C-Level Advisory Pre-mortemAnalysisChallenge

Executive Mentor — Challenge

Pre-mortem plan analysis to find weaknesses before they find you.

$skillfish add ~skills/executive-mentor-challenge

Real Conversations

See how the Executive Mentor — Challenge skill responds to actual requests. These are representative examples of what your AI agent will produce.

You

I'm about to present a plan to the board: $2.1M ARR today, target $6M ARR in 18 months — a 3x from here. The plan requires: doubling the sales team (3→6 AEs), $400K marketing investment, and launching a new enterprise tier. Find the holes in this plan before I present it.

Agent

I'll pressure-test this the way a skeptical board member will. Here are the five holes.

Hole 1 — The headcount assumption: Doubling AEs from 3→6 assumes new AEs ramp in 90 days and hit full quota in 6 months. Industry data says SaaS AE ramp is 9–12 months. If you hire in month 2, you get 6–9 months of productive quota from them. On a 3x growth plan, timing of ramp matters enormously. Have you modeled monthly ARR contribution from each AE with realistic ramp, or just used annualized quota?

Hole 2 — The marketing ROI assumption: $400K in marketing generating what MQLs? At what close rate? If your current blended CAC is $8K and you're closing 1 deal per $8K, $400K = 50 new customers. If average ACV is $14K, that's $700K ARR from the marketing investment. That gets you to $2.8M, not $6M. Where does the other $3.2M come from?

Hole 3 — The enterprise tier: New pricing tier assumes enterprise customers exist in pipeline, have been validated, and your product is ready. What's the evidence? Have you signed even 2–3 enterprise customers at the proposed price point? Enterprise launches without pipeline validation are commonly 6+ months behind schedule.

Hole 4 — The retention assumption: To go from $2.1M to $6M in 18 months, you need net new ARR AND low churn. What NRR assumption is baked in? At 85% NRR, you're fighting an erosion that requires $3.15M in gross new ARR just to net $2M. At 110% NRR, your expansion revenue is a tailwind. Your plan needs an explicit NRR assumption.

Hole 5 — Dependencies between workstreams: Enterprise tier requires product work, which requires engineering, which is competing with your current roadmap. Marketing investment requires pipeline management capacity, which requires AEs to be ramped, which takes time. Have you mapped the critical path and identified where a single delay creates a cascade?

Get Started

How to install and use this skill in your preferred environment.

Skills are designed for AI coding agents (Claude Code, Cursor, Windsurf) and IDE-based workflows where the agent can read files, run scripts, and act on your codebase. Web-based AI can use the knowledge and frameworks, but won't have tool access.

Models & Context

Which AI models and context windows work best with this skill.

Recommended Models

Best
Claude Opus 4 Claude Sonnet 4 GPT-4.1 Gemini 2.5 Pro Grok 3 Kimi K2
Good
Claude Haiku 4.5 GPT-4.1 mini Gemini 2.5 Flash Grok 3 mini

Larger models produce more detailed, production-ready outputs.

Context Window

This skill's SKILL.md is typically 3–10 KB — fits in any modern context window.

8K Skill only
32K+ Skill + conversation
100K+ Skill + references + codebase

All current frontier models (Claude, GPT, Gemini) support 100K+ context. Use the full window for complex multi-service work.

Pro tips for best results

1

Be specific

Include numbers — users, budget, RPS — so the skill can size the architecture.

2

Share constraints

Compliance needs, team size, and existing stack all improve the output.

3

Iterate

Start with a high-level design, then ask follow-ups for IaC, cost analysis, or security review.

4

Combine skills

Pair with companion skills below for end-to-end coverage.

Ready to try Executive Mentor — Challenge?

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$skillfish add ~skills/executive-mentor-challenge
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