The AI Strategist

Quantitative research, practical AI workflows, and live market data for investors, operators, and strategists.

Research
Quantitative analysis, frameworks, and deep dives on competitive strategy, value creation, and AI adoption.
AI Workflows
Step-by-step AI workflows for strategy, diligence, and operating decisions. Each one shows the problem, the output, and the prompt.
Market Comps
Daily-refreshed valuation comps for 100+ public companies across seven sectors. Sortable tables, sector pulses, and revenue forecasts.

Latest

 

Labor Tightness and Operating Margins, Sector by Sector

A descriptive look at how BLS JOLTS labor tightness co-moves with sector-median operating margins from 2022 to 2025. Patterns differ sharply across the seven sectors in our equity panel.

We measure the co-movement between a BLS JOLTS-based labor tightness index and operating margins across seven sectors. Healthcare shows a strongly negative correlation; the other six show positive correlations driven by shared cyclical exposure in this post-COVID window. The piece is descriptive, not causal. The sample is small and statistical inference is not reported.

May 13, 2026
 

B2B Customer Research: A Human-in-the-Loop AI Workflow

Five intervention points where human judgment gates AI output, and why that structure matters for diligence

A structured workflow for using Claude to accelerate B2B customer research in diligence and strategy contexts, with explicit human review gates at each step to prevent compounding errors from unvalidated AI output.

May 7, 2026
 

Map Vendor Concentration, Leverage, and Renewal Risk from a Spreadsheet

Paste a vendor list into Claude and surface the procurement risks that derail integrations

A structured workflow for using Claude to analyze a target company’s vendor list and identify single-source dependencies, unfavorable renewal timing, and supplier leverage risks before close.

May 2, 2026
 

The Pricing Power Map

Which company characteristics predict margin resilience when revenue growth slows? An XGBoost + SHAP analysis of 238 company-year observations.

We isolated the component of operating margin change not explained by revenue dynamics and used SHAP to rank the entry characteristics most associated with margin defense. The lever ranking shifts dramatically by sector.

Apr 7, 2026
 

The Margin Expansion Playbook

What actually predicts operating margin improvement? A machine learning analysis of 140 companies over six years.

We trained an XGBoost model on 355 company-year observations and used SHAP to rank the entry characteristics that most reliably predict forward operating margin improvement. The top levers shift dramatically by sector.

Mar 25, 2026
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