Running local AI agents on laptops breaks the second you close your lid or step into a Wi-Fi dead zone. Beyond the personal frustration, it leaves engineering organizations with zero visibility or governance over what those agents actually executed.
Here is how to make practical build versus buy decisions across your agent stack:
- Centralize execution inside temporary sandboxes so work continues reliably and audit logs remain intact.
- Avoid unconstrained local tools in favor of harness engineering that enforces permission boundaries.
- Treat infrastructure options as replaceable commodities by keeping your orchestration layer decoupled.
- Use off the shelf frontier models, but build internal evaluation frameworks to benchmark real performance and cost.
Your team should buy standard infrastructure components and build only the evaluation logic and safety constraints that represent your actual product judgment.
Read the full article to explore how these patterns apply at every layer of the stack:
Build vs. buy in agentic engineering | Upsun
How Upsun engineers decided what to build and what to buy at each layer while creating Dispatch, its AI agent platform
upsun.com
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