Build vs buy for AI agents: what to build, and what to buy around it
Build the part only your agent does: its logic, its prompts and your business rules. Buy the parts every agent needs around it: approvals before risky actions, an audit trail of every step, evals before a change ships, and rollback. A coding agent can write all of them. Writing them was never the expensive part, though. Owning them is.
Build vs buy is the choice between writing a part yourself and paying a vendor for it. Most teams are making this call now. In October 2026, Gartner’s CIO survey found that 71% of CIOs plan to deploy agentic AI within 12 months, and only 21% have agentic AI governance today.
What does an AI agent need around it before it touches real work?
The same few things, whatever the agent does:
- Approvals. A person says yes before a risky action runs, like a refund or an email to a customer. Reading data waits for no one.
- An audit trail. Every step on record: each model call, each tool call with its arguments, what came back, and who approved what.
- Evals and expert reviews. A new version is checked against cases your people already judged, before customers see it.
- Versions and rollback. You know which version ran, and going back is one step, not a rebuild.
None of this is what makes your agent yours.
If a coding agent can write all of it, why not build it?
Because the effort moved rather than went away. The work that used to go into writing the code now goes into reviewing it properly. Building it takes tokens, and so does keeping up with how fast models and practices change. Then there is your team’s focus, better spent on what only your agent can do.
For example: Acme builds its order-desk agent’s refund tool, its refund rules and its tone with customers. Around those sit approvals, a record of every run, checks against past refunds and a way back, which a coding agent could write quickly. Then a new model calls tools differently, or an auditor asks for evidence in a new form, and each change is Acme’s job for as long as the agent runs. More in When a coding agent builds your AI agent.
For a business leader, the question was always “should we build it?”, and the answer was a business case. When code takes a prompt to write, building in-house looks like a saving. The equation is not that simple.
What stays with your team either way?
The decisions: which failures matter, which actions need a person’s yes, and what a good answer looks like for your customers. Those are yours whether you build or buy, so they don’t tip the choice. What you can buy is building and maintaining the gates that enforce them, which leaves your team more time for the decisions themselves.
Does a rollback undo what the agent already did?
No. A rollback decides which version runs next. It can’t take back an order change or an email that already went out. What protects the customer is a yes before the risky call, plus a record of exactly what changed, so you can make it right. More on that in Questions our customers ask.
How do you compare the cost of building with the cost of buying?
Weigh the cost of owning a part over time against the vendor’s bill, not the cost of the first build. A component can be cheap to generate once and still become a recurring job: models change, rules change, and old reviews go stale.
The other side of the scale moved too. Coding agents make building a real option, so every vendor has to earn its price. A vendor used to be a product you fit your work around. Now it can be the parts your coding agent builds on.
| Build it yourself | Buy it and build on it | |
|---|---|---|
| Your agent’s logic, prompts and rules | You write them | You write them |
| Approvals, audit trail, evals and rollback | You write, review and maintain them | They come with what you build on |
| When models and practices change | Your team updates them | The vendor keeps them current |
| What you pay | Your team’s time and tokens, for as long as it runs | The vendor’s bill |
Where Kindgi fits
Kindgi is an agent framework for production: your coding agent writes the tools, agents and flows in your own code, and Kindgi runs them and keeps every step on record. It’s the stack under your agents: approvals per tool, a journal of every step, signed evidence for auditors, replays against runs your people already corrected, and a version pinned per project, where going back is one more pin. We keep those parts tested and current. Your business logic stays yours, and you choose where it runs.
The guides: ask before a tool runs, read the journal, export signed evidence and release an agent version.
How this was written: a coding agent drafted it from our docs, our code and questions our customers ask. We checked every claim, edited it and said yes. We publish articles like this partly because we want you to find us, including through AI assistants. More in How we write our posts.