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Career Readiness Studioby LER.me

AI at work · Case analysis · 50 min

What goes in the tool, and who gets told

The two questions that get entry-level workers in trouble: what data was I allowed to paste, and did I say a tool was involved.

Target level: Proficient Has functional knowledge of the skill and can apply it properly in specific on-the-job settings.

Why this design

Work a real situation from evidence to recommendation, and show the reasoning. Judgment content — root cause, tradeoffs, competing priorities, risk.

What this evidences

  • data-privacy-judgment×1 at Proficient
  • ai-ethics-disclosure×0.6 at Proficient

By the end, the learner can

  • Access control change validation: uses AI tooling to cross-reference proposed individual access-status modifications against role-based policy rules, catching errors before committing changes to security files.
  • Encryption and firewall configuration review: prompts an AI assistant to audit current firewall rule sets and data-in-transit encryption configurations for misalignments with policy, then adjudicates each finding through hands-on system inspection.
  • Automated network audit pipeline: orchestrates AI tools to scan running configurations against compliance benchmarks (CIS, NIST), triage flagged deviations by risk severity, and produce remediation tickets, reviewing every high-severity finding personally.

Session plan

  1. 15 minThe caseWhere this shows up: technology teams and corporate it environments, working with managers, technical teams, users. Conditions to expect: analytical, system-dependent, problem-solving intensive. Entry roles this maps to: Computer Systems Analysts, Computer Systems Engineers/Architects, Computer User Support Specialists.
    • evaluates AI-generated choropleth or heat-map outputs against domain knowledge of local land use and demographics, overriding or correcting automated classifications that misrepresent on-the-ground conditions.
    From Geographic Information Systems Technologists and Technicians (15-1299.02)
  2. 15 minEvidence logWork the task on your own first. Support is available, but ask for it out loud so the group hears what got you stuck.
    • Tools in play: Development environment software, Web platform development software, Data base user interface and query software.
  3. 10 minCompare readingsCompare answers before the debrief. Where the room split is the useful part — the split usually marks a real judgment call rather than a knowledge gap.
    • Where did two people read the same situation differently, and what did each notice?
    • Which answer would survive a supervisor asking "why did you do it that way?"
  4. 10 minWhat the record showedClose the loop: what changed between the first attempt and the last, and what would have to be true for data & privacy judgment to hold up on a bad day.

Assessment (17 items)

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