actually caps of companies for how do we actually caps of companies for how do we actually evaluate what contract size this is that evaluate what contract size this is that evaluate what contract size this is that wasn't how it actually happened but the wasn't how it actually happened but the wasn't how it actually happened but the core tenant and the core insight was an core tenant and the core insight was an core tenant and the core insight was an FTE is judged by their ability to be an FTE is judged by their ability to be an FTE is judged by their ability to be an extension of the product team to extension of the product team to extension of the product team to identify areas of opportunity and identify areas of opportunity and identify areas of opportunity and generalize product solutions out of it.

generalize product solutions out of it. generalize product solutions out of it. And so this is the story of how we And so this is the story of how we And so this is the story of how we actually made project Frontline at actually made project Frontline at actually made project Frontline at Palunteer and what I'm using to build Palunteer and what I'm using to build Palunteer and what I'm using to build this function out at Kepler along with this function out at Kepler along with this function out at Kepler along with Susanna here is one of our founding Susanna here is one of our founding Susanna here is one of our founding engineers. Um engineers. Um engineers. Um back in the days, Palenter was first back in the days, Palenter was first back in the days, Palenter was first trying to get into big data. So around trying to get into big data. So around trying to get into big data. So around 2013, uh we had this idea that we wanted 2013, uh we had this idea that we wanted 2013, uh we had this idea that we wanted to store transaction information. And to store transaction information. And to store transaction information. And the product that came out of that was the product that came out of that was the product that came out of that was something called Phoenix. Phoenix was something called Phoenix. Phoenix was something called Phoenix. Phoenix was built totally in isolation. We didn't built totally in isolation. We didn't built totally in isolation. We didn't talk to customers. We didn't understand talk to customers. We didn't understand talk to customers. We didn't understand our financial banks or any anything our financial banks or any anything our financial banks or any anything else. What we did is we designed a else. What we did is we designed a else. What we did is we designed a system in perfect isolation that worked system in perfect isolation that worked system in perfect isolation that worked perfectly under certain circumstances perfectly under certain circumstances perfectly under certain circumstances and crashed and burned when we hit and crashed and burned when we hit and crashed and burned when we hit actual real data. And the situation was actual real data. And the situation was actual real data. And the situation was simple. We had a large scale financial simple. We had a large scale financial simple. We had a large scale financial customer and the idea was we're going to customer and the idea was we're going to customer and the idea was we're going to store your information in bucketed key store your information in bucketed key store your information in bucketed key spaces. Uh this is going to enable easy spaces. Uh this is going to enable easy spaces. Uh this is going to enable easy rolloff and easy retention. Now what we rolloff and easy retention. Now what we rolloff and easy retention. Now what we hit fairly quickly is a lot of banks and hit fairly quickly is a lot of banks and hit fairly quickly is a lot of banks and financial institutions have data that's financial institutions have data that's financial institutions have data that's not perfect. So when we hit a blank data not perfect. So when we hit a blank data not perfect. So when we hit a blank data value, it defaulted to the epoch January value, it defaulted to the epoch January value, it defaulted to the epoch January 1st, 1970. Our retention strategy made 1st, 1970. Our retention strategy made 1st, 1970. Our retention strategy made it such that what we wanted to do is it such that what we wanted to do is it such that what we wanted to do is actually take each 10-minute increment actually take each 10-minute increment actually take each 10-minute increment between January 1st, 1970 and 2013 and between January 1st, 1970 and 2013 and between January 1st, 1970 and 2013 and spin up a time bucketed window. The spin up a time bucketed window. The spin up a time bucketed window. The problem is Cassandra requires 5 problem is Cassandra requires 5 problem is Cassandra requires 5 megabytes per file handle, which means megabytes per file handle, which means megabytes per file handle, which means with the 2.3 million key spaces we with the 2.3 million key spaces we with the 2.3 million key spaces we generated to start up our server would generated to start up our server would generated to start up our server would require 14 terabytes of RAM and we were

require 14 terabytes of RAM and we were require 14 terabytes of RAM and we were dead on arrival. There was no one else dead on arrival. There was no one else dead on arrival. There was no one else we could call. We were the only we could call. We were the only we could call. We were the only individuals and only institutions in the individuals and only institutions in the individuals and only institutions in the room. And we realized something fairly room. And we realized something fairly room. And we realized something fairly simple. The gap wasn't the fact that we simple. The gap wasn't the fact that we simple. The gap wasn't the fact that we had not looked for information about how had not looked for information about how had not looked for information about how customers use our product. It came from customers use our product. It came from customers use our product. It came from the ownership about co-building a piece the ownership about co-building a piece the ownership about co-building a piece of software without being directly of software without being directly of software without being directly embedded with a customer. embedded with a customer. embedded with a customer. The whole purpose of this talk is to The whole purpose of this talk is to The whole purpose of this talk is to convince you of one thing. Forward convince you of one thing. Forward convince you of one thing. Forward deployed engineering is a product deployed engineering is a product deployed engineering is a product strategy. Being an FD is an extension of strategy. Being an FD is an extension of strategy. Being an FD is an extension of the product function, not the go to the product function, not the go to the product function, not the go to market function. So what I'm going to do market function. So what I'm going to do market function. So what I'm going to do is walk through four things and four is walk through four things and four is walk through four things and four real stories that I learned at Palanteer real stories that I learned at Palanteer real stories that I learned at Palanteer and other places. what we learned from and other places. what we learned from and other places. what we learned from those experiences and how they informed those experiences and how they informed those experiences and how they informed building FTE at every other institution. building FTE at every other institution. building FTE at every other institution. The first starts from something fairly The first starts from something fairly The first starts from something fairly simple. Palenter was onboarding uh a simple. Palenter was onboarding uh a simple. Palenter was onboarding uh a large-scale dispatching and shipping large-scale dispatching and shipping large-scale dispatching and shipping company. We sat down with the VP of company. We sat down with the VP of company. We sat down with the VP of operations who generated a 47page operations who generated a 47page operations who generated a 47page requirements doc. What they wanted is a requirements doc. What they wanted is a requirements doc. What they wanted is a custom dashboard, 14 metrics, drill down custom dashboard, 14 metrics, drill down custom dashboard, 14 metrics, drill down alerts, this massive BI tool, a dev alerts, this massive BI tool, a dev alerts, this massive BI tool, a dev project that was estimated at three project that was estimated at three project that was estimated at three months. The kind of hilarious thing that months. The kind of hilarious thing that months. The kind of hilarious thing that happened in this process is we took them happened in this process is we took them happened in this process is we took them at face value. We spent four months at face value. We spent four months at face value. We spent four months scoping this engagement trying to scoping this engagement trying to scoping this engagement trying to understand exactly what this customer understand exactly what this customer understand exactly what this customer wanted before one of us actually showed wanted before one of us actually showed wanted before one of us actually showed up on site just by virtue of the fact up on site just by virtue of the fact up on site just by virtue of the fact that their family happened to live there that their family happened to live there that their family happened to live there and asked what's the first thing you do and asked what's the first thing you do and asked what's the first thing you do with this information Monday morning.

