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    Enterprise Agent Portfolio Architect

    1

    Design a governed AI agent portfolio around business workflows, shared capabilities, human authority, least-privilege access and measurable economics.

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    Enterprise Agent Portfolio Architect

    Enterprise Agent Portfolio Architect

    Example session with this skill installed

    Illustrative scenario: A company wants AI help with internal support. Supplied workflow: employees submit questions; support staff search approved articles, draft answers and send them. No ticket connector or performance baseline is available. Design a minimal pilot portfolio; humans must approve all outgoing answers.

    • Read your context and instructions
    • Compiled the enterprise agent portfolio

    Outcome: Test whether source-grounded drafting helps support staff answer routine questions while retaining human approval. No efficiency target is asserted without baseline data.

    Minimal portfolio: One support-drafting assistant, owned by the support lead. Shared capability: approved-knowledge retrieval with source and version references. Avoid separate agents for every article category until workflow evidence justifies them.

    Task allocation: Human staff receive and classify requests. Assistant drafts from supplied approved articles, identifies gaps and proposes escalation. Human staff verify sources and approve or revise every answer, then send through existing tools.

    Access boundary: Read only authorized articles and necessary sanitized request text. No employee-record access, outbound messaging, account changes or ticket writes. Unknown or conflicting policy goes to the human owner.

    Quality controls: Check source support, scope, completeness, privacy and clarity. Track unsupported-claim rate, corrections, reviewer effort and successful resolution using real pilot records.

    Deployment waves: First build a manual evaluation set from authorized examples. Next conduct a limited assisted-drafting pilot. Expand only after quality and cost evidence, owner review and explicit access approval.

    Economics: Record model/tool cost, reviewer time, setup, maintenance and failure handling. Baseline handling time and quality are unknown; ROI cannot yet be calculated.

    Stop conditions: Repeated unsupported answers, privacy leakage or unavailable approved sources require pausing the pilot and review.

    Status: Proposed architecture only. No agent deployed, connector configured or monitoring activated.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Enterprise Agent Portfolio Architect helps leaders and enterprise architects plan a coherent AI workforce from business outcomes and actual work. It inventories tasks and decisions, assesses AI suitability, identifies agent roles and reusable capabilities, and defines where humans remain accountable.

    The skill structures collaboration, knowledge and tool access, authorization boundaries, quality monitoring, ownership, deployment waves and portfolio measurement. Economics include model, integration, review, support and failure costs rather than unsupported savings claims. Agent count is not treated as success.

    Use in ChatGPT, Claude or host-neutral workflows with supplied enterprise context. The output is an architecture and governance plan; deployment, integrations and continuous operation require real authorized infrastructure. It does not guarantee ROI, security, compliance or transformation.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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