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From vpe-advisor
VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and production discipline (on-call, deployment cadence, postmortem culture). Use when sprint velocity is dropping, eng hiring is broken, team structure is unclear, or deciding when to add a tech-lead manager. NOT a CTO skill (which owns architecture) — VPE owns delivery operations and how the team ships.
npx claudepluginhub ciciliaeth/claude-skills --plugin vpe-advisorHow this skill is triggered — by the user, by Claude, or both
Slash command
/vpe-advisor:vpe-advisorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Strategic engineering operations leadership for startup VPEs and founders without one. **Four decisions, no generic engineering survey:**
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Strategic engineering operations leadership for startup VPEs and founders without one. Four decisions, no generic engineering survey:
This skill is NOT a CTO skill. CTO owns what to build (architecture, scaling cliffs, build-vs-buy). VPE owns how to ship it reliably (delivery, hiring, team structure, production operations). At early stage these are often the same person; at scale they're distinct roles.
This skill is NOT a cs-engineering-lead replacement. Engineering-lead owns day-to-day incident and on-call coordination. VPE owns the operating model that engineering-lead executes.
VPE, VP of Engineering, VP Engineering, engineering operations, delivery throughput, DORA, deployment frequency, lead time for changes, mean time to recovery, MTTR, change failure rate, cycle time, lead time, throughput, engineering hiring, eng hiring funnel, technical interview, take-home, pair programming, hiring pipeline, time-to-fill, cost-per-hire, ramp time, engineering team structure, squad, tribe, chapter, Spotify model, conway's law, tech lead, engineering manager, EM, span of control, hiring funnel conversion, eng comp, leveling, IC track, manager track, deployment cadence, on-call rotation, postmortem culture, blameless retro
# Decision A: DORA 4 metrics + bottleneck identification
python scripts/delivery_throughput_analyzer.py # embedded sprint sample
python scripts/delivery_throughput_analyzer.py path/to/sprint_metrics.json
# Decision B: Hiring funnel health + pipeline gap
python scripts/eng_hiring_funnel_calculator.py # embedded 3-quarter sample
python scripts/eng_hiring_funnel_calculator.py path/to/funnel.json
# Decision C: Team structure recommendation + manager-trigger
python scripts/eng_team_structure_designer.py # embedded 25-engineer sample
python scripts/eng_team_structure_designer.py path/to/team.json
The framework: Google DORA's 4 key metrics (from "Accelerate", Forsgren/Humble/Kim 2018).
| Metric | What it measures | Elite | High | Medium | Low |
|---|---|---|---|---|---|
| Deployment Frequency | How often code reaches prod | Multiple/day | Daily-weekly | Weekly-monthly | < monthly |
| Lead Time for Changes | Commit → production | < 1 hour | 1 day-1 week | 1 week-1 month | > 1 month |
| Mean Time to Recovery (MTTR) | Incident detection → resolved | < 1 hour | < 1 day | 1-7 days | > 7 days |
| Change Failure Rate | % of deploys causing incidents | 0-15% | 16-30% | 16-45% | 46-60% |
Bottleneck identification — where does work wait?
Cycle time = (PR creation → first review) + (review → approval) + (approval → merge) + (merge → deploy). The longest segment is the bottleneck.
Common bottlenecks:
Run delivery_throughput_analyzer.py with sprint data to get DORA verdict + top bottleneck.
See references/delivery_throughput.md for the full DORA framework, anti-patterns, and what to fix first.
The trap: "We can't find good engineers."
The reality: the funnel has 4-6 stages, each with a conversion rate. Find which stage is leakiest; fix that one. "Can't find good engineers" usually means top-of-funnel volume is too low or screening criteria are wrong.
Standard funnel stages:
| Stage | Healthy conversion | What it measures |
|---|---|---|
| Applied → Sourcer screen | 30-50% | Resume quality |
| Sourcer → Recruiter screen | 50-70% | Basic fit |
| Recruiter → Hiring manager | 60-80% | Team fit |
| Hiring manager → Technical interview | 70-85% | Technical baseline |
| Technical → Onsite (full loop) | 30-50% | Technical depth |
| Onsite → Offer | 25-40% | Final go/no-go |
| Offer → Accept | 70-90% | Comp + close discipline |
Funnel math: to hire N engineers, you need N / (product of all conversion rates) candidates at top of funnel.