with this information Monday morning. with this information Monday morning. The dispatcher said, "I check if trucks The dispatcher said, "I check if trucks The dispatcher said, "I check if trucks are trucks are late and then I call the are trucks are late and then I call the are trucks are late and then I call the dispatcher to ship a new inventory or dispatcher to ship a new inventory or dispatcher to ship a new inventory or new institution." new institution." new institution." The whole thing could have been The whole thing could have been The whole thing could have been simplified to a trivial Slack alert, simplified to a trivial Slack alert, simplified to a trivial Slack alert, which is what we ended up building. In 4 which is what we ended up building. In 4 which is what we ended up building. In 4 hours, we were able to solve this hours, we were able to solve this hours, we were able to solve this problem cradle to grave. The first move problem cradle to grave. The first move problem cradle to grave. The first move that we learned from forward deployed that we learned from forward deployed that we learned from forward deployed perspective is detect the real problem perspective is detect the real problem perspective is detect the real problem and ship the real thing. The vast and ship the real thing. The vast and ship the real thing. The vast majority of the time, people don't need majority of the time, people don't need majority of the time, people don't need massive BI dashboards. They don't need massive BI dashboards. They don't need massive BI dashboards. They don't need fully scaled designed pieces of software fully scaled designed pieces of software fully scaled designed pieces of software cradle to grave. They have a problem and cradle to grave. They have a problem and cradle to grave. They have a problem and they need that problem actually solved. they need that problem actually solved. they need that problem actually solved. And so the first thing that we learned And so the first thing that we learned And so the first thing that we learned is before you build anything, you as an is before you build anything, you as an is before you build anything, you as an extension of the product team need to extension of the product team need to extension of the product team need to understand three things. First, what are understand three things. First, what are understand three things. First, what are you trying to accomplish? Meaning what's you trying to accomplish? Meaning what's you trying to accomplish? Meaning what's the core goal in actually solving this the core goal in actually solving this the core goal in actually solving this problem? What happens after you have the problem? What happens after you have the problem? What happens after you have the solution? And how is the customer solution? And how is the customer solution? And how is the customer actually solving it today? every single actually solving it today? every single actually solving it today? every single one of these open uh AI or FD deployment one of these open uh AI or FD deployment one of these open uh AI or FD deployment companies are all approaching it in a companies are all approaching it in a companies are all approaching it in a slightly different way than how slightly different way than how slightly different way than how Palanteer did which is we have the Palanteer did which is we have the Palanteer did which is we have the people are going to go on site and build people are going to go on site and build people are going to go on site and build things. What do we build? So I think of things. What do we build? So I think of things. What do we build? So I think of this in terms of an XY situation.

this in terms of an XY situation. this in terms of an XY situation. Customers describe solutions not Customers describe solutions not Customers describe solutions not problems. Your job as the FTE is to problems. Your job as the FTE is to problems. Your job as the FTE is to understand what the problem is. understand what the problem is. understand what the problem is. Customers don't know what happens next Customers don't know what happens next Customers don't know what happens next and your job as the FD is to define it. and your job as the FD is to define it. and your job as the FD is to define it. >> [snorts] >> [snorts] >> [snorts] >> My simple solution and takeaway is if >> My simple solution and takeaway is if >> My simple solution and takeaway is if solving the problem is under a day of solving the problem is under a day of solving the problem is under a day of work, just build it and ship it and work, just build it and ship it and work, just build it and ship it and close the loop. Don't make it a product close the loop. Don't make it a product close the loop. Don't make it a product strategy. Don't expand your product strategy. Don't expand your product strategy. Don't expand your product vision and bring in your PMs and vision and bring in your PMs and vision and bring in your PMs and everything else. If you can solve this everything else. If you can solve this everything else. If you can solve this problem in a short curtailed way, that's problem in a short curtailed way, that's problem in a short curtailed way, that's the first thing we did at Palunteer. the first thing we did at Palunteer. the first thing we did at Palunteer. That's how we started. The secret here That's how we started. The secret here That's how we started. The secret here is whoever defines the problem actually is whoever defines the problem actually is whoever defines the problem actually owns the solution. If we were able the owns the solution. If we were able the owns the solution. If we were able the virtue of the fact that we were able to virtue of the fact that we were able to virtue of the fact that we were able to look at the problem this shipping look at the problem this shipping look at the problem this shipping operator had define the solution and operator had define the solution and operator had define the solution and ship the actual solution meant that we ship the actual solution meant that we ship the actual solution meant that we were always the owners of that system were always the owners of that system were always the owners of that system and we were able to articulate what and we were able to articulate what and we were able to articulate what subsequent solutions looked like. By subsequent solutions looked like. By subsequent solutions looked like. By controlling what we're going to build controlling what we're going to build controlling what we're going to build and by controlling the narrative around and by controlling the narrative around and by controlling the narrative around the solution, you end up in a really the solution, you end up in a really the solution, you end up in a really powerful position. And this is why FDES powerful position. And this is why FDES powerful position. And this is why FDES actually become valuable in early sales.

