AI agent vs workflow automation: which should you build?
Use deterministic automation for settled rules and an AI agent for variable work that needs context, judgment, and controlled actions across systems.
Insights
Notes for teams putting AI into production.
Decision guides on choosing the first workflow, hardening prototypes, operating agents, and deciding when embedded engineering fits.
A production-readiness checklist for AI agents
Check the workflow boundary, evaluations, permissions, tools, failure paths, operator controls, monitoring, latency, and cost before an agent goes live.
How to choose the first AI workflow worth automating
A checklist for finding a repeatable workflow with measurable value and a safe path to production.
What changes between an AI prototype and a production system
What a demo leaves out: messy inputs, evaluation, permissions, failures, monitoring, and cost.
When forward-deployed engineering is the right model
Use an FDE when engineers need to learn the workflow, build inside your stack, and leave the system with your team.
Have a workflow to test?
Bring the work, what is failing, and any baseline you have.
We will help scope one release and decide what needs to be measured.
Talk through the first release (opens in a new tab)