Living Portfolio

What we're building right now.

Thanks for reading. Here's what we're building right now — AI systems that put the book's ideas into practice. This page is updated regularly.

AllAI AgentsAnalyticsCreativeResearch
AI Agents

AI Strategist

An AI agent grounded in the book's frameworks that lets readers explore and apply the ideas.

Problem

Books are static. Readers have follow-up questions, want to apply concepts to their own business, or need to revisit ideas in context. Traditional book websites don't offer this.

What AI Does

An LLM agent trained on the full manuscript with chapter-specific context packages, behavioral rules, and conversation design.

Key Takeaway

The quality of the conversation depends more on the system prompt architecture and context design than the base model. Chapter-level framing dramatically improves relevance.

AI AgentLLMEducation

Book connection: Chapter on AI as amplifier — the companion itself is a demonstration of AI extending human-created intellectual work.

Analytics

Automated ROAS Bridge Analysis

Decomposes performance changes into CPC, CVR, and AOV contributions automatically.

Problem

When ROAS changes, marketers often guess at the cause. Was it a traffic quality issue (CPC)? A conversion rate problem? Or a shift in average order value?

What AI Does

Automated decomposition engine that pulls performance data and attributes ROAS changes to their component drivers with statistical significance checks.

Key Takeaway

Decomposition analysis is far more actionable than headline ROAS tracking. Teams that use this framework make better allocation decisions.

AnalyticsAutomationGoogle Ads

Book connection: Chapter on measurement and incrementality — understanding what's actually driving outcomes.

Creative

Creative Intelligence System

AI-powered analysis of ad creative performance with winner/loser breakdowns and recommendations.

Problem

Creative analysis is usually manual, subjective, and inconsistent. Teams need data-driven insights about what's working and why.

What AI Does

Computer vision models analyze ad creative assets. LLM generates performance narratives, identifies patterns, and recommends next tests.

Key Takeaway

Hook rates and early-funnel engagement metrics are better predictors of creative longevity than conversion rates alone.

Computer VisionMeta AdsCreative

Book connection: Chapter on AI-driven creative — how AI can enhance the creative process without replacing human judgment.

AI Agents

Search Term Mining Agent

An AI agent that continuously identifies wasted spend and new keyword opportunities from search term data.

Problem

Search term reports are massive and tedious to review. High-waste terms slip through for weeks before anyone notices.

What AI Does

Agent reviews search term data daily, flags wasted spend, recommends negatives, and identifies high-potential new keywords.

Key Takeaway

Automated monitoring catches waste 10x faster than weekly manual reviews. The key is setting intelligent thresholds, not just flagging everything.

AI AgentGoogle AdsAutomation

Book connection: The broken playbook chapter — optimization shortcuts that used to be manual advantages are now table stakes.

Research

Competitive Intelligence Dashboard

Automated monitoring of competitor activity, industry trends, and market shifts across channels.

Problem

Competitive intelligence is usually ad-hoc and reactive. Teams need systematic awareness of what's changing in their market.

What AI Does

Web scraping and LLM-powered analysis of competitor ad creative, landing pages, messaging shifts, and market positioning.

Key Takeaway

Systematic monitoring reveals patterns that spot checks miss. Competitor creative changes often signal strategic shifts weeks before performance data shows impact.

Competitive IntelResearchAutomation

Book connection: Mental availability chapter — understanding how competitors are building (or failing to build) memory structures.

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