actually become valuable in early sales. actually become valuable in early sales. It's not because they are really good at It's not because they are really good at It's not because they are really good at talking to customers or we're not talking to customers or we're not talking to customers or we're not socially awkward software engineers as socially awkward software engineers as socially awkward software engineers as people seem to claim. It is because we people seem to claim. It is because we people seem to claim. It is because we actually solve the customer's problems actually solve the customer's problems actually solve the customer's problems in small bite-sized ways that wins us in small bite-sized ways that wins us in small bite-sized ways that wins us trust and that gets us access to the trust and that gets us access to the trust and that gets us access to the real problem that we can then use from a real problem that we can then use from a real problem that we can then use from a product strategy perspective to product strategy perspective to product strategy perspective to generalize. Foundry is a general product generalize. Foundry is a general product generalize. Foundry is a general product solution that we can use across a number solution that we can use across a number solution that we can use across a number of verticals that was informed by tens of verticals that was informed by tens of verticals that was informed by tens of thousands of hours of doing things of thousands of hours of doing things of thousands of hours of doing things like this in the field. Cool. like this in the field. Cool. like this in the field. Cool. Actions speak louder than words. This is Actions speak louder than words. This is Actions speak louder than words. This is a real situation also in Palunteer days. a real situation also in Palunteer days. a real situation also in Palunteer days. Um we had a data quality engineer who Um we had a data quality engineer who Um we had a data quality engineer who was viscerally adamant to a pipeline was viscerally adamant to a pipeline was viscerally adamant to a pipeline adamant about how to solve a pipeline adamant about how to solve a pipeline adamant about how to solve a pipeline stability issue. Every day we were stability issue. Every day we were stability issue. Every day we were dropping about a terabyte of information dropping about a terabyte of information dropping about a terabyte of information to someone's S3 bucket and it was to someone's S3 bucket and it was to someone's S3 bucket and it was putting a lot of pressure on on our own putting a lot of pressure on on our own putting a lot of pressure on on our own data pipelines. We had an easy solution. data pipelines. We had an easy solution. data pipelines. We had an easy solution. Instead of dropping huge numbers of Instead of dropping huge numbers of Instead of dropping huge numbers of CSVs, we can migrate everything to CSVs, we can migrate everything to CSVs, we can migrate everything to parquet. Makes it easier for our parquet. Makes it easier for our parquet. Makes it easier for our pipelines. Makes it easier for like your pipelines. Makes it easier for like your pipelines. Makes it easier for like your cost. Makes it easier from a compute cost. Makes it easier from a compute cost. Makes it easier from a compute perspective. But we had one engineer who perspective. But we had one engineer who perspective. But we had one engineer who was viscerally against this. We couldn't was viscerally against this. We couldn't was viscerally against this. We couldn't figure out why. Every time we'd bring figure out why. Every time we'd bring figure out why. Every time we'd bring this up over the course of about a year, this up over the course of about a year, this up over the course of about a year, she would push back. Whenever I'd ask, she would push back. Whenever I'd ask, she would push back. Whenever I'd ask, she'd say, "Park is way worse. It she'd say, "Park is way worse. It she'd say, "Park is way worse. It doesn't work. It doesn't make sense to doesn't work. It doesn't make sense to doesn't work. It doesn't make sense to me."

