Context and broken promisesHero
Observation: Vendors sell autonomy while omitting the context contracts an agent needs to act reliably.
Business consequence: Deployments create speculative actions, leading to rework and lost customer trust.
Operational insight: Establish canonical data sources and ownership before enabling agent actions.
Core conflict: process ignoranceConflict
Observation: The technical stack is rarely the issue; the missing element is process: who decides and why.
Business consequence: Poorly framed autonomy produces costly incorrect decisions and organizational friction.
Operational insight: Reverse-map the process to routing logic and encode it as machine-checkable rules.
AI must sit inside the funnel, not next to it.
AI agents do not know when to hand offEscalation
Observation: Agents lack explicit escalation boundaries and attempt resolution beyond their remit.
Business consequence: Missed escalations increase SLA breaches and customer dissatisfaction.
Operational insight: Implement predicates for escalation and capture context snapshots at handoff.
The core mistake: routing is not designedRouting
Observation: Routing is often an ad-hoc rule set rather than a coordinating architectural layer.
Business consequence: Support teams receive irrelevant work and operational costs rise.
Operational insight: Centralize intent classification, rule evaluation, and destination selection in a routing service.
LLM without operational context — an expensive mistake
Observation: LLM outputs are plausible but not authoritative without validation against business state.
Business consequence: Pricing and policy errors lead to refunds, fines, and reputational harm.
Operational insight: Validate LLM suggestions through deterministic checks before actioning them.
Customers don't wait — they require immediate solutions
Observation: User satisfaction correlates more with time-to-resolution than with conversational sophistication.
Business consequence: Latency causes churn and measurable revenue decline.
Operational insight: Optimize the end-to-end critical path and remove redundant handoffs.
The myth of 'smart' automationAutomation
Observation: AI projects inherit undocumented complexity rather than simplify it.
Business consequence: Exceptions proliferate and support costs shift upward.
Operational insight: Standardize workflows and encode exceptions into routing rules first.
Architectures: from identification to accountabilityAccountability
Observation: Decision provenance is rarely recorded in a way that maps to roles and audit needs.
Business consequence: Missing traceability kills trust with regulators and partners.
Operational insight: Attach immutable decision logs and responsibility metadata to routed actions.
Most automation systems fail at the handoff layer.
Instrument escalations as KPIs: percent auto-resolved, escalation rate, and time-to-ownership. Use them to tune thresholds.
- Design routing as an architectural layer.
- Define decision boundaries and ownership.
- Integrate canonical data into routing contracts.
- Log provenance and measure operational KPIs.