📊 Product Management

Linear Regression: Forecasting with a Straight Line

Linear regression forecasts the future by drawing a straight line through past data. It's used to predict outcomes like sales based on ad spend or energy use based on temperature.

Standard Error: Gauging Your Measurement's Precision

Standard error measures the precision of a sample statistic, like the mean. It answers: "If I ran this experiment again, how much would my result change?" It's key for building confidence intervals and A/B testing. Don't confuse it with standard deviation.

DRY: Don't Repeat Yourself

DRY means every piece of knowledge has one single, authoritative representation in your system. This applies to business logic, config, or docs; a change in one place updates everywhere.

Rules of Engagement: API Contracts for Teams

Rules of Engagement (RoE) are an API contract for human teams, defining how they interact to prevent chaos. They clarify who owns a customer conversation or how feature requests are handled.

Market Sizing: TAM, SAM, and SOM for Realistic Planning

Market sizing is a funnel, not a single number. TAM is the total universe of customers, SAM is the segment you can reach, and SOM is who you can realistically win. It's crucial for business plans and investor pitches.

Bayesian Inference: Updating Beliefs with Data

Bayesian inference formalizes learning from experience, updating your belief in a hypothesis as you gather evidence. It's used in A/B testing and medical diagnostics. The footgun is that a poor initial belief (the prior) can skew your conclusions.

The Test Pyramid: Fast Feedback, Stable Code

The Test Pyramid is a strategy for balancing automated tests: write many fast unit tests, fewer integration tests, and very few slow end-to-end tests. It guides CI/CD pipelines to catch failures quickly. The footgun is over-relying on slow E2E tests.

Demand Generation: Creating Your Sales Pipeline

Demand generation creates the market for your product. It's the marriage of marketing programs and a structured sales process, driving awareness for complex B2B or B2G sales.

The Bass Diffusion Model: Innovators vs. Imitators

The Bass Diffusion Model splits product adoption into innovators who buy first and imitators who follow the crowd, creating the classic S-curve of growth. It's used to forecast sales for new products by modeling how word-of-mouth drives adoption.

ANOVA: Comparing Group Averages by Analyzing Spread

ANOVA checks if group averages are different by comparing the spread *between* groups to the spread *within* them. It's used to see if three ad campaigns yield different click-through rates.

Code Smells: Indicators of Deeper Problems, Not Flaws

A code smell is a surface-level hint, like a long method, that suggests a deeper design problem. It's an indicator, not a definitive flaw. The footgun is blindly "fixing" every smell; a smell is a reason to investigate, not an automatic command to refactor.

Product-Led Growth (PLG): When the Product Sells Itself

Product-Led Growth (PLG) makes the product its own salesperson. Instead of a sales team, the product's features and user experience drive acquisition and expansion.

Prophet: Time Series Forecasting for Seasonal Data

Prophet treats a time series as a sum of its parts: a long-term trend, seasonal cycles, and holidays. It's used for business forecasting, like predicting sales, when you have strong seasonal data. The footgun is using it for non-seasonal data.

Statistical Power: Detecting Real Effects in Your Tests

Think of statistical power as your experiment's sensitivity. It's the probability of detecting a real effect, like a true lift in an A/B test. The main footgun is running a low-power test, which will likely miss a real improvement and lead you to discard good.

Strangler Fig Pattern: Replace Legacy Systems Safely

The Strangler Fig pattern lets you replace a legacy system by gradually growing a new one around it, eventually choking out the old code. It's used for modernizing critical systems where a "big bang" rewrite is too risky, routing traffic feature by feature.

Partner Enablement: Getting External Partners to Sell Your Product

Partner enablement removes friction for your external sales channels. It equips resellers and distributors with the training, tools, and content they need to sell your product effectively, especially when they also represent competitors.

Survival Analysis: Predicting When, Not Just If

Survival analysis predicts *when* an event like user churn will happen, not just *if*. It's used to model customer lifetime or hardware failure rates. The key mistake is using simple averages, which are skewed by users who haven't churned yet (censored data).

Bootstrapping: Quantifying Uncertainty with Resampling

Bootstrapping estimates uncertainty by resampling your own data. It's used to find confidence intervals for complex stats like medians where no simple formula exists. The footgun: it can't fix a biased sample, only reveal the uncertainty within it.

Contract Testing: Test Interfaces, Not Integrations

Contract testing ensures services work together without slow integration tests. It's a formal agreement where a 'consumer' defines its needs, and a 'provider' proves it can meet them.