me." me." We decided to actually go on site at We decided to actually go on site at We decided to actually go on site at this customer and watch her use our tool this customer and watch her use our tool this customer and watch her use our tool and do this workflow end to end. What we and do this workflow end to end. What we and do this workflow end to end. What we saw is she was downloading CSVs from S3 saw is she was downloading CSVs from S3 saw is she was downloading CSVs from S3 manually onto her Windows computer, manually onto her Windows computer, manually onto her Windows computer, double clicking them to open it up and double clicking them to open it up and double clicking them to open it up and doing a spot check of data quality. She doing a spot check of data quality. She doing a spot check of data quality. She could not do that with Paret files could not do that with Paret files could not do that with Paret files because Parquet didn't have a native because Parquet didn't have a native because Parquet didn't have a native reader that you could just open and reader that you could just open and reader that you could just open and view. kind of a hilarious problem if you view. kind of a hilarious problem if you view. kind of a hilarious problem if you think about it because she was so think about it because she was so think about it because she was so viscerally opposed to this without viscerally opposed to this without viscerally opposed to this without really understanding the benefit it really understanding the benefit it really understanding the benefit it would give her. That night we built a would give her. That night we built a would give her. That night we built a parquet viewer. She approved the parquet viewer. She approved the parquet viewer. She approved the migration in the next 2 days massively migration in the next 2 days massively migration in the next 2 days massively reducing data costs. I think the reducing data costs. I think the reducing data costs. I think the pipeline execution time went from 17 pipeline execution time went from 17 pipeline execution time went from 17 hours to about two. hours to about two. hours to about two. And what this teaches us it's actually And what this teaches us it's actually And what this teaches us it's actually something pretty simple. Uh when you are something pretty simple. Uh when you are something pretty simple. Uh when you are working with a user you are effectively working with a user you are effectively working with a user you are effectively an observer of what happens on site. An an observer of what happens on site. An an observer of what happens on site. An action speaks significantly louder than action speaks significantly louder than action speaks significantly louder than words. So you as an FTE should be words. So you as an FTE should be words. So you as an FTE should be looking for any task a user does more looking for any task a user does more looking for any task a user does more than once. Meaning if they're doing than once. Meaning if they're doing than once. Meaning if they're doing something the same day, same same time something the same day, same same time something the same day, same same time multiple times a day or they're doing multiple times a day or they're doing multiple times a day or they're doing something multiple times a week or something multiple times a week or something multiple times a week or multiple times an hour, that is a multiple times an hour, that is a multiple times an hour, that is a pattern and a hint that there's a pattern and a hint that there's a pattern and a hint that there's a problem and an opportunity. Anytime a problem and an opportunity. Anytime a problem and an opportunity. Anytime a user copies and pastes between tools, user copies and pastes between tools, user copies and pastes between tools, meaning if they're moving from one tool meaning if they're moving from one tool meaning if they're moving from one tool to another, anytime they're reacting to another, anytime they're reacting to another, anytime they're reacting this way, if the first thing you say is, this way, if the first thing you say is, this way, if the first thing you say is, "Hey, how do you feel about this "Hey, how do you feel about this "Hey, how do you feel about this problem?" And their reaction is, problem?" And their reaction is, problem?" And their reaction is, "Well, I have to." And this visceral "Well, I have to." And this visceral "Well, I have to." And this visceral exasperation, you know, you have an exasperation, you know, you have an exasperation, you know, you have an opportunity there. Anytime a user opportunity there. Anytime a user opportunity there. Anytime a user switches tools or tabs, it's an

switches tools or tabs, it's an switches tools or tabs, it's an opportunity. And anytime a user pulls opportunity. And anytime a user pulls opportunity. And anytime a user pulls out their phone in the middle of a task, out their phone in the middle of a task, out their phone in the middle of a task, meaning they're going through a workflow meaning they're going through a workflow meaning they're going through a workflow using your software or anything else, using your software or anything else, using your software or anything else, and pull out their phone, it becomes and pull out their phone, it becomes and pull out their phone, it becomes pretty easy that this is an annoying pretty easy that this is an annoying pretty easy that this is an annoying problem or this software is taking too problem or this software is taking too problem or this software is taking too long. Your goal as an FTE is to make long. Your goal as an FTE is to make long. Your goal as an FTE is to make tomorrow, their tomorrow different from tomorrow, their tomorrow different from tomorrow, their tomorrow different from their today. And it starts with a their today. And it starts with a their today. And it starts with a question, what's the most annoying part question, what's the most annoying part question, what's the most annoying part of your morning? Every morning we all of your morning? Every morning we all of your morning? Every morning we all come into work. Every morning we all come into work. Every morning we all come into work. Every morning we all have something we need to solve. This have something we need to solve. This have something we need to solve. This all goes back to again FTE is informing all goes back to again FTE is informing all goes back to again FTE is informing your product strategy. You earn the your product strategy. You earn the your product strategy. You earn the right to extract user pain and define right to extract user pain and define right to extract user pain and define product strategy by solving small product strategy by solving small product strategy by solving small repetitive problems. repetitive problems. repetitive problems. Now the most valuable intel here is Now the most valuable intel here is Now the most valuable intel here is never going to be in documentation. We never going to be in documentation. We never going to be in documentation. We only saw Maria's uh challenge because we only saw Maria's uh challenge because we only saw Maria's uh challenge because we were badged onto their building. We were were badged onto their building. We were were badged onto their building. We were physically present. We were in physically present. We were in physically present. We were in Afghanistan. We were in Iraq. We were Afghanistan. We were in Iraq. We were Afghanistan. We were in Iraq. We were running around Soho. We were here in running around Soho. We were here in running around Soho. We were here in Palo Alto or in San Francisco. The vast Palo Alto or in San Francisco. The vast Palo Alto or in San Francisco. The vast majority of stuff that matters is only majority of stuff that matters is only majority of stuff that matters is only going to happen live inside of the walls going to happen live inside of the walls going to happen live inside of the walls of the office. Your badge on site at a of the office. Your badge on site at a of the office. Your badge on site at a customer site and your email address, customer site and your email address, customer site and your email address, your contractor email address, those are your contractor email address, those are your contractor email address, those are your data mining permits. The first your data mining permits. The first your data mining permits. The first thing every FTE should do is get access thing every FTE should do is get access thing every FTE should do is get access to customer information by getting in to customer information by getting in to customer information by getting in the room where things actually happen.

