From the course: AI Product Foundations: Planning Strategies for Data Scientists
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Optimizing development workflows
From the course: AI Product Foundations: Planning Strategies for Data Scientists
Optimizing development workflows
- Development workflows are often overlooked in AI product development. They're crucial for product relevance and competitive advantage. Great AI product development workflows increase iteration speed, reduced downtime, and make it easier to respond to market changes. When your workflow isn't smooth, every competitor's product release can become a crisis. Among the ways to structure workflows, three ways stand out. First, use gradual rollouts for flexibility during AI product launches. I learned this lesson the hard way when launching a sentiment analysis feature to our entire customer base. Within hours, we discovered the model struggled with industry specific terminology leading to a flood of support tickets. Since then, I've become a advocate for careful stage deployments. In fast moving markets, launching AI products or features all at once carries too much risk. Bugs, bad predictions or performance issues can damage the user experience and give competitors an edge. Smart…
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