Curriculum

Deploying AI Products in Enterprises

Enterprise and deployment is 79 percent (70 companies), enterprise AI agents is the top product surface, and the report calls this the largest single mismatch between JDs and courses: the field teaches greenfield capstones while the hiring

1. 10.01

   Brownfield first

   Your enterprise agent has to read and write the customer's existing system of record, and that integration, not the model, is what makes or breaks the deployment.
2. 10.02

   Support handoff flow

   Scope the integration from the API reference, then place the agent inside ServiceNow, Zendesk, or Teams, carry a trace id through the ticket, and define the handoff, resolution, and escalation thresholds that keep automation safe.
3. 10.03

   Auth and access

   Build the admin console a security team actually evaluates: single sign-on, automated provisioning, roles, and an audit log that records the agent's own actions.
4. 10.04

   The permission-aware retrieval layer

   Design a retrieval layer that filters by who is asking so the agent cannot surface a document the user could never open, and price the re-index a permission change forces.
5. 10.05

   From pilot to production

   Turn a one-queue support-agent pilot into a production rollout with staged exposure, a real reliability floor, and a written rollback plan, and run the forward-deployed motion where the PM embeds at the customer to stand the agent up.
6. 10.06

   Procurement

   Answer the security questionnaire, clear the regulatory tier, and use cloud marketplaces to compress an enterprise deal that would otherwise take the better part of a year.
7. 10.07

   After the signature

   You turn a landed account into org-wide adoption, then defend the renewal with time to value, expansion, and retention evidence rather than a demo.
8. 10.08

   Hosted

   Choose between hosted, VPC, on-prem and air-gapped deployment, decide when a Small Language Model, a frontier Open Weight Model, or a hybrid route fits the customer's boundary, and price the GPU hours and telemetry each choice costs you.
9. 10.09

   Who owns the output

   You take a defensible position on who owns model output, and ship the provenance, filtering, and opt-out features that back it.
10. 10.10

    INTEGRATION CASE

    Spot contradictions across security, legal, and IT answers before a reviewer finds a claim your product cannot verify.