the room where things actually happen. the room where things actually happen. Everything lives in that environment. Everything lives in that environment. Everything lives in that environment. And you can't survey your way to this. And you can't survey your way to this. And you can't survey your way to this. You have to be physically present. It's You have to be physically present. It's You have to be physically present. It's very easy to be a forward deployed very easy to be a forward deployed very easy to be a forward deployed engineer in name sitting in a nice engineer in name sitting in a nice engineer in name sitting in a nice conference room in New York, but that's conference room in New York, but that's conference room in New York, but that's not where the actual problems are and not where the actual problems are and not where the actual problems are and that's not where the solutions are. And that's not where the solutions are. And that's not where the solutions are. And the way I've heard this put and the way the way I've heard this put and the way the way I've heard this put and the way we threw it around a palunteer is we threw it around a palunteer is we threw it around a palunteer is residents get the truth. Go on site. residents get the truth. Go on site. residents get the truth. Go on site. Third, when you define the language, you Third, when you define the language, you Third, when you define the language, you control the narrative. We had a customer control the narrative. We had a customer control the narrative. We had a customer where I'm sure this occurs across pretty where I'm sure this occurs across pretty where I'm sure this occurs across pretty much everyone's company here. From a much everyone's company here. From a much everyone's company here. From a logistics perspective, everyone defines logistics perspective, everyone defines logistics perspective, everyone defines customers slightly differently. Sales customers slightly differently. Sales customers slightly differently. Sales members calls them customers. Ops calls members calls them customers. Ops calls members calls them customers. Ops calls them clients. Finance calls them billing them clients. Finance calls them billing them clients. Finance calls them billing entities. Devs call them org IDs. The entities. Devs call them org IDs. The entities. Devs call them org IDs. The way that we talk about the same entity way that we talk about the same entity way that we talk about the same entity in a customer is fundamentally different in a customer is fundamentally different in a customer is fundamentally different depending on what team you're in. That depending on what team you're in. That depending on what team you're in. That results in a huge amount of pain. It results in a huge amount of pain. It results in a huge amount of pain. It generally means integrations break. It generally means integrations break. It generally means integrations break. It means there's data quality issues. It means there's data quality issues. It means there's data quality issues. It means pipelines are constantly not means pipelines are constantly not means pipelines are constantly not working. And it ultimately comes back to working. And it ultimately comes back to working. And it ultimately comes back to a simple fact. We're all human. We a simple fact. We're all human. We a simple fact. We're all human. We define things differently because we define things differently because we define things differently because we operate in our environments and we operate in our environments and we operate in our environments and we understand how to talk about topics with understand how to talk about topics with understand how to talk about topics with people that are similar to us. It's a people that are similar to us. It's a people that are similar to us. It's a feature, not a bug. And so this idea of feature, not a bug. And so this idea of feature, not a bug. And so this idea of an ontology was kind of an accidental an ontology was kind of an accidental an ontology was kind of an accidental thing that Palunteer tripped into. And thing that Palunteer tripped into. And thing that Palunteer tripped into. And what it came from was not this what it came from was not this what it came from was not this understanding that by making everyone understanding that by making everyone understanding that by making everyone stick everything in elastic search and stick everything in elastic search and stick everything in elastic search and you know scheming everything we can you know scheming everything we can you know scheming everything we can solve every problem. came from the solve every problem. came from the solve every problem. came from the simple idea that we need to enable simple idea that we need to enable simple idea that we need to enable humans to operate in the domain that

humans to operate in the domain that humans to operate in the domain that they understand best. And so when I say they understand best. And so when I say they understand best. And so when I say define the language, every organization define the language, every organization define the language, every organization is made up of two things, nouns and is made up of two things, nouns and is made up of two things, nouns and verbs. The nouns define the entities, verbs. The nouns define the entities, verbs. The nouns define the entities, the verbs define the operations. What the verbs define the operations. What the verbs define the operations. What FDES started eventually doing was FDES started eventually doing was FDES started eventually doing was building those nouns and verbs and building those nouns and verbs and building those nouns and verbs and figuring out what the terminology to use figuring out what the terminology to use figuring out what the terminology to use was. In a lot of these enterprises, was. In a lot of these enterprises, was. In a lot of these enterprises, users don't just adopt your product, users don't just adopt your product, users don't just adopt your product, they actually adopt your language. And they actually adopt your language. And they actually adopt your language. And what we were able to do is we're able to what we were able to do is we're able to what we were able to do is we're able to start defining the languages that we start defining the languages that we start defining the languages that we wanted people to use. I think in this wanted people to use. I think in this wanted people to use. I think in this case, we called them um uh c like I case, we called them um uh c like I case, we called them um uh c like I think we canonicalize on customers. In think we canonicalize on customers. In think we canonicalize on customers. In other situations, you canonicalize on other situations, you canonicalize on other situations, you canonicalize on ids. Something like DAU, daily active ids. Something like DAU, daily active ids. Something like DAU, daily active users can mean something very different users can mean something very different users can mean something very different to different people. For product teams, to different people. For product teams, to different people. For product teams, high quality DAUs. for anyone logging in high quality DAUs. for anyone logging in high quality DAUs. for anyone logging in from infosc just the number of people from infosc just the number of people from infosc just the number of people that logged in. All these phrases that that logged in. All these phrases that that logged in. All these phrases that we take for granted are illdefined by we take for granted are illdefined by we take for granted are illdefined by nature. And so when a user adopts your nature. And so when a user adopts your nature. And so when a user adopts your product, they also adopt your language. product, they also adopt your language. product, they also adopt your language. How many people are calling things How many people are calling things How many people are calling things skills right now? How many people are skills right now? How many people are skills right now? How many people are calling things MCPs that are function calling things MCPs that are function calling things MCPs that are function calls with prompts? And that matters.

