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.
Learn when a backfill is necessary, how to define its scope and choose a method, and how to validate results without duplicating notifications, charges, or changes.
↗
A useful export starts by defining which data leaves the system, who can request it, and how the file is protected. This guide offers practical design criteria.
↗
Decide which features to keep, limit, or stop when a dependency fails. This practical framework helps protect data, inform users, and restore service safely.
↗
Learn how to assess whether you can replace a SaaS solution without losing data or disrupting workflows by reviewing exports, dependencies, exit tests, and responsibilities.
↗
An idempotency key lets you retry sensitive operations without repeating their effects. Learn how to define its scope, handle concurrency, and respond to errors.
↗
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.
↗
Plan digital maintenance using impact, communication, rollback, and validation criteria to reduce technical and operational risks.
↗
A shared state model prevents discrepancies between applications, clarifies ownership, and helps detect stalled processes before they affect customers.
↗
Learn how to prioritize errors in digital processes using operational criteria to block, alert, or correct them without unnecessarily slowing the business.
↗
A practical framework for defining data retention, archiving, anonymization, and deletion without disrupting operations or increasing risk.
↗
A practical framework for deciding which internal processes require an SLA and which need reviewable operational targets, without inflating costs.
↗