Build-Buy-Use Agent Decision Loop
Map recurring work, choose build or buy, and operationalize agents continuously.
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 6
- Confidence
- 95%
The loop begins by observing actual work, ideally through screen recordings or similarly detailed process evidence. A frontier model analyzes those examples to identify repeatable inputs, decisions, outputs, and opportunities for agent assistance. The practitioner then evaluates whether an existing product can perform the work or whether the workflow is sufficiently niche to justify a custom agent, AI workflow, custom GPT, or specialized assistant. The choice is not complete until ownership, human review, exceptions, and regular use are defined. As the agent operates, its failures and uncovered edge cases become inputs to another improvement cycle. The framework preserves the domain expert's judgment while using agents to scale execution far beyond manual capacity.
Origin
Extracted from Marketing Against The Grain as the hosts reframed agent adoption around three actions: build, buy, and use.
Core principles
- 01Start from real work rather than agent novelty.
- 02Buy capable general solutions and build only distinctive workflows.
- 03Use domain expertise to supervise automated craft.
- 04Treat ongoing adoption as part of the design decision.
How to run it
- 1
Capture real work
Record representative executions of the workflow, including inputs, decisions, tool changes, and final outputs.
Pro tip Capture both routine cases and difficult exceptions.
Watch out A polished procedure document may omit the tacit decisions visible in real execution.
- 2
Model the workflow
Ask a capable model to identify repeatable stages, decision points, data dependencies, and candidate agent roles.
Pro tip Request a proposed division between automated work and human judgment.
Watch out Do not automate a process that the team cannot yet explain or evaluate.
- 3
Search for existing agents
Evaluate products that already cover the general or standardized portions of the workflow.
Pro tip Test with the recorded examples rather than relying on product demonstrations.
Watch out Buying a tool without testing workflow fit can add another unused system.
- 4
Choose build versus buy
Buy mature commodity capabilities and build the niche logic, integrations, or context that differentiates the work.
Pro tip Include maintenance, permissions, reliability, and monitoring in the comparison.
Watch out Custom building creates an ongoing operational obligation.
- 5
Define operational use
Assign an owner, trigger, review path, exception process, and measurable output standard.
Pro tip Integrate the agent where the work already happens.
Watch out An agent that is technically complete but not routinely used creates no leverage.
- 6
Improve from evidence
Review outcomes and failures, then update instructions, context, integrations, or the build-buy boundary.
Pro tip Track error classes rather than fixing isolated outputs.
Watch out Expanding autonomy before reliability is demonstrated increases risk.
In the wild
A marketer records several executions of a recurring campaign-analysis task and gives the recordings to a frontier model. The model identifies research and summarization as commodity capabilities available in an existing agent, while the company's unique prioritization logic requires a small custom workflow.
→ The team buys the general capability, builds only its differentiating logic, and establishes a recurring review process.
Common mistakes
Starting with the tool
Choosing an agent before observing the work encourages automation theater rather than workflow improvement.
Building commodity capability
Custom development is wasteful when a reliable product already handles the standardized work.
Ignoring ongoing adoption
The build-versus-buy choice fails if no trigger, owner, review process, or regular usage pattern follows it.
Is it for you?
Best for
Domain experts with recurring, observable workflows that consume substantial manual effort.
Not ideal for
Rare, poorly understood, high-risk tasks that lack stable inputs, review criteria, or accountable owners.
From the transcript
“I think you have to build buy and use agents”
“we just we'll do screen recordings of the work we do and then just put those into the frontier models and say how can I…”
“And understanding what that work is, when to build versus buy, and then how to like actually use on an ongoing basis is going to,…”
From the episode
5 AI Tools The Smartest Marketers Are Using In 2026