calls with prompts? And that matters. calls with prompts? And that matters. So third piece here, defining the So third piece here, defining the So third piece here, defining the ontology. Your job as an FTE is to ontology. Your job as an FTE is to ontology. Your job as an FTE is to understand what the ontology is. What understand what the ontology is. What understand what the ontology is. What phrases, nouns, and terms in an phrases, nouns, and terms in an phrases, nouns, and terms in an enterprise are overloaded? Meaning, what enterprise are overloaded? Meaning, what enterprise are overloaded? Meaning, what words are people using to describe the words are people using to describe the words are people using to describe the same concepts? Second, where do the same concepts? Second, where do the same concepts? Second, where do the integration points exist in the system? integration points exist in the system? integration points exist in the system? Are things going from Snowflake to data Are things going from Snowflake to data Are things going from Snowflake to data bricks? Are they going from Palunteer to bricks? Are they going from Palunteer to bricks? Are they going from Palunteer to Tableau? Are they going from Anthropic Tableau? Are they going from Anthropic Tableau? Are they going from Anthropic to SAP? Where do these integration to SAP? Where do these integration to SAP? Where do these integration points actually exist? And what are the points actually exist? And what are the points actually exist? And what are the translation layers where it goes from translation layers where it goes from translation layers where it goes from one term to the other? Naturally, what one term to the other? Naturally, what one term to the other? Naturally, what are the system boundaries? What are the are the system boundaries? What are the are the system boundaries? What are the systems of record you're never going to systems of record you're never going to systems of record you're never going to be able to switch out? And what words do be able to switch out? And what words do be able to switch out? And what words do people use when they're describing their people use when they're describing their people use when they're describing their issues? If someone is saying, well, in issues? If someone is saying, well, in issues? If someone is saying, well, in AI, my agent keeps failing. What is an AI, my agent keeps failing. What is an AI, my agent keeps failing. What is an agent? Like we can't even define FTE. agent? Like we can't even define FTE. agent? Like we can't even define FTE. We're trying to define agents, right? We're trying to define agents, right? We're trying to define agents, right? Are they prompts? Are they like series Are they prompts? Are they like series Are they prompts? Are they like series of steps? Understanding that viscerally of steps? Understanding that viscerally of steps? Understanding that viscerally becomes important. Your job is to define becomes important. Your job is to define becomes important. Your job is to define the terms. If you can define the terms the terms. If you can define the terms the terms. If you can define the terms in your own solution, you can build the in your own solution, you can build the in your own solution, you can build the ontology and you can have customers ontology and you can have customers ontology and you can have customers answer questions and think through answer questions and think through answer questions and think through things in your terms. So the the secret things in your terms. So the the secret things in your terms. So the the secret here is if you become the linguistic here is if you become the linguistic here is if you become the linguistic foundation, you're locked in. And simple foundation, you're locked in. And simple foundation, you're locked in. And simple examples are things like skills, things examples are things like skills, things examples are things like skills, things like MCPs, things like any of the terms like MCPs, things like any of the terms like MCPs, things like any of the terms that weren't a big deal a year ago but that weren't a big deal a year ago but that weren't a big deal a year ago but are now day-to-day in our entire econ are now day-to-day in our entire econ are now day-to-day in our entire econ entire ecosystem. And so when you are entire ecosystem. And so when you are entire ecosystem. And so when you are able to define the vocabulary that users able to define the vocabulary that users able to define the vocabulary that users use and codify that in your platform, use and codify that in your platform, use and codify that in your platform, you become the foundation under which

you become the foundation under which you become the foundation under which every solution and tool is built on top every solution and tool is built on top every solution and tool is built on top of foundry enabled that ontology to be of foundry enabled that ontology to be of foundry enabled that ontology to be constructed and built. That then enabled constructed and built. That then enabled constructed and built. That then enabled the next generation of FTEEs, the go-to the next generation of FTEEs, the go-to the next generation of FTEEs, the go-to market FTEEs to go out there and just do market FTEEs to go out there and just do market FTEEs to go out there and just do data integrations and sell the product. data integrations and sell the product. data integrations and sell the product. We had to learn this the hard way when We had to learn this the hard way when We had to learn this the hard way when we were actually building it for the we were actually building it for the we were actually building it for the first time. first time. first time. Last thing here, ship fast but build for Last thing here, ship fast but build for Last thing here, ship fast but build for production. This is a true story. Um, production. This is a true story. Um, production. This is a true story. Um, they all are, I guess. But, uh, we had a they all are, I guess. But, uh, we had a they all are, I guess. But, uh, we had a customer that needed to run data customer that needed to run data customer that needed to run data retention. I decided to build a very retention. I decided to build a very retention. I decided to build a very quick script. It was in Groovy, if quick script. It was in Groovy, if quick script. It was in Groovy, if anyone knows that language, as a anyone knows that language, as a anyone knows that language, as a temporary fix. Um, it wasn't designed temporary fix. Um, it wasn't designed temporary fix. Um, it wasn't designed for prod by any means. Like, I just for prod by any means. Like, I just for prod by any means. Like, I just randomly hacked this thing together to randomly hacked this thing together to randomly hacked this thing together to solve an initial problem, but it made it solve an initial problem, but it made it solve an initial problem, but it made it there. 12 months later, this thing was there. 12 months later, this thing was there. 12 months later, this thing was all over the place. It was a almost all over the place. It was a almost all over the place. It was a almost 100,000 person customer. Uh it was 100,000 person customer. Uh it was 100,000 person customer. Uh it was running in a number of places for my running in a number of places for my running in a number of places for my then and my nickname at Palanteer Nat's then and my nickname at Palanteer Nat's then and my nickname at Palanteer Nat's not here anymore but she can attest to not here anymore but she can attest to not here anymore but she can attest to this became venue.groovy. this became venue.groovy. this became venue.groovy. My wedding people showed up wearing a My wedding people showed up wearing a My wedding people showed up wearing a name the shirt venue.groovy.

