Case Study · Engineering Managers
How an EM Cut PR Review Latency and Raised On‑Time Delivery
An operating system for 1:1s, PR reviews, incidents, and focused delivery—without sacrificing team health.
Executive summary
An EM managing an 8‑engineer team needed to improve PR throughput and sprint predictability. Cortexta centralized review windows, protected maker time for architecture work, and automated incident follow‑ups via RAG. The result: faster reviews, more on‑time delivery, and fewer after‑hours scrambles.
- PR latency: -41% median time to first review.
- On‑time delivery: +19 points in sprint predictability.
- After‑hours reviews: -58% thanks to daytime review windows.
- Incident hygiene: Postmortem closure within 7 days rose to 91%.
From ad‑hoc reviews to predictable delivery
Before Cortexta
- Drive‑by PRs during any open slot; uneven review coverage.
- After‑hours reviews common near sprint end.
- Incidents created tasks, but follow‑ups slipped.
- Architecture work lost to meetings and interrupts.
After Cortexta
- Two daily review windows; urgent PRs preempt Tier‑3 only.
- Maker blocks protected; reviews pulled into windows.
- RAG extracts postmortem tasks and schedules closure work.
- Clear buffers and do‑not‑disturb around deep work.
Implementation blueprint (week 0 → week 2)
1) Connect & ingest
- Connected GitHub for PRs; Linear for issues; Calendar for events.
- Imported last 4 weeks of incidents and retros into RAG.
- Defined team members’ working hours and on‑call schedule.
2) Cadences & SLAs
- Review windows: 10:30–11:00 and 3:30–4:00 daily.
- SLA: first review within 2 business hours for active PRs.
- Incident postmortem closure target: 7 days.
3) Focus & interrupts
- Maker blocks: 2× 90m weekly for architecture/strategy.
- Do‑not‑disturb during deep work; buffers of 10–15m around meetings.
- Urgent PRs only preempt Tier‑3 tasks, not maker blocks.
4) AI Prioritization Engine
Weights aligned to team outcomes:
- Review SLA (30%): PRs nearing SLA breach bubble up.
- Delivery deadlines (25%): sprint commitments prioritized.
- Blocker severity (20%): issues blocking others elevated.
- Team health (15%): 1:1s and feedback rituals preserved.
- Recovery cost (10%): limit context switching/preemption.
5) Living schedule
- PRs pulled into windows; overflow queued to next window.
- Incidents spawn postmortem tasks scheduled within 7 days.
- Maker blocks auto‑rescheduled if unavoidable conflicts arise.
Quantified outcomes (week 2 → week 8)
Minutes to first review
Committed points delivered
Reviews outside 9–6
Closed within 7 days
Daily rituals that made it stick
Standup prep (5 minutes)
- “Now” shows top blockers/PRs; confirm review windows.
- Lock one 45–60m deep‑work slot for the day.
Review windows (2 × 30 minutes)
- Batch PRs; address SLA‑at‑risk first; avoid ad‑hoc reviews.
EOD closure (6 minutes)
- Mark completions; queue tomorrow’s priorities; capture postmortem tasks.
Exact configuration used
Scheduling rules
- Review windows 10:30–11:00, 3:30–4:00; urgent PRs may preempt Tier‑3.
- Maker blocks 2× 90m weekly; 10–15m buffers around meetings.
- On‑call drills reserve 30–45m weekly for readiness.
Prioritization weights
- Review SLA 0.30 · Delivery deadline 0.25 · Blocker severity 0.20 · Team health 0.15 · Recovery cost 0.10
- Large design reviews scheduled in maker blocks only.
- Retro actions time‑boxed within 7 days.
Time allocation (weekly)
A week at a glance
Milestones achieved
Week 1: Windows and SLAs live
Review windows configured; RAG seeded with incidents/retros.
Week 2: Latency falling
Median PR wait down 25%; fewer after‑hours reviews.
Week 4: Predictability up
On‑time delivery +12 pts; review queues stable.
Week 8: Hygiene and health
91% postmortems closed ≤7 days; team after‑hours down significantly.
“Centralizing reviews into windows changed everything. We ship more on time, and I finally have real maker time.”
— Engineering Manager, B2B SaaS
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