Wroking with AI/automation managers

 Turning work into structured “footprints” + letting systems track leading indicators and nudge us is where modern knowledge work is headed. Here’s an evidence-backed playbook you can use right away.

What the research says (and what to do)

1. Set clear goals, then let the system track them.
   Specific, challenging goals reliably boost performance (large effects across meta-analyses). Use OKRs for ambition + transparency and translate strategy into a few measurable outcomes. Stanford MedicineReworkHarvard Business Review

2. Record decisions as lightweight Decision Logs (ADRs).
   Capture time, context, options, trade-offs, stakeholders, expected impact. ADRs are a well-accepted practice for scaling alignment and auditability. martinfowler.comAWS Documentation

3. Track a tiny set of leading (predictive) and lagging (outcome) metrics.
   Safety and operations guidance is clear: use leading indicators to drive change; lagging indicators to verify results. Keep it to 3–5 leading metrics on a dashboard. OSHAPMC

4. Use reminders and nudges—without creating notification noise.
   RCTs show that simple message reminders meaningfully improve adherence to intended behaviors; batching notifications a few times per day reduces stress and improves attention. Also, frequent interruptions increase speed and stress. So tie prompts to workflow checkpoints and deliver in batches. JAMA NetworkSquarespaceBren School of ICS

5. Improve via small, trustworthy experiments.
   Follow A/B-testing rules of thumb from the big experiment platforms (design, guardrails, power, SRM checks). Treat each change as a test with a success metric. Cambridge University Press & AssessmentExP Platform

6. Limit Work-in-Progress (WIP) and visualize flow.
   Kanban + WIP limits shorten cycle times and surface bottlenecks; case studies show measurable improvements when teams reduce WIP and shorten cycles. Use Little’s Law to size WIP against throughput. Queen's University BelfastSixSigma.us

7. Schedule 10–15 minutes of daily reflection.
   Lab + field experiments (including a large training program) found that short, structured reflection significantly improves later performance—partly by boosting self-efficacy. Put it on the calendar. Larry Ferlazzo's Websites of the Day...Harvard Business School Library

8. Use AI to shrink “work about work”—but stay on the right side of the frontier.
   Controlled studies show sizable productivity/quality gains from gen-AI on writing and coding; benefits are task-dependent and best with guidance. Feed AI with clean, linked artifacts (tickets, docs, ADRs) and clear permissions. SciencearXivHarvard Business School

Don’t turn datafication into surveillance. Meta-analyses show electronic performance monitoring doesn’t improve performance and does raise stress; if monitoring is required, keep it minimal, transparent, and worker-benefiting. Wiley Online LibraryAmerican Psychological Association

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Your “work-footprint” template (copy/paste into your tool)

• Timestamp: YYYY-MM-DD HH:mm

• Task / Context:

• Decision / Hypothesis (options & trade-offs):

• Stakeholders & contacts: @Name (role)

• Risks / Constraints:

• Action taken:

• Metrics: Leading … / Lagging … (with targets)

• Result / Evidence:

• Links: Ticket / Doc / PR / Meeting notes

• Reflection (<5 lines): what worked, what didn’t, next step

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One-week rollout (individual edition)

• Today: Rewrite one goal as an OKR (1 Objective, 2–3 Key Results) and add the footprint template as a quick-add form in your system. Rework

• This week: Stand up a simple Kanban with WIP limit (e.g., “In Progress ≤ 3”); pick 3 leading indicators for your personal dashboard. Queen's University BelfastOSHA

• Daily: Batch notifications into two windows; schedule a 10-minute reflection at day’s end. SquarespaceHarvard Business School Library

• This month: Run one small experiment (e.g., new handoff checklist): define success metric → A/B (or pre/post) → keep the winner. ExP Platform