name the shirt venue.groovy. name the shirt venue.groovy. And so the the kind of funny thing here And so the the kind of funny thing here And so the the kind of funny thing here is we solved a problem in a very hacky is we solved a problem in a very hacky is we solved a problem in a very hacky way that did fix an issue but we didn't way that did fix an issue but we didn't way that did fix an issue but we didn't actually productize it. We didn't think actually productize it. We didn't think actually productize it. We didn't think through the end state. So we ended up in through the end state. So we ended up in through the end state. So we ended up in a situation where we were forced to a situation where we were forced to a situation where we were forced to support a very hacky product for years support a very hacky product for years support a very hacky product for years that was never actually productized. And that was never actually productized. And that was never actually productized. And so again when people say customer FTEES so again when people say customer FTEES so again when people say customer FTEES are forward deployed software engineers are forward deployed software engineers are forward deployed software engineers or customerf facing software engineers or customerf facing software engineers or customerf facing software engineers and your job is to make the customer and your job is to make the customer and your job is to make the customer successful that's not true. When you do successful that's not true. When you do successful that's not true. When you do that things like this happen so scripts that things like this happen so scripts that things like this happen so scripts and hacks can fix problems but they're and hacks can fix problems but they're and hacks can fix problems but they're not driving your product strategy not driving your product strategy not driving your product strategy forward. Meaning you're not doing your forward. Meaning you're not doing your forward. Meaning you're not doing your job successfully as an FTE. We have job successfully as an FTE. We have job successfully as an FTE. We have people that jobs are making customers people that jobs are making customers people that jobs are making customers successful. They're solutions successful. They're solutions successful. They're solutions architects. architects. architects. So calibrating what you ship becomes the So calibrating what you ship becomes the So calibrating what you ship becomes the last mo most important skill here as an last mo most important skill here as an last mo most important skill here as an FTE. First, am I going to get a 2 a.m. FTE. First, am I going to get a 2 a.m. FTE. First, am I going to get a 2 a.m. phone call about this in 6 months? If phone call about this in 6 months? If phone call about this in 6 months? If you are, you probably shouldn't ship you are, you probably shouldn't ship you are, you probably shouldn't ship that thing. Second, what is my trade-off that thing. Second, what is my trade-off that thing. Second, what is my trade-off for solving this problem quickly? Am I for solving this problem quickly? Am I for solving this problem quickly? Am I making the right decision for the making the right decision for the making the right decision for the product as a whole? Or am I just solving product as a whole? Or am I just solving product as a whole? Or am I just solving this customer's painoint in a way that's this customer's painoint in a way that's this customer's painoint in a way that's going to have potentially small wins but going to have potentially small wins but going to have potentially small wins but negative compounding challenges later negative compounding challenges later negative compounding challenges later on? Who do I hand this off uh to when I on? Who do I hand this off uh to when I on? Who do I hand this off uh to when I actually leave the customer site? Is it actually leave the customer site? Is it actually leave the customer site? Is it going to a customer? Is it going to going to a customer? Is it going to going to a customer? Is it going to another institution? Is it going to another institution? Is it going to another institution? Is it going to another FDE? What happens when this another FDE? What happens when this another FDE? What happens when this breaks? Am I going to be held breaks? Am I going to be held breaks? Am I going to be held responsible for that? Am I building responsible for that? Am I building responsible for that? Am I building something so missionritical that if something so missionritical that if something so missionritical that if something breaks, I'm going to be hated?

something breaks, I'm going to be hated? something breaks, I'm going to be hated? what happens there. So, we need to solve what happens there. So, we need to solve what happens there. So, we need to solve problems, but we need to be aware of problems, but we need to be aware of problems, but we need to be aware of when we fold those solutions into the when we fold those solutions into the when we fold those solutions into the core offering and when we should just core offering and when we should just core offering and when we should just discard those solutions quickly. discard those solutions quickly. discard those solutions quickly. Here's the actual reality. Every hack Here's the actual reality. Every hack Here's the actual reality. Every hack goes into production. If you make goes into production. If you make goes into production. If you make someone's life easier, it will go into someone's life easier, it will go into someone's life easier, it will go into production and you will be responsible production and you will be responsible production and you will be responsible to support that hack in perpetuity. The to support that hack in perpetuity. The to support that hack in perpetuity. The most dangerous words in forward deployed most dangerous words in forward deployed most dangerous words in forward deployed engineering or engineering is this is engineering or engineering is this is engineering or engineering is this is just temporary. Anyone here who's been just temporary. Anyone here who's been just temporary. Anyone here who's been at a software company knows this is not at a software company knows this is not at a software company knows this is not just temporary. And we know that we're just temporary. And we know that we're just temporary. And we know that we're still writing running on 40-year-old still writing running on 40-year-old still writing running on 40-year-old cobalt code at some IBM mainframe cobalt code at some IBM mainframe cobalt code at some IBM mainframe because of a hack that was put in place. because of a hack that was put in place. because of a hack that was put in place. If it solves a problem, it's not If it solves a problem, it's not If it solves a problem, it's not temporary. It will live forever. So, as temporary. It will live forever. So, as temporary. It will live forever. So, as you're thinking from an FTE perspective, you're thinking from an FTE perspective, you're thinking from an FTE perspective, ship everything like it's going to run ship everything like it's going to run ship everything like it's going to run for 18 months because it probably will. for 18 months because it probably will. for 18 months because it probably will. and through the lens of again the and through the lens of again the and through the lens of again the product building focus should tell you a product building focus should tell you a product building focus should tell you a lot about what goes into the core lot about what goes into the core lot about what goes into the core product offering versus what wins you product offering versus what wins you product offering versus what wins you customer goodwill. So the cheat sheet customer goodwill. So the cheat sheet customer goodwill. So the cheat sheet that we all ran frontline people to uh that we all ran frontline people to uh that we all ran frontline people to uh through rather is the following. Most through rather is the following. Most through rather is the following. Most people who are trying to develop an FTE people who are trying to develop an FTE people who are trying to develop an FTE function treat it like a product function treat it like a product function treat it like a product management task and a customer success management task and a customer success management task and a customer success uh operational task. They take uh operational task. They take uh operational task. They take requirements, they schedule user requirements, they schedule user requirements, they schedule user research, they add insights, they run research, they add insights, they run research, they add insights, they run the processes without actually figuring the processes without actually figuring the processes without actually figuring out how you steer the product from the out how you steer the product from the out how you steer the product from the insights. The right FTEEs who enabled insights. The right FTEEs who enabled insights. The right FTEEs who enabled the creation of something like Foundry

