From Hype to Habit: How We’re Building an AI-First SaaS Company—While Still Shipping the Roadmap
00:00:00.000 | .
00:00:15.280 | Hello, everyone.
00:00:16.400 | Welcome to our talk on building AI first companies.
00:00:20.000 | I'm Rossella.
00:00:21.120 | And I'm Debsha.
00:00:22.240 | We are so excited to be here with all of you today.
00:00:25.520 | You've probably heard the term AI first a gazillion times already,
00:00:29.920 | this week.
00:00:30.960 | And if you are in this room, chances are you're not just wondering what that means.
00:00:35.120 | You're also trying to figure out how to actually make it real inside your own company.
00:00:40.800 | And that's what today's talk is about.
00:00:43.200 | We wish we could stand here and give you the talk.
00:00:50.000 | The one with all the answers and a crystal clear playbook for becoming an AI first company.
00:00:57.280 | But the truth is that that talk probably doesn't exist.
00:01:00.640 | AI transformation is really hard.
00:01:03.440 | It's messy.
00:01:04.320 | It's full of trade-offs and it looks different for every company.
00:01:09.440 | At Sprout Social, we are in the messy middle of our own AI transformation.
00:01:14.720 | So this talk is a candid real-time look at what it takes to lead a SaaS company into the AI era.
00:01:23.760 | We'll share what's working, what's not, and a practical framework to guide you through your own AI transformation.
00:01:36.160 | But first, let's break down the buzzword.
00:01:39.680 | What does AI first even mean?
00:01:42.000 | I feel like AI first is like teenage sex.
00:01:46.080 | Everyone talks about it.
00:01:48.480 | No one really knows how to do it.
00:01:50.160 | Everyone thinks everyone else is doing it.
00:01:53.040 | So everyone claims they're doing it.
00:01:55.200 | Jokes aside, what does it mean to be AI first?
00:02:00.160 | It's about evolving from AI features sprinkled into the product to rethinking how you plan,
00:02:08.480 | build, and deliver value all through an AI lens.
00:02:13.840 | More than that, it's about putting AI at the center of your strategy.
00:02:19.200 | But most importantly, it's a mindset shift more than anything else.
00:02:24.400 | Now, if you've been in tech for a while, you've seen big shifts before.
00:02:30.160 | Cloud first, mobile first, DevOps, and many more.
00:02:34.400 | But here's the difference.
00:02:36.080 | Those shifts disrupted one area at a time.
00:02:41.360 | AI is distracting all of them at once.
00:02:44.960 | It's product, it's architecture, it's people, it's process, it's ethics, it's everything.
00:02:52.960 | And that's what makes it so hard, but also such a game changer.
00:02:57.840 | Here's the good news.
00:03:00.160 | Being AI first isn't binary.
00:03:03.280 | It's not like flipping a switch.
00:03:05.520 | It's not about throwing everything out and rebuilding your company overnight.
00:03:11.280 | AI transformation is a multi-dimensional journey.
00:03:14.480 | It's an evolution.
00:03:15.520 | Where you are on this spectrum will vary depending on your own company.
00:03:21.200 | But the important thing is to know where you are and to move with purpose.
00:03:26.320 | AI transformation is complex, but it doesn't have to feel chaotic.
00:03:33.600 | At Sprout Social, we found that it helps to think about it through a simple framework.
00:03:38.800 | At its core, becoming an AI-first company means evolving across three key dimensions.
00:03:45.600 | Strategy, what you prioritize and why.
00:03:48.960 | Ways of working, how you build, ship, and adapt.
00:03:53.520 | And people, how your teams evolve, and the skills that define success.
00:03:59.040 | Whether you're just getting started or already in the thick of it, these three areas give you a way to make sense of the work that is ahead of you.
00:04:09.920 | And we hope that this simple framework can help you navigate your own AI transformation.
00:04:15.760 | So, now that we set the bigger picture, let's start with the first dimension, strategy.
00:04:20.720 | The very first critical shift is about how to determine what to build.
00:04:28.320 | about evolving from an AI-enhanced to an AI-first strategy, where you are reimagining what's possible today thanks to AI.
00:04:38.720 | In the past, investing in AI meant asking, where can we add intelligence to an existing experience?
00:04:47.120 | It was about sprinkling AI across your product to make workflows better.
00:04:54.000 | In contrast, in an AI-first company, the question becomes, what new experiences can we deliver that weren't even possible before?
00:05:03.520 | Being AI-first means reimagining what's possible.
00:05:08.560 | It's about solving problems that were previously unsolvable in ways that customers may not even imagine.
