Marketing
A proposed workflow for marketing. Revised 17 September 2026. The roles below are design options, not claims that these agents are deployed or that multiple agents are necessary.
The business opportunity
A marketing team needs to explain a new service to a specific audience using accurate claims and approved brand material.
Start with the simplest useful solution
Compare the agent with templates, approved copy, and a conventional campaign experiment. Use the same representative cases and count human review, errors, integration, and ongoing operation. Add an agent only where choosing what to investigate or handling varied evidence improves the result.
Proposed responsibilities
- Agent
- Content drafting agent
- What it does
- Produces drafts against brief, brand corpus and prior performance
- Autonomy and learning position
- A2, L1
- Notes
- Human edit before publication is the control, not a courtesy
- Agent
- Campaign operations agent
- What it does
- Assembles, schedules and QAs campaign mechanics across platforms
- Autonomy and learning position
- A3, L1
- Notes
- The best-evidenced win: mechanical, bounded, verifiable
- Agent
- Performance analysis agent
- What it does
- Explains campaign performance against history with provenance
- Autonomy and learning position
- A2, L2
- Notes
- Explains; the marketer decides
- Agent
- Localisation agent
- What it does
- Adapts approved content per market against local rules
- Autonomy and learning position
- A2 to A3, L1
- Notes
- Local disclosure and labelling rules vary sharply
Start with one agent and ordinary tools. Separate a responsibility only when it needs different permissions, independent review, or its own operating schedule. The autonomy and learning positions are starting choices to test, not certification levels.
How the architecture supports the task
Knowledge and memory (direct: brand and claims corpus with an owner), human oversight (direct: publication approval), observability and audit trail (direct: synthetic-content labelling), evaluation and release (direct), tool gateway, identity and policy, runtime (supporting).
Controls and human decisions
Review product claims and image rights. Apply audience permissions and publication approval outside the model.
Give every tool call a task identity, a limited permission scope, and a recorded result. Before a write, check that the source record has not changed. Stop when required evidence is unavailable, the task budget is reached, or a proposal exceeds the authorised scope.
A useful investigation loop
Observe the exception, identify the missing fact, request that evidence, and check whether it changes the proposed action. Repeat only while there is a concrete unanswered question. End with a reviewed proposal, a confirmed result, or an explicit request for human help.
Economics and measures
Measure incremental qualified response, conversion, cost, complaints, and correction effort.
Agree the baseline with the process owner. Count value only after the outcome is confirmed. Compare the value of recovered time and improved outcomes with the full cost of tools, models, evidence preparation, supervision, and correction.
Limits to test
Generating more content is not evidence of business growth. Test audience relevance and factual accuracy before increasing volume.
Evaluate ordinary cases, uncommon failures, conflicting evidence, and recovery after an interrupted action before expanding authority.
External reading
The workflow above is the guide's proposal. These sources support the general investigation and risk-management methods; they do not validate the proposed business result.
- ReAct: reasoning and acting with language models, 2022. Research basis for alternating reasoning and tool use.
- NIST AI Risk Management Framework, 2023. General framework for managing AI risks.
Sources reviewed 17 September 2026.
Cite this page
Written by Murali Sid, Founder and AI Systems Architect, last updated 15 October 2026. Licensed CC BY-SA 4.0, so quote it freely with attribution.
Murali Sid (2026). Marketing. Agentic Architecture Skills. https://www.agenticarchitectureskills.com/library/blueprints/departments/marketingMachine-readable version of this page: /library/blueprints/departments/marketing.md
Sales
A proposed workflow for sales. Revised 17 September 2026. The roles below are design options, not claims that these agents are deployed or that multiple agents are necessary.
Supply chain and operations
A proposed workflow for supply chain and operations. Revised 17 September 2026. The roles below are design options, not claims that these agents are deployed or that multiple agents are necessary.