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.
Design SaaS invitations with clear states, expiration rules, safe resending, and consistent handling of duplicate emails, existing accounts, and permission changes.
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Define what information each agent needs to resolve a case, and how to limit, retrieve, and log access without replicating unnecessary data.
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Learn how to deploy schema changes while application versions coexist, using validation and gradual removal to reduce disruption and risk.
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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.
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A favorable primary metric does not always justify a launch. Learn how to weigh secondary signals, set guardrails, and choose the right next step.
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Design a clear settings hierarchy so each organization inherits what it needs, allows justified exceptions, and can always understand which value is currently active.
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A secure transfer separates organizational ownership from individual permissions, verifies the incoming administrator, and plans for disputes, mistakes, and orphaned accounts.
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Define where promotions are managed, how discounts combine, and what to validate before publishing to reduce discrepancies between sales channels.
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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.
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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.
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Compare synthetic data, anonymized data, and controlled copies to choose representative test data, limit information exposure, and define practical safeguards for each environment.
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Design fallback rules that distinguish temporary from permanent errors, respect preferences and permissions, and prevent duplicate messages when switching channels.
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