Portfolio case study builder
Collect project artifacts, decisions, and measured outcomes into a client-approved story.
What this workflow does
Collect project artifacts, decisions, and measured outcomes into a client-approved story. It produces a source-linked draft, validates it against policy, and keeps publication or system updates behind an explicit approval.
What you gain
Finished work becomes a credible portfolio asset faster.
What the AI agent changes
How this worked before
Templates could merge known fields, but they could not understand source documents or adapt the draft to exceptions.
What the AI agent changes
The agent reads source material, drafts the right version for the case, cites evidence, and leaves the final send or write to a person.
Agent trigger
A project closes and its publication permissions are known.
Inputs
- Process context: brief, project files, decisions, feedback, outcomes, and confidentiality limits
- Approved policies, ownership, and exception rules
Agent flow
- 1
Assemble the current source material, template, and policy version.
- 2
Draft only claims that can be linked to allowed evidence.
- 3
Prepare a factual case-study draft with unsupported claims removed and mark every unresolved exception.
- 4
Publish or write back only the approved version.
Human decisions
After step 3
The accountable process owner approves a factual case-study draft with unsupported claims removed.
Outcome
- Client-approved portfolio case study
- Evidence, exceptions, and audit trail
Guardrails
- Never publish, send, or post without the named approval.
- Keep templates, policies, and source timestamps visible to the reviewer.
Risks and mitigations
Unsupported claims can enter a customer-facing or regulated record.
Attach evidence to material claims and block approval when citations are missing.
Sources and evidence
Sources establish feasibility or impact. Not every metric comes from an identical implementation.
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