# Worked Example: Finding Your AI Contribution

Turn domain experience into a direction and a two-week learning project.

Built Into Work | Vic Akosile | Version 1.0 | October 5, 2026

For: Professionals deciding where to focus their AI learning
Use when: Alongside the AI positioning session
Suggested time: 10 minutes

Use synthetic or authorized information. Keep sensitive work in approved tools. A named person owns each decision. These tools support discussion and planning; they are not validated assessments.

All organizations, workflows, numbers, and results in these examples are fictional and provided for learning. Targets are proposed decision criteria, not validated standards or promised outcomes.

## The person and starting point

Maya is a fictional HR operations specialist. She knows service-desk workflows, has improved escalation guidance, and enjoys helping colleagues use a clear process. She has not yet built an AI product.

## Completed positioning session

Start with evidence of contribution and choose a small way to extend it.

**Experience**
Policy lookup, escalation, and service handoffs; recognizes conflicting versions and incomplete questions.

**Evidence**
Standardized escalation guidance and trained analysts on policy lookup.

**Direction**
Practitioner: improve a daily workflow. Amplifier: teach colleagues to evaluate evidence. Builder is a capability to explore through a bounded prototype, not a new job title.

**Project**
Create ten fictional policy questions, write expected behavior, and evaluate cited drafts in an approved test tool.

**Skill**
Define test cases, inspect source support, recognize exceptions, and explain a failure clearly.

**Review partner**
A willing policy specialist checks expected answers and boundaries; no real personnel data is used.

**Evidence**
Ten annotated cases, one failed case, a revised brief, and a short explanation of human decision rights.

## Completed two-week plan

Days 1-2: choose the workflow and confirm the approved test environment. Days 3-5: create synthetic policies and ten questions. Days 6-8: evaluate drafts and log failures. Days 9-10: improve the brief and discuss evidence with the review partner. Keep the focus on work quality, not the number of prompts used.

## Completed review decision

Suppose Maya finds one draft that invents an eligibility condition. She documents the failure and revises the boundary to escalate individual decisions. Her next decision is whether to deepen evaluation skills, learn bounded building, or focus on enabling the team. The project demonstrates learning; it does not establish production readiness, a promotion, or a career outcome.

## Working record

Owner:
Review date:
Decision:
Evidence still needed:

Original guide: https://builtinto.work/resources/worked-example-career-positioning