All Things Product with Teresa and Petra

Build Vs. Buy

21 snips

Jan 27, 2026

They debate when to build tools versus buying them, and why the choice keeps recurring across product teams. AI's role in lowering prototyping cost and enabling bespoke tools comes up. Personal stories contrast moving platforms with building a custom task system. The conversation centers on data ownership, vendor lock-in, portability, and treating make-or-buy as a discovery problem.

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ANECDOTE

Why Teresa Chose Ghost Over Building

Teresa moved from WordPress to Ghost because platform choice wasn't core to her value and maintenance was a burden.
She later built a personal task system, surprising others who asked why she didn't use existing to-do apps.

ANECDOTE

Building A Personal Task System Fast

Teresa built her own task management system using Claude Code and Obsidian in a few days because her workflow is idiosyncratic.
People questioned her because many capable to-do apps already exist.

INSIGHT

Core Value Determines Make Or Buy

If a tool is not core to your value stream, don't build it; buy it instead to save product and engineering time.
If it is core, evaluate build cost, vendor options, and competitive risk before deciding.

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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

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