Founder Habits You Need To Drop To Be A Great CEO

1. Key Themes

The Fundamental Shift from SaaS to AI Product Development

The traditional SaaS playbook—talk to customers, prioritize their requests, build and iterate—breaks down with AI because customers can't articulate what's possible with jagged AI capabilities. "In SaaS, you go to your customers, you ask them what they want and what they're going to pay for. You prioritize that list and you start building it... With the capabilities of AI, because they're so jagged, it's a technology first understanding of what is possible. If you go to your customers and tell them and ask them what they want, like they're not even going to be able to describe what's possible" [00:11:00]. This requires companies to adopt a bottom-up, technology-first approach where engineers and product leaders must deeply understand model capabilities before building, fundamentally inverting the traditional enterprise software development model.

The Year-Long Transformation Timeline for Incumbent Companies

Even for a relatively agile 800-person company, genuine AI transformation required a full year of deliberate organizational change. Spencer hired a new engineering leader (Wade Chambers) in October 2024 and acquired Command AI, both serving as "change agents" [00:04:39]. The pivotal moment was "AI Week" in June, where leadership live-coded features using AI tools in front of the entire organization, followed by a company-wide hackathon [00:09:09]. "It's still taking us a full year to get the team fully on board and ramped and believing and seeing and building" [00:06:20]. This suggests that incumbent advantage in AI transformation is not about speed but about having the resources and runway to execute a methodical cultural shift.

The Unexpected Top-Down Adoption Pattern of AI

Unlike previous technology waves where engineers were early adopters pushing tools upward, AI adoption is inverted—executives and investors bought into Sam Altman's vision before engineers believed in the capabilities. "Sam Altman is the best salesperson of this generation by no bar none... You have these execs, investors already bought in, executives are bought in, world leaders are bought in... the capabilities are still trying to catch up" [00:12:04]. This created frustration among engineers who saw "tremendous what they feel is grifting in AI where it's a lot of talkers. Not many doers" [00:13:01], forcing founders to demonstrate value through training and hands-on experience rather than strategic mandates.

2. Contrarian Perspectives

AI Visibility Products Are Not Real Businesses—Just Lead Generation

Spencer publicly argued that AI visibility/monitoring startups are "features not companies," which angered many in the startup community. His team built their own AI visibility product "in a few months" and gave it away for free, doubling their weekly signups [00:14:43]. "The commoditization is going to happen real, real fast... the real business has to be downstream of AI visibility" [00:24:38]. He contrasts this with AirOps, which has "a whole content generation business to help you create blog posts and other material" as their real business [00:25:20]. The controversial implication: many YC-backed AI infrastructure companies may lack defensibility because incumbents can replicate their core value proposition as a marketing tool.

Enterprise AI Adoption Failure Creates the Real Opportunity

While many focus on building general-purpose AI agents, Spencer sees the security and compliance concerns preventing enterprise AI adoption as the bigger opportunity. "There's all these studies being like, hey, enterprise is failing to adopt AI. And if you look at, you kind of dig into the Y behind it, there's all these security and compliance concerns. And so, okay, I think there's a huge opportunity to solve those to get much faster adoption of these products" [00:28:18]. This suggests the winning AI companies may not be those with the most advanced models, but those solving the operational and governance problems blocking deployment.

Most Founders Should Not Start Companies—The Pain Isn't Worth It

Counter to the typical founder cheerleading, Spencer explicitly states: "It's extraordinarily emotionally painful. I do not recommend it for the vast majority of people... there's so many times like every few years I've gotten to a spot where I feel like I want to quit the business" [00:36:20]. He argues the "worst" approach is "hey, you know, I'll do it. And if it takes off, I'll double down. If not, I'll go back to grad school or a job" [00:37:09]. The harsh reality: "there is a point that you get to a year, maybe two years in where from a rational standpoint, you probably should quit. But for whatever reason, those successful ones don't" [00:37:32]. Success depends on irrational commitment anchored to intrinsic motivation, not optionality.

3. Companies Identified

Cursor

Description: AI-native coding assistant tool that has transformed software engineering productivity.

Why mentioned: Spencer cited Cursor as a proof point that AI can fundamentally change workflows, specifically stating it had a "transformative effect" on software engineering [00:04:04]. This was one of the key pieces of evidence that convinced Amplitude's leadership team that AI was ready for enterprise applications.

Quote: "It was very clear that you would be a lot more productive using these things... That was kind of the first of us saying, okay, there's something there there" [00:04:19]

Command AI

Description: YC company acquired by Amplitude that was building AI-powered user guidance and chatbot products.

Why mentioned: This acquisition in October 2024 was one of the two major catalysts (along with hiring Wade Chambers) that jump-started Amplitude's AI transformation. The Command team served as "change agents" within Amplitude [00:04:44].

Quote: "They had been building a product where they were trying to smartly trigger guides to end users just based on if they were confused. And they created this chatbot that very much like an Intercom Fin" [00:05:09]

AirOps

Description: AI content generation company that started with visibility but built a real business around content creation.

Why mentioned: Spencer holds up AirOps as the right model for AI visibility companies—using visibility as an entry point but building a substantial business "downstream" with content generation for blog posts and other materials [00:25:20].

Quote: "There is a business that is very viable here, which is what AirOps is doing, where they're, yes, they have some visibility aspects, but they have a whole content generation business to help you create blog posts and other material on that. And that's their real business" [00:25:20]

Notion

Description: Workspace and documentation tool competing with Google Workspace.

Why mentioned: Spencer identifies Notion as an example of successfully competing against Google in the B2B workspace market, which he considers one of the biggest opportunities because "Google is the worst B2B company of all time" [00:26:44].

