Software-Engineering on Harlan D. Harris

How Search and AI Product Teams are Different

harlan@harris.name (Harlan Harris) — Tue, 03 Feb 2026 00:00:00 +0000

Engineering leadership knows the standard playbook for product teams: the Product Trio, the Spotify model, outcome-based roadmaps, and so on. I've seen teams adopt these practices and still struggle when they add responsibility for advanced algorithms -- search, recommendations, predictive modeling, or generative AI -- without changing how the team is led. The processes and role expectations that work for a typical product team break down when the domain is heavily algorithmic. This post pulls together what I've learned and what others have written about building teams that own these systems.

Insights from a Predictive Model Pipeline Abstraction

harlan@harris.name (Harlan Harris) — Mon, 07 Nov 2016 00:00:00 +0000

This post was originally published on Medium

When building a complex system, it’s often helpful to think about the design of that system using patterns and abstractions. Architects and software engineers do so frequently, and the experience of implementing predictive modeling pipelines has recently led to a variety of patterns and best practices. For instance, when dealing with large amounts of streaming data, some organizations use the Lambda Architecture to handle both real-time and computationally-intensive use-cases.

Patterns for Connecting Predictive Models to Software Products

harlan@harris.name (Harlan Harris) — Tue, 12 Jul 2016 00:00:00 +0000

This post was originally published on Medium

You’re a data scientist, and you’ve got a predictive model — great work! Now what? In many cases, you need to hook it up to some sort of large, complex software product so that users can get access to the predictions. Think of LinkedIn’s People You May Know, which mines your professional graph for unconnected connections, or Hopper’s flight price predictions. Those started out as prototypes on someone’s laptop, and are now running at scale, with many millions of users.