TBW / AGENTIC AI / AUTOMATION
AI Workflow Automation
Combine deterministic automation with bounded AI decision points, approvals and audit trails for defined business processes.
Purpose and Approach
TBW maps a business process, separates fixed rules from variable interpretation, and designs the smallest controlled automation that can be tested and operated. An agent is a bounded component—not permission to bypass process ownership or approval.
Workflow or Agent?
| Approach | Choose when | Example | Control |
|---|---|---|---|
| Deterministic workflow | Known steps, stable rules and predictable inputs | Scheduled export, fixed approval routing, synchronization or notifications | Defined state transitions and exception handling |
| Agent inside workflow | Inputs vary; interpreting a request or choosing a bounded path adds value | Classify a ticket, summarize a case, draft a response or choose an approved tool | Constrain tools, verify output and escalate uncertainty |
| Consequential action | A step sends externally, changes records or permissions, deletes data, approves money or affects a customer | External send, production change or payment approval | Apply appropriate policy checks or human approval before execution |
Use deterministic automation where the process is deterministic. Add an agent only where variable reasoning provides value.
Automation Patterns
Triage and Routing
Classify an incoming request; hand a proposed queue and reason to the routing rule.
Enrichment
Fetch approved context and attach evidence to a case without expanding the reader’s access.
Drafting for Approval
Prepare a message, document or ticket update; require review before external delivery or a consequential write.
Scheduled Digests
Summarize approved sources on an agreed schedule with provenance and a clear audience.
Event-Driven Actions
Process authenticated source-system events with validation and duplicate detection.
Workflow + Agent
Insert one bounded interpretation step into a deterministic sequence, then return control to the workflow.
The Control Envelope
Before enabling a run, define the initiating identity, owner, allowed systems and actions, tool allowlist, step and time limits, data classification, approval points, audit events and safe failure behavior. The runtime should enforce these outside prompt text.
Before a step
Authenticate the actor; validate destination, data class and allowed action.
At a decision
Bound model/tool options, inspect arguments and record the chosen path.
Before a write
Show the exact proposed target and change to an authorized approver when required.
After a run
Record outcome and exceptions without logging unnecessary sensitive content.
Example flow: authenticated event → validated input → fixed routing → bounded AI classification → policy check → human approval where required → scoped action → recorded result.
Reliability Engineering
AI does not remove distributed-systems reliability requirements. A run must be safe when the network fails, a tool times out, an event is delivered twice or a worker restarts.
Duplicate-safe execution
Use idempotency keys, event IDs and duplicate detection before external side effects.
Retry discipline
Apply bounded retries with exponential backoff; distinguish transient errors from permanent policy failures.
Recoverable failures
Set timeouts and dead-letter handling; permit reviewed replay rather than automatic endless loops.
Safe stop and recovery
Alert an operator, preserve state, and design compensating actions where reversal is possible.
How to Measure a Workflow
Agree on a baseline and the unit of analysis before rollout: one request, event or case. Segment by workflow version and exception type so a rise in volume is not mistaken for improved completion. The measures below are diagnostic categories, not promised outcomes or target values.
- Workflow completion: count runs that reach the intended terminal state, alongside abandoned and manually completed runs.
- Failure and retry rate: separate transient retries, exhausted retries and permanent validation or policy failures; track repeat attempts against the same event ID.
- Human corrections: review changed classifications, revised drafts and overridden routing decisions against representative cases.
- Blocked unsafe actions: record denied tool calls, disallowed destinations and approvals refused; investigate both true catches and false positives.
- Exception volume and review backlog: show queue age and unresolved cases as well as counts, so work is not merely shifted to reviewers.
- Operator feedback: capture which alerts, replay steps and runbook instructions are useful in real incidents.
Review these together; a faster workflow is not an improvement if it increases incorrect writes or hides exceptions.
Platform Options
Appropriate implementations may use n8n, Microsoft or Salesforce workflow ecosystems, an internal workflow engine, API orchestration or event-driven services. These are architectural examples, not partnerships or deployed-customer claims.
Whatever the platform, protect administration behind authenticated access; authenticate webhooks and restrict their sources; keep credentials in a vault; separate environments; limit roles; log executions appropriately; and document ownership and recovery.
How This Connects to Use Cases
Use-case pages give domain-specific details rather than repeating this automation design:
Implementation and Deliverables
Start with one bounded process. Inventory triggers, data and permissions; map the normal path and exceptions; build a test environment; run duplicate, timeout, invalid-input and approval-bypass scenarios; pilot with an owner; then define the operator handover.
Design pack
Workflow architecture, integration map, credential model and a written control envelope.
Control evidence
Approval matrix, access boundaries and test scenarios for permitted and blocked actions.
Operations
Error-handling design, runbook and monitoring recommendations.
Related: Agentic AI · AI Agents · Agent Design and Orchestration · Integrations
Frequently Asked Questions
When should we use an agent instead of a fixed workflow?
Only when variable inputs require interpretation that fixed rules cannot handle adequately; compare quality, risk and operating cost first.
Can automation work without agent write access?
Yes. An agent may classify or draft while a deterministic service or person makes the approved change.
How do you prevent duplicate actions?
Use source event identifiers, idempotency keys and destination checks; test retries after partial failures.
How are failed steps handled?
Classify the error, bound retries, dead-letter unresolved events, alert an owner and require reviewed replay for consequential actions.
Can we start with one small workflow?
Yes. Choose a bounded process with an owner, representative examples and explicit stop conditions.
Discuss a Bounded Workflow
Bring one process, its systems and the actions it may take. We can identify the rule-driven steps, AI decision points and controls.