Software and SaaS development
Digital products that solve, scale and evolve.
Insights
Guides, analysis and lessons on product, artificial intelligence, growth, communications and cloud.
Editorial themes
Digital products that solve, scale and evolve.
AI systems for real-world processes.
Demand, catalogue, partners and conversion.
Every conversation in the right channel.
Available, observable and ready services.
An integrable API helps an external team move from access to a valid operation with fewer questions. Learn how to design, test, and measure that journey.
↗
Choosing between users and accounts changes how you interpret activity, adoption, and friction in B2B SaaS. Learn to define metrics that guide better decisions.
↗
Set cutoffs, tolerances, and owners to find differences between systems before month-end close, resolve them with evidence, and improve the next cycle.
↗
Event sourcing stores changes as events, while a traditional model stores the current state. Compare requirements, costs, and risks before choosing an approach.
↗
A practical framework for deciding which business rules teams can edit, which require approval, and which changes need technology review, testing, and controls.
↗
Define what information each agent needs to resolve a case, and how to limit, retrieve, and log access without replicating unnecessary data.
↗
Design a clear settings hierarchy so each organization inherits what it needs, allows justified exceptions, and can always understand which value is currently active.
↗
A secure transfer separates organizational ownership from individual permissions, verifies the incoming administrator, and plans for disputes, mistakes, and orphaned accounts.
↗
Learn how to trace a metric from a report back to its sources, rules, and owners, and diagnose why two systems may show different figures.
↗
Learn how to decide when a feature flag is ready to retire, check its dependencies, remove alternative code paths, and validate the change without losing control of your product.
↗
Compare synthetic data, anonymized data, and controlled copies to choose representative test data, limit information exposure, and define practical safeguards for each environment.
↗
Design fallback rules that distinguish temporary from permanent errors, respect preferences and permissions, and prevent duplicate messages when switching channels.
↗