How to Get Your AI Coding Assistant to Catch Its Own Mistakes Before You Do
The AI that wrote your draft is the worst reviewer of it. Here's the independent-review technique that catches what a second read-through misses.
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Free Learning · Better Decisions Make Growth Decisions
Make Growth Decisions
You Can Defend
Know what to test, when to trust the result, and what to do next. Practical guides for analysts, growth teams, and founders.
Behavioral Economics Examples That Explain Your Bad Decisions
Behavioral economics examples reveal why even Microsoft's experiments succeed only a third of the time. Learn what actually works and why.
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How the Behavioral Economy Quietly Shapes Your Choices
Every product is already a behavioral intervention. Learn why most fail, and how founders can govern behavioral economics before it governs users.
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What the Behavioral Economics Definition Really Means for You
Behavioral economics definition explained: why it's not just bias lists, and how to test if it actually works on your own users.
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How Loss Aversion Quietly Shapes Your Decisions
Loss aversion makes losses feel 2x stronger than gains—and it's secretly shaping how leaders judge experiments, hire talent, and kill good programs.
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The Action-Velocity Signal: Why Raw Token Counts Lie About AI Agent Costs
Token totals and dollar totals are the metrics everyone reaches for first when auditing AI agent spend — and they are frequently the wrong ones. A better diagnostic, and a portfolio-style framework for model selection.
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The Three-Layer Audit: How to Actually Verify an AI Coding Agent Before You Trust It
Most people accept an AI agent’s first answer. A three-layer audit — primary-source check, realistic-input test, goal re-derivation — catches what pattern-matching misses.
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The Habits That Actually Make Claude Code Reliable
Most Claude Code advice focuses on the prompt. The habits that actually determine reliable output are upstream of that — and they're the same ones Anthropic's own documentation recommends and the tool's creator uses daily. Here's where those two sources agree, why it works mechanically, and what to actually do about it.
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The New Claude Code Features Most People Are Still Ignoring
Most Claude Code advice — including Anthropic's own conference talks — describes a tool that no longer exists. Six changes actually change how you should work: rewind, auto mode, background subagents, worktrees, agent teams, and adversarial review.
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Cognitive Bias Examples: A CRO Practitioner's Field Guide
Real cognitive bias examples from 200+ A/B tests: where each one lifts conversion, the lift range, and exactly when it backfires or fails to replicate.
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Foot-in-the-Door Technique: When Micro-Commitments Lift Conversion (and When They Backfire)
How the foot-in-the-door technique lifts signup conversion with micro-commitments, the diagnostic that catches hollow ones, and when it backfires.
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Understand LLMs in Under 15 Minutes
Karpathy's 2023 LLM talk, rebuilt for 2026 — what changed in scaling, tool use, and security, and what founders deploying AI agents need to know.
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How to Run Five-Second Tests on SaaS Landing Pages
A prospect forms their first impressions of your SaaS landing page in about five seconds before deciding whether to keep reading or leave. They will not tell you that your message was unclear. They will simply close the tab, compare you to a competitor, or return to the product they already use.
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How I Test AI Landing Page Copy Without Brand Drift
Modern AI tools can function as a powerful landing page copy generator, writing 20 variants before your next meeting. That does not mean any of them should reach production.
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Mediation Analysis for A/B Tests With a Causal Story
You ran the test. Conversion moved. Now someone asks the question that matters: why?
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How I Reconcile CRM Revenue and Test Data
A test can win and still lose money. I have seen that happen enough times that I do not trust lift charts by themselves anymore.
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Minimum Detectable Effect (MDE): How to Choose the Right One
Minimum detectable effect (MDE) is the most important input to A/B test design. Learn how to calculate and choose the right MDE for business impact and traffic.
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A/B Test Sample Size & MDE Calculator Guide
An A/B test sample size calculator gives one number. Here is the whole table: visitors per variant by baseline and MDE, plus the mistake that halves power.
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How to Fund Experimentation on Evidence, Not Arguments
One honest experiment result can get a growth program funded or gutted. The fix isn't better reporting — it's pre-registration, borrowed from clinical trials.
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How I Detect Carryover Effects in Repeat Visitor Tests
Repeat visitor tests can lie with a straight face. The dashboard says variant B won, but what it may have found is memory, not lift.
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Why a Model Router Won't Save Your AI Coding Budget (And What Actually Does)
The dream of a 'master orchestrator' that auto-picks the cheapest model that can do each coding task is a research spiral, not a shortcut.
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Claude Code vs Codex vs Cursor: A Task-by-Task Buyer's Guide (2026)
There's no single best AI coding tool — the largest study of real merged pull requests found no universal winner.
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How to Near-One-Shot a Feature
One-shotting a feature with AI isn't luck — it's a method. The goal isn't the prettiest first draft; it's the fewest total tokens to a change that compiles…
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Experimentation Maturity for B2B SaaS Teams
If every test feels urgent, you do not have a broken experimentation strategy. You have a decision quality problem. Most B2B SaaS teams are not short on
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