Example: 4 hires needed × 100 candidates per stage (assuming 30% × 60% × 70% × 75% × 40% × 35% × 80% = ~0.7% end-to-end) = ~570 candidates at top of funnel.
Run eng_hiring_funnel_calculator.py with funnel data to compute conversion per stage, time-to-fill, and pipeline gap.
See references/engineering_hiring_funnel.md for the full funnel framework, common leakage points, and sourcing channel diversification.
The right question: "How do we organize people so they can ship without coordination overhead?"
Three-axis model (adapted from Spotify, refined by reality):
When to evolve:
| Stage | Structure |
|---|---|
| 1-5 engineers | One team. No structure. |
| 6-15 engineers | 2-3 informal pods around major work streams. Founder-CTO can still know everyone. |
| 16-40 engineers | 4-6 squads. First eng manager hires. Chapter structure emerges for cross-squad skill alignment. |
| 41-100 engineers | 2-3 tribes (clusters of squads). Director of engineering layer. Chapters are formal. |
| 100+ engineers | Multiple tribes + group EM/director per tribe. VPE + director(s) + EMs + tech leads. |
Manager-trigger thresholds:
Run eng_team_structure_designer.py with team profile for structure recommendation + manager-trigger.
See references/eng_team_structure.md for the full framework, Conway's Law implications, and EM-vs-tech-lead split.
Production discipline is the operating model that lets the team sleep. Four pillars:
engineering/slo-architect/)See references/production_discipline.md for the full operating model.
Goal: Diagnose throughput + identify top bottleneck.
# 1. Pull sprint metrics: deployment frequency, lead time, MTTR, change failure rate
python ../../skills/vpe-advisor/scripts/delivery_throughput_analyzer.py sprint_metrics.json
# 2. Review DORA verdict per metric
# 3. Identify top bottleneck (longest wait stage)
# 4. Cross-check with cs-cto-advisor on architectural causes
# 5. Output: 90-day fix plan with one bottleneck owned by one engineer
# 6. Log via /cs:decide
Goal: Identify funnel leakage + compute pipeline gap for hiring target.
# 1. Pull funnel data from ATS for last 90 days
python ../../skills/vpe-advisor/scripts/eng_hiring_funnel_calculator.py funnel.json
# 2. Identify weakest conversion stage
# 3. Compute pipeline volume needed for next quarter's hiring target
# 4. Cross-check with cs-chro-advisor on comp/leveling competitiveness
# 5. Cross-check with cs-cfo-advisor on cost-per-hire envelope
# 6. Output: top-3 fixes + sourcing channel diversification plan
Goal: Confirm team structure matches headcount + work streams.
# 1. Build team.json: headcount, work streams, manager count, IC distribution
python ../../skills/vpe-advisor/scripts/eng_team_structure_designer.py team.json
# 2. Check manager-trigger thresholds (5-7 IC rule)
# 3. Identify squad sizes outside 5-9 range
# 4. Cross-check with cs-cto-advisor on Conway's Law alignment
# 5. Output: structure recommendations + manager hire plan
Goal: Confirm operating model can scale through current growth.
engineering/slo-architect/)**Bottom Line:** [one sentence — decision and rationale]
**The Decision:** [one of: throughput | hiring | structure | production]
**The Evidence:** [numbers from the tool, not adjectives]
**How to Act:** [3 concrete next steps]
**Your Decision:** [the call only the founder/CTO can make]
../cto-advisor/ — Architecture, scaling cliffs, tech debt strategy (CTO decides what to build; VPE decides how to ship)../chro-advisor/ — Hiring systems (ladders, bands, leveling rubrics company-wide); VPE owns eng-specific funnel execution../coo-advisor/ — Operating cadence company-wide; VPE owns eng-specific cadence../../../engineering/slo-architect/ — SLO design (tactical; VPE owns the policy that SLOs are required)../../../engineering/chaos-engineering/ — Chaos experiment design (tactical resilience)../../../engineering/feature-flags-architect/ — Progressive delivery (tactical deployment)../../../engineering/kubernetes-operator/ — K8s operator pattern (tactical infra)cs-engineering-lead agent — Day-to-day incident + on-call coordination (VPE owns the operating model that engineering-lead executes)Version: 1.0.0 Status: Production Ready