00:05:16.160 | Now, dreaming about the future is super fun.
00:05:21.120 | But the challenge is that you still have to ship features to meet your customer needs today.
00:05:27.920 | That's the tension every company is facing right now.
00:05:32.000 | How do you ship what customer needs today while also investing in the future you know is coming?
00:05:38.960 | If you over-index on the present, you risk falling behind and missing the moment.
00:05:46.320 | If you focus only on the future, you risk disappointing customers, slowing revenue, and potentially starving innovation of resources.
00:05:55.120 | That's the core of the innovator's dilemma.
00:05:58.240 | And AI makes it 10 times harder.
00:06:01.200 | You basically need the discipline of an enterprise and the curiosity and nimbleness of a startup.
00:06:09.840 | But you need both to be running in parallel.
00:06:12.560 | It's like steering a ship and launching a rocket at the same time.
00:06:19.600 | So at some point, you have to figure out how to build a startup inside your own company.
00:06:27.280 | I couldn't agree more.
00:06:28.320 | And that is what makes this so difficult.
00:06:31.200 | With this fast-evolving goalposts, if you felt this tension, you're not alone.
00:06:36.000 | When a three-month roadmap starts to feel stale in three weeks, what is possible is constantly evolving.
00:06:43.200 | How do you adjust that in the roadmap?
00:06:46.240 | And because of that, we're realizing that we're moving farther from deterministic roadmaps, where we generally knew what we were building for months in advance.
00:06:54.800 | We've had to shift our mindset that embraces ambiguity, where learning and discovery are what shaped the path forward.
00:07:02.960 | Now the destination itself can evolve as we learn more about what's possible.
00:07:08.400 | And that's how we plan.
00:07:11.120 | It's also evolved how we design.
00:07:13.520 | When earlier, we could build AI into features.
00:07:16.720 | In an AI-first interaction, customers expect seamless, intelligent systems that stretch across workflows and even roles.
00:07:26.000 | Let's think through that with an example.
00:07:28.480 | Let's talk about Woofwell.
00:07:29.920 | It's a health tracking app for puppies.
00:07:32.960 | And here, our customer is Pineapples.
00:07:35.120 | Pineapples uses Woofwell to track meals, activities, digestive insights.
00:07:41.520 | Yes, that's a poop log.
00:07:43.120 | And also track supplement recommendations.
00:07:45.440 | Each of these features in our company is owned by different teams.
00:07:50.880 | But in an AI-first world, when Pineapples is engaging with that app in a natural language,
00:07:56.560 | he's not thinking in features.
00:07:58.080 | He's expecting a unified value.
00:08:00.400 | So when Pineapples says, I'm feeling kind of blah, a meal-based response could say, hey,
00:08:06.000 | maybe because you skipped breakfast.
00:08:07.520 | A digestive-based response could say, yeah, your poop seems a little off today.
00:08:12.400 | But both answers are useful, but very narrow.
00:08:16.880 | Now imagine a unified experience for Pineapples.
00:08:20.160 | The answer could be, it might be the new kibble.
00:08:23.360 | Your activity seems to be going down over the days and your poop also seemed to be off today.
00:08:29.040 | Maybe this new supplement that you're trying, pause it and see how you feel tomorrow.
00:08:33.200 | That's what AI-first really means.
00:08:36.000 | Not just smarter features with AI sprinkled in them,
00:08:39.040 | but the unification to generate a broader value that you unlock incrementally through your roadmap.
00:08:47.200 | But that has also evolved how we build, which means how we work together, move fast, learn fast,
00:08:53.760 | and stay aligned through this uncertainty.
00:08:56.640 | Here's what those shifts look like.
00:08:58.160 | Historically, innovation often happened in a reactive way.
00:09:03.600 | Someone had an idea, we tested in isolation, maybe do a spike to see if something worked,
00:09:09.440 | and then move on to the next big idea.
00:09:11.120 | It was ad hoc.
00:09:12.720 | And while it led to moments of inspiration, it rarely became sustained strategic driver.
00:09:19.280 | In an AI-first world, that kind of fragmented discovery doesn't hold up.
00:09:24.640 | The landscape is moving so fast, with the stakes so high,
00:09:28.480 | that we need to treat discovery as repeatable, deliberate process.
00:09:33.040 | And that's what a ritualized discovery means.
00:09:36.080 | It means building time into our planning cycles for experimentation, hackathons,
00:09:42.320 | and learning in various forums and formats that are visible and actionable across the company's strategy.
00:09:48.640 | As part of ritualized discovery, we've also embraced a mindset of MVPs for learning.
