Insights on cloud infrastructure, AI/ML strategy, engineering leadership, and scaling technology organizations.
Most companies collect huge amounts of data but fail to extract value. Here are five high-impact AI opportunities hiding in plain sight—and how to capture them.
Read ArticleMoving to the cloud is easy. Maturing in the cloud is hard. This framework helps organizations assess where they are and map a realistic path forward.
Read More →Most FinOps advice focuses on tactics. But sustainable cloud cost optimization requires understanding three fundamental levers: visibility, accountability, and architecture.
Coming Soon →Scaling an engineering team is not a hiring challenge—it's an organizational design challenge. When teams stretch across time zones and cultures, clarity and structure become the difference between predictable delivery and constant friction.
Read More →The shift from centralized data warehouses to decentralized data platforms isn't just technical—it's organizational. Here's how to navigate that transition successfully.
Coming Soon →Training a model is 10% of the work. Deploying it, monitoring it, maintaining it, and ensuring it delivers business value is the other 90%. Lessons from building production ML systems that actually worked.
Coming Soon →You don't need to move to Toronto or San Francisco to build a world-class tech career. Here's how to leverage Saskatchewan's unique advantages while building skills that compete globally.
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