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 how to assess whether you can replace a SaaS solution without losing data or disrupting workflows by reviewing exports, dependencies, exit tests, and responsibilities.
↗
A lightweight decision log preserves the context behind product choices, clarifies the reasoning that supports them, and makes it easier to revisit them when circumstances change.
↗
Decide what to translate, adapt, or share based on clarity, risk, market differences, and maintenance. Use practical fallback criteria and a review workflow.
↗
Compare shared databases, separate schemas, and dedicated databases to choose the data isolation model that fits your SaaS risks, customers, and team.
↗
Plan digital maintenance using impact, communication, rollback, and validation criteria to reduce technical and operational risks.
↗
A spreadsheet can support useful processes for years. This framework helps identify when its flexibility becomes an operational risk.
↗
Define users, cases, exceptions, and dependencies to run a representative, safe digital pilot that can guide the next decision.
↗
A practical framework for distinguishing a product gap from a process, data, permissions, user experience, or adoption issue before prioritizing development.
↗
A shared state model prevents discrepancies between applications, clarifies ownership, and helps detect stalled processes before they affect customers.
↗
A practical framework for assigning autonomy to automations based on impact, reversibility, uncertainty, context, and the ability to correct errors.
↗
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 deciding which data travels in an event, which data is retrieved later, and how to avoid dependencies, stale data, and security risks.
↗