00:09:54.480 | not just to launch quickly, but to validate direction.
00:09:58.480 | We assume that not every bet will land.
00:10:01.360 | Some features won't work the way that we're expecting them to.
00:10:04.880 | But in this case, failure is a feature, not a bug.
00:10:08.880 | It's what drives clarity through ambiguity.
00:10:11.280 | We've also had to rethink what processes are for.
00:10:15.760 | Many of the processes we've built in the past were designed for predictable,
00:10:20.880 | linear roadmaps with deterministic risks.
00:10:24.320 | It was a world where we generally knew what we were building months in advance.
00:10:28.480 | But in an AI-first world where timelines shift, capabilities are evolving monthly,
00:10:33.200 | those old processes don't always hold up.
00:10:36.720 | At the same time, if you introduce too many new processes all at once, it can backfire.
00:10:42.320 | Instead of helping, they slow us down.
00:10:44.720 | They become overhead.
00:10:46.240 | They create drag.
00:10:47.200 | And a few folks here from Sprout will confirm that in Sprout, we've learned that the hard way.
00:10:52.240 | That's why we've started treating process as a product.
00:10:56.640 | We evaluate it against outcomes.
00:10:59.520 | Does it create clarity of direction?
00:11:01.840 | Does it unblock teams?
00:11:03.280 | Does it help us make better decisions faster?
00:11:05.920 | And if the answer is no, we have to read to rate or cut it entirely.
00:11:10.320 | Process isn't a dirty word.
00:11:11.760 | When it's purposeful, it gives teams the clarity and flow and becomes a process that accelerates.
00:11:17.680 | Now, we heard in the amazing keynotes yesterday that execution is the moat.
00:11:23.520 | Speed is paramount to delivering against the evolving landscape of tech and the customer expectations.
00:11:29.680 | But if you move fast without clarity of direction, you end up with chaos.
00:11:34.160 | And if you have clarity of direction with no momentum, you stagnate.
00:11:38.240 | How do you find that balance?
00:11:39.680 | Because in AI world, speed matters, but only when it's paired with direction,
00:11:44.800 | we've had to move from speed to smart velocity.
00:11:47.840 | Which means building the muscle to move fast with purpose.
00:11:51.840 | When we talk about prototyping quickly, building MVPs and speed,
00:11:56.480 | we're not just saying ship it for the sake of shipping it.
00:11:59.760 | We're talking about working with clarity, momentum and adaptability.
00:12:04.880 | Smart velocity is what keeps us grounded and moving all at the same time.
00:12:10.000 | And now let's talk about the most important piece of it all.
00:12:14.480 | The people.
00:12:15.440 | If strategy sets the direction and ways of working determines how we execute,
00:12:21.840 | the people are what makes the whole thing real.
00:12:25.840 | After all, country is strategy for breakfast, right?
00:12:29.200 | And here's the truth.
00:12:31.360 | Becoming an AI-first company isn't just tech transformation.
00:12:35.360 | It's mainly a cultural transformation.
00:12:38.640 | And country lives in people, how they think, how they work, how they lead and how they feel.
00:12:44.240 | That means that we need to rethink what great talent looks like in the AI era.
00:12:50.160 | Not just in your AI team, but across the entire company.
00:12:55.600 | At Sprout Social, we are seeing two major shifts.
00:12:59.040 | How talent is evolving in this AI area and how to scale AI fluency across the organization.
00:13:08.000 | So let's start with the first one.
00:13:10.880 | As the world changes, so do the capabilities that matter most.
00:13:14.480 | To be clear, the talent that we need today isn't replacing what we had yesterday.
00:13:20.000 | It's just building on it.
00:13:21.440 | Until now, what made an AI practitioner great was deep specialization.
00:13:27.840 | Being a generalist or a visionary builder gave you an edge, but for most roles, those skills weren't critical.
00:13:35.920 | Today, that is changing.
00:13:38.240 | AI depth is still essential, but now being a versatile visionary builder has become critical to success.
00:13:48.960 | That's why we are investing in T-shaped talent.
00:13:51.920 | People with deep expertise who can also stretch wide, prototype quickly, collaborate fluidly across silos,
00:14:00.800 | and bring end-to-end systems to life.
00:14:03.600 | It's a bit like Indiana Jones.
00:14:06.000 | We're not choosing the professor and the adventurer.
00:14:10.160 | We are combining them, bringing the deep specialization of the scholar into the jungle
00:14:18.320 | to uncover unimaginable possibilities.
00:14:20.720 | And that's why more than ever, we need people who can navigate ambiguity.
