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💡 Our Thesis

At Swan, we don’t just preach agent-led business — we run on it. We spend over $400K a year on our AI agent stack, not for the vanity of being “AI-first,” but because it delivers real leverage.

But here's the hard truth: most founders burn time and money trying to build what they should’ve bought, or buy tools they can’t shape to fit their edge.

This guide helps you avoid both mistakes.

🎯 The Matrix: Build vs Buy for AI Agents

We break the decision down into a 2x2 matrix, based on two factors:

X-Axis: Use Case Type

• Commoditized → horizontal, repeatable, generic (e.g. CRM sync, meeting prep)
• Unique → specific to your GTM, playbook, voice, or edge

Y-Axis: Internal Capability

• Low → no prompt chops, no agent-building infra, limited time
• High → fluent in prompt design, API orchestration, agent debugging

🧩 What Each Quadrant Means

1. 🟩 Bottom Left: Commoditized Use Case + Low Capability
   • Action: Buy an off-the-shelf, opinionated solution
   • Don’t tinker. Pick a tool that solves the job with defaults baked in.
   • Example: opinionated simple end to end Meeting assistant like Fathom
2. 🟥 Bottom Right: Unique Use Case + Low Capability
   • Action: Don’t build, don’t buy
   • You're tempted to solve something strategic, but you're not ready.
   • Wait until you’ve developed the need or built internal muscle.
   • Example: Custom meeting assistant that contextualize data from CRM + data warehouse + email
3. 🟦 Top Left: Commoditized Use Case + High Capability
   • Action: Buy an open platform or framework you can customize
   • Use off the shelve solution with no code / customization capabilities
   • Example: Platform to build bespoke meeting assistants like Attention
4. 🟨 Top Right: Unique Use Case + High Capability
   • Action: Build with low/no code tools or frameworks
   • This is where the magic happens. You’re solving for your edge — build agents that adapt and evolve.
   • Example: Build the meeting assistant of your dream that syncs context from CRM, emails, calendar, and online research