the creation of something like Foundry the creation of something like Foundry redefined the problem. They got badged redefined the problem. They got badged redefined the problem. They got badged on site and they flew to places like on site and they flew to places like on site and they flew to places like Afghanistan, like Iraq, like Somalia, Afghanistan, like Iraq, like Somalia, Afghanistan, like Iraq, like Somalia, like any of these places where we had to like any of these places where we had to like any of these places where we had to be where our customers were. I I have a be where our customers were. I I have a be where our customers were. I I have a friend who was spending time on an oil friend who was spending time on an oil friend who was spending time on an oil rig in the middle of the ocean. They rig in the middle of the ocean. They rig in the middle of the ocean. They shipped the fix before leaving the shipped the fix before leaving the shipped the fix before leaving the customer site to win the goodwill, but customer site to win the goodwill, but customer site to win the goodwill, but they owned the fix end to end in the they owned the fix end to end in the they owned the fix end to end in the product ecosystem. And they took those product ecosystem. And they took those product ecosystem. And they took those fixes and created product leverage from fixes and created product leverage from fixes and created product leverage from it. They were able to translate the it. They were able to translate the it. They were able to translate the problems they saw into nouns and verbs problems they saw into nouns and verbs problems they saw into nouns and verbs that they were then able to use to that they were then able to use to that they were then able to use to define the foundation of every define the foundation of every define the foundation of every subsequent problem that was solved. And subsequent problem that was solved. And subsequent problem that was solved. And finally, they were the ones who got the finally, they were the ones who got the finally, they were the ones who got the call when things actually broke. They call when things actually broke. They call when things actually broke. They were the ones who got in the airplane to were the ones who got in the airplane to were the ones who got in the airplane to fly everywhere else. The question is not fly everywhere else. The question is not fly everywhere else. The question is not what did they learn in the process, but what did they learn in the process, but what did they learn in the process, but what did they ship from the product what did they ship from the product what did they ship from the product perspective? The goal here is actually perspective? The goal here is actually perspective? The goal here is actually fairly simple. I'm going to wrap up with fairly simple. I'm going to wrap up with fairly simple. I'm going to wrap up with this. Product leverage is the only thing this. Product leverage is the only thing this. Product leverage is the only thing that wins you customers. It's the only that wins you customers. It's the only that wins you customers. It's the only thing that backs every Citadel portfolio thing that backs every Citadel portfolio thing that backs every Citadel portfolio manager trading hundreds of millions of manager trading hundreds of millions of manager trading hundreds of millions of dollars. It's the only thing that backs dollars. It's the only thing that backs dollars. It's the only thing that backs every decision being made in the war every decision being made in the war every decision being made in the war fighter ecosystem at Palunteer or in fighter ecosystem at Palunteer or in fighter ecosystem at Palunteer or in customer ecosystems at Palanteer. your customer ecosystems at Palanteer. your customer ecosystems at Palanteer. your job as an FTE and what we learned and job as an FTE and what we learned and job as an FTE and what we learned and what Kepler is doing is using FTEE as an what Kepler is doing is using FTEE as an what Kepler is doing is using FTEE as an extension of the product function to extension of the product function to extension of the product function to enable us to build products that are enable us to build products that are enable us to build products that are actually sticky and that solve problems.

actually sticky and that solve problems. actually sticky and that solve problems. And if you were to take one thing away, And if you were to take one thing away, And if you were to take one thing away, please don't treat FTEEs as go to market please don't treat FTEEs as go to market please don't treat FTEEs as go to market extensions. You can do that when you're extensions. You can do that when you're extensions. You can do that when you're palunteer and have 20 years and palunteer and have 20 years and palunteer and have 20 years and unlimited money. You don't do that when unlimited money. You don't do that when unlimited money. You don't do that when you're an early stage company and you you're an early stage company and you you're an early stage company and you need to figure out what product will need to figure out what product will need to figure out what product will allow you to use those FDs to maximum allow you to use those FDs to maximum allow you to use those FDs to maximum degree. degree. degree. Thank you so much. [applause]