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 turn business rules into observable scenarios, cover exceptions, and validate workflows across systems with clear acceptance criteria.
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Compare roles and contextual rules to decide who can do what in a B2B application. Identify signs of complexity and plan a safe evolution.
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Learn to distinguish instants, calendar dates, and local times so you can store, display, and communicate dates consistently across applications and connected systems.
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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.
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Decide what to translate, adapt, or share based on clarity, risk, market differences, and maintenance. Use practical fallback criteria and a review workflow.
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A spreadsheet can support useful processes for years. This framework helps identify when its flexibility becomes an operational risk.
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A practical framework for distinguishing a product gap from a process, data, permissions, user experience, or adoption issue before prioritizing development.
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A practical framework for deciding whether a process change should be addressed with code, manageable configuration, or a new product capability.
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A practical guide to documenting, reviewing, and retiring automations without losing control of data, decisions, permissions, and exceptions.
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Design accessible internal tools for searching, editing, approving, and resolving issues without blocking critical team tasks.
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Design web application load tests with real user journeys, verifiable thresholds, and useful evidence to make decisions before a usage spike.
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Guide to planning, testing, and validating a data migration between systems, with controlled parallel operation and evidence-based rollback.
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