Quote: "I think what the notion guys, for example, are doing as a competitor to Google Docs is very exciting" [00:27:01]

4. People Identified

Wade Chambers

Description: Engineering leader hired by Amplitude in October 2024, described as a "Silicon Valley legend."

Why mentioned: Wade was one of the two critical hires (along with the Command AI acquisition) that catalyzed Amplitude's AI transformation. He had previous experience working on AI and knew people "on the bleeding edge of leveraging the capabilities of models" [00:04:54].

Quote: "I hired a new engineering leader, this guy Wade Chambers, who's just Silicon Valley legend... Wade had been working on AI in his previous company and had known a bunch of people who were on the bleeding edge of leveraging the capabilities of models" [00:04:39]

Mitch Morando

Description: Sales executive and coach who helped Spencer learn B2B sales.

Why mentioned: Mitch was instrumental in teaching Spencer how to do enterprise sales, coaching him weekly and challenging him to think deeper about customer pain points rather than features.

Quote: "We work with this guy, Mitch Morando, who coached, you know, as a sales exec, who had gone on to coach a bunch of other companies... He would just come in once a week and just beat me up and just being like, hey, you don't really, you know, what's the customer pain?" [00:33:13]

James (from Command AI)

Description: Founder and CEO of Command AI (acquired by Amplitude).

Why mentioned: James worked alongside Spencer and Wade to design Amplitude's "AI Week" training program that transformed the organization's understanding of AI capabilities.

Quote: "I started working with James, the founder, CEO of Command, as well as Wade, our engineering leader to figure out how do we train the organization on AI" [00:08:57]

Leo Chang

Description: Amplitude engineer who built the AI visibility product.

Why mentioned: Leo exemplifies bottom-up innovation—he was planning to leave Amplitude to start a company but instead built AI visibility as an internal project, which became a massive success, doubling new signups [00:14:14].

Quote: "You had one of our engineers, this guy named Leo Chang, who built AI visibility and he just wanted to he was actually going to leave amplitude to start a company... that launch product launch doubled new signups to amplitude" [00:14:14]

Brian Geori

Description: Amplitude engineer who built the company's MCP server.

Why mentioned: Brian created the MCP server as an unplanned project that emerged from AI Week, demonstrating the value of bottom-up experimentation [00:14:03].

Quote: "Our MCP server, which we didn't even plan for, like that was actually one of our engineers Brian Geori, who's incredibly excited" [00:14:03]

Bull Newton

Description: Amplitude's "very best designer."

Why mentioned: Bull exemplifies how AI transformation extends beyond engineering—he self-selected to focus exclusively on the AI chat interface to ensure excellence at launch [00:23:06].

Quote: "Our very best designer at amplitude. This guy named Bull Newton... he was like, no, I got to focus in like, let's say, noted some of these for a little bit so I can go really deep on this chat interface" [00:23:06]

5. Operating Insights

Train Through Demonstration, Not Strategy Decks

Amplitude's breakthrough came when leadership live-coded features in front of the entire organization during "AI Week." "We had one of our product leaders, vibe code, like a dark mode for amplitude in front of the entire organization, which was actually very scary... the entire engineering product and design organization saw what was, it's like, wow, okay, all the leaders with an amplitude are saying, this is the thing and they're showing how they're doing it" [00:09:36]. The format was two days of training followed by a hackathon where teams used AI tools on their existing work—not greenfield projects. This "show, don't tell" approach proved far more effective than executive mandates.

Two Reorganizations in One Year May Be Necessary for Transformation

Spencer conducted two separate reorganizations of the engineering, product, and design organization in 2024. "We've done two reorganizations in the engineering product and design organization since the since the start of this year... There were leaders and executives and different people who were very much kind of in the sass modality, but were not on the bleeding edge of AI that just unfortunately were not quite the right fit" [00:15:52]. While disruptive, this signals that genuine transformation may require accepting short-term organizational pain to bring in people with the right capabilities and mindset.

Acquisitions as Cultural Catalysts, Not Just Technology

Amplitude acquired multiple YC companies (Command AI, Inari, June) not just for technology but as "change agents" to shift internal culture. "We brought in all these great YC founders and then kind of meld with them with a lot of long time amplitires and that combination has been very, very special" [00:16:32]. The Command team specifically brought hands-on experience with AI product development that served as proof points for skeptical engineers. This suggests M&A strategy should explicitly consider cultural transformation value, not just product or market expansion.

6. Overlooked Insights

The "Uber for Tech Support" Remains Unsolved

In a brief aside, Spencer mentioned running an IT support business in high school and expressed genuine frustration that no one has built a scaled solution for on-demand tech support: "There has to be a Uber for tech support... The fact there's still not a scaled solution, it just blows my mind for this. Like you have a lot of people that are older, that are not native to technology that have a bunch of money and want this stuff to be set up. And you have this young generation that desperately needs money that has a ton of expertise on technology" [00:28:36]. This throwaway comment reveals a massive market inefficiency—the demographic aging into wealth needs technical help, Gen Z has the skills and needs income, yet no one has successfully built the marketplace. With AI's ability to help diagnose issues remotely and guide repairs, this might be newly feasible.

The 10-Year Founder CEO Limit May Be Structural, Not Personal

Spencer made a subtle but profound observation about why most successful founder CEOs leave after about a decade: "Even if you look at the successful founder CEOs, after about a decade, most of them leave. And in my mind, it's actually for this very reason is could be because being a large company executive is different. And because you can't lead by example everywhere all the time" [00:39:13]. This suggests the typical founder CEO departure isn't about burnout or wanting to start something new—it's about the fundamental incompatibility between the founder operating mode (leading by example on the hardest problems) and large company requirements (judging others' work across domains you can't personally master). This has implications for succession planning and board expectations—the transition might be inevitable regardless of founder quality.