All Things Product with Teresa and Petra
All Things Product with Teresa and Petra

Build Vs. Buy

27 January 2026 16:47 Petra Wille & Teresa Torres

Listen to episode

About this episode

What this episode covers: Why build vs. buy keeps coming up

  • It shows up in every product org, at every stage
  • AI makes building feel easier — but doesn’t eliminate the real tradeoffs

The classic rule of thumb (and its limits)

  • If something isn’t core to your value stream, don’t build it
  • Even when it is core, vendors may still be better positioned (payments, invoicing, infrastructure)

Teresa’s two contrasting examples

  • Why she moved from WordPress to Ghost instead of building her own blog platform
  • Why she did build her own task management system — despite plenty of existing tools

The role of data ownership

  • When the underlying data becomes the real product
  • How task management, notes, and workflows become deeply personal and idiosyncratic
  • Why owning and controlling data changes the build vs. buy equation

How AI is changing the decision

  • Cheaper prototyping and “vibe coding” lower the cost of building
  • Smaller, more targeted tools become viable alternatives to big SaaS platforms
  • Pressure on vendors to improve data portability

Vendor lock-in and data portability

  • Why exports aren’t always enough
  • What to look for when evaluating tools like CRMs or course platforms
  • When buying still makes sense — and when it doesn’t

Build vs. buy as a discovery problem

  • Treating options as assumptions to test
  • Feasibility testing on the build side
  • Actually trialing vendors instead of trusting marketing claims

A caution on complexity

  • Why “we can build anything” isn’t the same as “we should build this”
  • How long-lived products accumulate hidden complexity over time
  • Being honest about engineering capabilities and maintenance costs

Key takeaways

  • Build vs. buy isn’t just about speed or cost — it’s about core value, data ownership, and long-term responsibility
  • AI lowers the barrier to building, but doesn’t erase complexity
  • Treat build vs. buy decisions like any other discovery effort: test assumptions, prototype, and validate before committing
  • Ask not just can we build it, but should we own it?

Resources & Links:

  • Follow Teresa Torres: https://ProductTalk.org
  • Follow Petra Wille: https://Petra-Wille.com

Mentioned in this episode:

  • Wordpress
  • Ghost
  • Vibe code
  • Claude Code
  • Obsidian
  • Stripe
  • Teachable
  • Melissa Perri and her Product Institute
  • Trello
  • Evernote
  • OmniFocus
  • Dropbox
  • OpenAI
  • Salesforce
  • HubSpot
  • DocuSign

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 All Things Product with Teresa and Petra. All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.