Ideas and updates
Research
Practical perspectives from our engineering, product, cloud, data, and AI teams.
Why product analytics fail without clear jobs-to-be-done
The difference between collecting data and using data to improve decisions.
Read insight →Research · Sep 2026Cloud migration without business disruption
A staged approach to moving platforms and data to the cloud without creating operational risk.
Read insight →Research · Aug 2026Data architecture for growing product teams
A practical pattern for organizing product, operational, and analytical data without creating a maintenance burden.
Read insight →Research · Aug 2026Security for data-heavy digital products
The minimum controls teams need as they collect more customer, operational, and business data.
Read insight →Research · Aug 2026Performance budgets that keep websites converting
How to set and enforce speed targets that improve experience and reduce abandonment.
Read insight →Research · Jul 2026How to structure a modern web platform for growth
The composition of a durable website or SaaS platform that can evolve without becoming fragile.
Read insight →Research · Jul 2026Designing discovery that creates better product decisions
Practical research methods to reduce decision churn and keep scope grounded in actual needs.
Read insight →Research · Jul 2026The product owner checklist for AI rollout
The decisions that should exist before an AI feature reaches a public or internal launch decision.
Read insight →Research · Jun 2026Building a measurable AI evaluation harness
A disciplined evaluation model that separates model quality from hype and keeps product decisions evidence-based.
Read insight →Research · Jun 2026From AI prototype to dependable production system
A practical framework for evaluating data readiness, governance, architecture, and operational ownership before scaling AI.
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