Build Vs. Buy
Episode
16 min
Read time
2 min
Topics
Career Growth, Design & UX, Sales & Revenue
AI-Generated Summary
Key Takeaways
- ✓Core Value Rule: Teams should buy tools that are not core to customer value delivery rather than spending product, engineering, and design resources on peripheral systems. The exception occurs when engineering teams lack the technical capabilities to maintain critical infrastructure, making purchase faster than hiring specialized talent.
- ✓Data Ownership Priority: AI capabilities elevate data portability as a primary decision factor when evaluating vendor solutions. Before selecting platforms like Salesforce or HubSpot, teams must verify complete data export capabilities including comments and attachments, or risk losing control of business-critical information that could limit future AI applications and strategic flexibility.
- ✓Vendor Capability Assessment: Choose vendors who excel beyond internal capabilities in specialized domains like payments, where Stripe dominates because no reasonable timeline allows matching their expertise. Evaluate whether competitors use the same vendor, creating competitive risk, and whether the vendor supports unique business requirements that justify avoiding custom development.
- ✓Build Complexity Reality Check: Engineering teams often overestimate their ability to replicate SaaS functionality due to hidden business logic complexity. Conduct technical spike tests to validate feasibility and user experience capabilities before committing to custom builds. Even simple-seeming tools like DocuSign contain years of accumulated features serving diverse customer segments.
What It Covers
Petra Billet and Theresa Schwartz examine when product teams should build custom solutions versus buying existing tools, exploring how AI and vibe coding capabilities are shifting traditional decision frameworks around data ownership, vendor lock-in, and engineering complexity.
Key Questions Answered
- •Core Value Rule: Teams should buy tools that are not core to customer value delivery rather than spending product, engineering, and design resources on peripheral systems. The exception occurs when engineering teams lack the technical capabilities to maintain critical infrastructure, making purchase faster than hiring specialized talent.
- •Data Ownership Priority: AI capabilities elevate data portability as a primary decision factor when evaluating vendor solutions. Before selecting platforms like Salesforce or HubSpot, teams must verify complete data export capabilities including comments and attachments, or risk losing control of business-critical information that could limit future AI applications and strategic flexibility.
- •Vendor Capability Assessment: Choose vendors who excel beyond internal capabilities in specialized domains like payments, where Stripe dominates because no reasonable timeline allows matching their expertise. Evaluate whether competitors use the same vendor, creating competitive risk, and whether the vendor supports unique business requirements that justify avoiding custom development.
- •Build Complexity Reality Check: Engineering teams often overestimate their ability to replicate SaaS functionality due to hidden business logic complexity. Conduct technical spike tests to validate feasibility and user experience capabilities before committing to custom builds. Even simple-seeming tools like DocuSign contain years of accumulated features serving diverse customer segments.
Notable Moment
Theresa built her own task management system using Cloud Code and Obsidian in three days to maintain data ownership and integrate notes with tasks, while simultaneously rejecting the idea of building her own blog platform despite AI making both technically feasible.
Episode Transcript
Hi, folks. This is all things product with Petra Billet And Theresa Schwartz. And we're so happy you're here. Theresa, I had a coaching session this week about buy versus build conversations in product management. And it was a productive session, so we shared tips and tricks and discussed certain approaches. But I was wondering what's your take on it because I think it's a conversation that keeps coming up in every organization and in every product management career. So maybe we can record an episode on that, and maybe you could start with sharing your take on it. And I'm happy to add mine later on. Yeah. Actually, I've been thinking about this a lot because I think AI and, like, a AI prototyping and how easy it is to build with AI now is kind of changing the equation, but I don't think as much as people think. So I'm gonna share some personal experience, and I'm gonna give some examples, and then we can use this to, like, unpack the product question of build versus buy. Go ahead. Last summer, I shifted from WordPress to ghost. And in the process, I posted on LinkedIn, like, before I picked ghost. I posted on LinkedIn, and I said, what blog newsletter platforms do people recommend? And somebody wrote, you're geeking out on AI. Why not just vibe code one yourself? My reaction to that was like, why in the world would I build my own blog platform? Like, there's a billion out there. They're all adequate. This is I mean, my content is core to my business, but, like, the platform it runs on is not really core to my business. And so it was a little bit surprising to me, and I was like, wow. This is like I mean, I could see if it sounded fun as a fun project to me. Maybe I would do it, but, like, talk about an ongoing maintenance nightmare that I would not want. And then about a month later, I actually built my own task management system using Cloud Code and Obsidian, and a lot of people thought I was crazy. They were like, what is wrong with the 4,000 to do list apps out there? Like, why are you building your own? And so this They have no brain. Yeah. So this got me really thinking about build versus buy. And I think, like, I think about it let's I'll talk about how I traditionally have thought about it and now how I how, like, AI has changed it. So I think, traditionally, I thought about it as, like, if you're on a product team and you need a tool that is not core to the value you deliver to customers, you should buy that tool. You should not spend products and engineering and design time on something that is not core to your value stream. That's crazy to me. Could add to that in a second? Yeah. Go …
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Books, tools, and gear mentioned in this episode
SignalCast may earn commission on purchases via these links.
Tools
by Salesforce
“Before selecting platforms like Salesforce or HubSpot, teams must verify complete data export capabilities including comments and attachments”
by HubSpot
“Before selecting platforms like Salesforce or HubSpot, teams must verify complete data export capabilities including comments and attachments”
by Stripe
“Choose vendors who excel beyond internal capabilities in specialized domains like payments, where Stripe dominates because no reasonable timeline allows matching their expertise.”
by DocuSign
“Even simple-seeming tools like DocuSign contain years of accumulated features serving diverse customer segments.”
“Theresa built her own task management system using Cloud Code and Obsidian in three days to maintain data ownership and integrate notes with tasks”
“Theresa built her own task management system using Cloud Code and Obsidian in three days to maintain data ownership and integrate notes with tasks”
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