Automation is a design problem
An AI workflow is a business process in which AI steps such as reading, drafting and classifying are combined with deterministic steps and human approval gates. The hard part of workflow automation is not the AI. It is deciding, precisely, which steps a machine should own, which steps a person should own, and what happens at the boundary. Automating a badly designed process just produces mistakes faster. So every Clodron workflow project starts by mapping the process as it really runs today, including the exceptions and workarounds that never made it into the official version.
The building blocks
A production AI workflow is assembled from a small set of recurring blocks:
- Trigger: the event that starts a run, such as an inbound email, a form submission, a new CRM record or a schedule.
- AI steps: the reading, drafting, classifying, extracting and deciding that a language model handles.
- Deterministic steps: lookups, calculations and API calls where you want exact, repeatable behavior rather than model judgment.
- Approval gates: defined points where a named person reviews, edits or rejects the agent's work before it takes effect.
- Escalation paths: what happens when the agent is uncertain, the data is missing or the customer is angry. Every workflow needs a route to a human.
- Audit log: a record of every step, input and decision, so any outcome can be reconstructed later.
Placing the approval gates
The rule of thumb is simple: gate on irreversibility and stakes, not on difficulty. An agent can safely do difficult internal work like summarizing a contract, but sending money, signing terms or emailing an important customer should pass a human even when the task is easy. Start with more gates than you think you need, measure how often reviewers actually change anything, and remove gates where the edit rate stays near zero. That gives you a paper trail justifying every expansion of autonomy.
Common failure modes
Three mistakes account for most failed automation projects: automating the exception path first instead of the boring high volume path, giving the agent write access before anyone has watched it work in draft mode, and skipping the audit log until something goes wrong. All three are avoidable with sequencing. Clodron ships workflows in stages, with the agent drafting first, acting under approval second and acting autonomously only where the numbers prove it is safe.