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.
Compare roles and contextual rules to decide who can do what in a B2B application. Identify signs of complexity and plan a safe evolution.
↗
An integration sandbox lets you validate connections without affecting live operations. Learn when to use one, what it should reproduce, and how to manage differences from production.
↗
An idempotency key lets you retry sensitive operations without repeating their effects. Learn how to define its scope, handle concurrency, and respond to errors.
↗
Compare offset and cursor pagination by stability, navigation, data volume, and cost. Choose the contract your API needs and plan a migration without breaking clients.
↗
Compare shared databases, separate schemas, and dedicated databases to choose the data isolation model that fits your SaaS risks, customers, and team.
↗
Learn when a shared inbox no longer works and how to design a work queue with priorities, owners, and traceability that supports daily operations.
↗
A practical framework for choosing, preserving, and reconciling identifiers across CRM, ERP, ecommerce, and custom applications without confusing entities.
↗
Choosing when to reserve inventory prevents overselling and inventory lockups. This framework helps define timing, expiration periods, priorities, and operational controls.
↗
A practical framework for distinguishing a product gap from a process, data, permissions, user experience, or adoption issue before prioritizing development.
↗
Learn to distinguish functional history, audit trails, and operational traceability to record the right events, protect data, and provide useful evidence.
↗
A practical framework for assigning autonomy to automations based on impact, reversibility, uncertainty, context, and the ability to correct errors.
↗
A practical framework for deciding which data travels in an event, which data is retrieved later, and how to avoid dependencies, stale data, and security risks.
↗