Process-to-Assistant Brief Loop

By Juan Beltrán — personal website on AI and digital growth for complex B2B industries.

How do we turn this process into a realistic AI assistant brief? Use this when someone says 'AI should automate this' and you need a grounded assistant brief that states scope, inputs, outputs, risks, and human review. Process-to-Assistant Brief Loop Task: How do we turn this process into a realistic AI assistant brief? Context: [Paste your notes, excerpts, draft, meeting transcript, CRM fields, proposal text, public research, or examples here.] Context I should provide: - Workflow notes - Current documents - User roles - Decisions made - Data sensitivity - Exceptions - Desired business outcome Useful setup: Paste workflow notes, current documents, user roles, decisions made in the process, data sensitivity, exceptions, and desired business outcome. Why this matters: Use this when someone says 'AI should automate this' and you need a grounded assistant brief that states scope, inputs, outputs, risks, and human review. Business problem: Teams say 'AI should automate this' before defining the task, safe inputs, desired output, exceptions, and human review. Instructions: Act as an AI assistant product brief writer. Turn the workflow notes below into a realistic assistant brief. Define task scope, users, inputs, outputs, boundaries, human review, escalation rules, and a first practical test. Workflow: 1. Define the assistant job: Name the specific task the assistant should help with, not the whole process. 2. Map inputs and outputs: List the context users provide and the artifact the assistant returns. 3. Set boundaries: Define what the assistant must not decide, access, store, or claim. 4. Add human review: Specify who reviews the output, when escalation is required, and what cannot be automated. 5. Design the first test: Create a small test using representative examples and clear success criteria. Quality bar: - Use only the context in this chat. - If important information is missing, ask for the minimum missing context before giving a final recommendation. - Separate facts from assumptions. - Do not invent customer facts, benchmarks, financial numbers, policy approvals, or system access. - Keep the answer useful for AI Product Owner. Output: An assistant brief with task scope, input checklist, output spec, guardrails, escalation rules, and first test. - BLUF recommendation or draft. - Evidence from my context. - Assumptions and missing information. - Risks, objections, or failure modes. - Recommended next action, owner, and stop condition. Evidence checklist: - Task - User - Input - Output - Sensitive data - Guardrail - Human review - First test Stopping condition: Stop when the assistant brief is narrow enough to test with examples this week.

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