00:14:26.480 | There's no playbook.
00:14:27.760 | The technology is evolving faster.
00:14:30.000 | The roadmap keeps shifting.
00:14:31.600 | That means we need pathfinders.
00:14:34.480 | People who can hold to their deep expertise while forging new ways through shifting terrain.
00:14:42.240 | And in most cases, the path doesn't even exist.
00:14:47.440 | So they have to imagine it first.
00:14:49.280 | And that's where visionary thinking becomes a core skill.
00:14:53.840 | So this shift from shipping what's known to charting what's newly possible is what we believe
00:15:03.440 | defines the next generation of AI builders.
00:15:06.320 | But evolving our builders is only part of the story.
00:15:11.920 | Becoming AI first isn't just about the few who train models or build agents.
00:15:16.720 | It's about building fluency across the whole organization.
00:15:21.680 | You can't go AI first if the rest of the company is still AI last.
00:15:29.440 | So in an AI first company, everyone touches AI, even if they're not training models or building agents.
00:15:36.400 | From marketers and designers to PM and care agents, we want every team to feel empowered to understand AI
00:15:45.120 | and confident enough to build with it.
00:15:47.760 | And that's why we're investing in our wide AI fluency.
00:15:52.880 | To inspire people of what's possible and to make AI feel usable, safe and real in the context of their day-to-day work.
00:16:01.120 | We're supporting this enablement through things like AI newsletters, podcasts, cross-functional AI show and tell,
00:16:07.760 | and by empowering teams to use whatever AI tools help them work smarter.
00:16:13.200 | But fluency isn't enough.
00:16:15.520 | It has to scale.
00:16:17.600 | To do that, we aim to be the sole service platform to enable product and engineering teams across the organization
00:16:27.120 | to prototype and ship AI-powered features without needing deep involvement from the AI team.
00:16:32.960 | The goal is not to turn everyone into an AI expert.
00:16:37.920 | It is to create a company where AI thinking and exploration is the default, not the exception.
00:16:45.120 | Sorry.
00:16:48.400 | Sorry.
00:16:51.200 | All right.
00:16:54.480 | Now we've talked about a lot of the things that have changed and I know that's very overwhelming,
00:16:59.200 | but there are also some things that haven't changed.
00:17:01.920 | The fundamentals.
00:17:03.040 | Our best AI features still solve customer problems.
00:17:07.440 | They're rooted in needs, not the novelty of AI, as long as they're solving customer problems.
00:17:12.720 | User experience, performance, reliability, trust.
00:17:17.200 | These are still non-negotiable in the AI-first world.
00:17:20.240 | Human creativity, human judgment, and human care remain central to how we lead, how we make decisions,
00:17:28.880 | and how we show up for our teams and customers.
00:17:32.560 | So if you're leading AI transformation in your company, get honest about the trade-offs.
00:17:37.760 | Invest in people, not just models and agents.
00:17:41.120 | Kill the roadmap if needed.
00:17:43.840 | Be bold.
00:17:44.400 | Learn out loud and ship that weird idea.
00:17:49.680 | We hope this talk served as the flashlight in the maze.
00:17:52.480 | And you'll leave knowing that becoming AI-first won't be a linear path and it won't be perfect.
00:17:58.880 | But the good news is you don't need all the answers to get started.
00:18:02.800 | You just need the right questions and the conviction to evolve.
00:18:06.720 | We're going to leave you with this one, with this last reflection.
00:18:10.880 | The most transformative inventions in human history only became truly revolutionary
00:18:17.360 | when they became part of our day-to-day life.
00:18:19.920 | And we're now standing at the cusp of the next greatest revolution.
00:18:24.960 | This is a profound privilege and an honor.
00:18:28.480 | Not only are we witnessing this moment, but we have the opportunity and responsibility to shape it,
00:18:35.280 | to guide our teams, our companies, and our communities through a transformation that will
00:18:41.280 | redefine how we live, how we work, and how we connect.
00:18:45.040 | This isn't just a technological revolution.
00:18:48.800 | It's a human one.
00:18:49.920 | This transformation isn't easy.
00:18:52.640 | It takes time, grit, and the patience to navigate setbacks, doubts, and growing backs.
00:18:59.600 | In fact, this is how we look like when we started the journey.
00:19:04.320 | And now, well, let's just say we learned a lot.
00:19:08.560 | So if it feels like a long road ahead, you're not alone.
00:19:15.520 | But we promise it's totally worth it.
00:19:18.640 | Thank you so much for spending time with us today.
00:19:21.760 | We'll see you next time.