Automating a Broken Process
Anti-pattern: deploy agents on top of a workflow that is already dysfunctional, so the dysfunction is amplified at machine speed instead of resolved.
Problem
If the underlying process has unclear handoffs, ambiguous decision rules, undocumented exceptions, or contradictory policies, the agent inherits all of those defects and executes them at machine speed and scale. Errors that a human would catch by hesitation or by asking a colleague are now produced in seconds, sometimes faster than downstream systems can absorb. The team measures cycle-time reduction and declares success, while error rate, rework, and customer escalations climb. Both Nordic sources name the same shape independently: techsy.io warns that 'an agent will automate a broken process faster but will not fix it', and HiQ frames the maturity-stage skip ('precision, speed, scalability') as efficiency-first agent adoption on top of broken workflows.
Solution
Don't agentify dysfunction. Run a process-redesign pass first — name the handoffs, document the decision rules, surface the exceptions. Then decide what shape of automation fits: a linear deterministic flow may fit Zapier or workflow tooling; only genuinely judgment-bearing steps warrant an agent. See demo-to-production-cliff for the operational gates that catch dysfunction-amplification once an agent is live, and rigor-relocation for where review discipline should land when humans step out of the inner loop.
When to use
- Never. Cite when reviewing an agent-deployment proposal that has not run a process-redesign pass.
- Demand a documented handoff/decision-rule/exception map before sign-off.
- Stage the redesign as an explicit deliverable, not as an implicit assumption.
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