How Duolingo Approaches Strategy, OKRs, and Discovery


How Duolingo Approaches Strategy, OKRs, and Discovery

READ ON

HERBIG.CO

PUBLISHED

Mar 7, 2025

READING TIME

4 min & 24 sec

​Dear Reader,​

Many Product Managers were in awe of the ways of working shared in The Duolingo Handbook a few weeks ago. While it’s an inspiring read, I used this as a reason to revisit some of my all-time favorite reads about how this company operates (or at least used to operate) and extract my takeaways with you.

Duolingo focuses on “Movable” Metrics for OKRs

via Meaningful metrics: How data sharpened the focus of product teams

Duolingo acknowledges the importance of broad strategic directions through lagging Impact metrics like Daily Active Users (DAUs). However, they have also realized this metric is strategically important but out of reach for steering and measuring individual initiatives.

After modeling driver metrics of DAU, they landed on Current User Retention Rate (CURR) as a potential driver. In the next step, they staffed a team who started running A/B tests to see whether 1) CURR is a metric they can move and 2) moving CURR actually moves DAU (remember: correlation does not equal causation!). And they were successful! With a team now focused on optimizing a movable metric, growth in DAU kicked off again. Since then, they have utilized the concept to set the quarterly OKRs of teams.

A Takeaway for your work: Revisit your team goals from a perspective of how movable (or, as I like to say, influenceable and leading) they are.

Duolingo Sometimes Puts Signals over Metrics

via How Duolingo builds product

To separate how the progress of metrics-based and feature-based teams are measured, they try to avoid the tyranny of metrics:

Obviously it’s harder to measure success with feature-based teams, but we’ve learned to work with that. We use a combination of qualitative and quantitative signals to see if we are tracking toward success, which looks different depending on the feature. For example, to measure how we are “making Duolingo more social,” we would use a few signals to decide if we are making progress:
- User research studies on the features we are building.
- Signals from public forums like Reddit and Twitter to see how our users are reacting to our features.
- Usage of features by Duos (Duolingo employees) and buzz around the features we are building. In other words, we look for how much Duos care about our features.

A Takeaway for your work: Don’t try to bend the success measures of teams whose work is hard to measure into obscurity by forcing them into conventional metrics structures. Acknowledge the importance of their work and focus on signals, not just metrics.

Duolingo’s Team Leads lean into their Unfair Advantage to create Space for Discovery

via How Duolingo builds product

Typically, a PM lead and an Engineering lead head up the team, sometimes joined by a Learning and Curriculum lead (experts in learning science, curriculum design, and educational content creation), Biz Ops lead, or Marketing lead, depending on what the team is working on.
Team co-leads are ultimately responsible for their team’s success and deciding its roadmap. They also own the decisions in their domain. For example, the PM co-lead owns more of the product discovery and roadmap decisions, whereas the engineering lead owns more of the product delivery and implementation decisions.

A Takeaway for your work: Even within a Trio, you want to make sure every member can focus on their unfair advantage instead of forcing everyone into the same type of work just for the sake of “equal collaboration.”

Did you enjoy the newsletter? Please forward it. It only takes two clicks. Creating this one took two hours.

Thank you for Practicing Product,

Tim

PS.: As I prepared for an in-house training day on adopting the Press Release FAQ format in the last weeks, I truly enjoyed Marcelo Calbucci's book on implementing this concept.

Content I found Practical This Week

Most PMs Aren't Good At Strategy

video preview

Thinking in Metrics

The most effective metric strategies often combine qualitative insights, quantitative measures, leading indicators, and strong signals. Let’s consider an example scenario: A new e-learning platform wants to improve user engagement and retention. First, the team uses qualitative metrics by interviewing users to understand pain points and unmet needs, discovering that users find the current onboarding process confusing. Next, they implement quantitative metrics by tracking daily active users and completion rates for courses. The team also establishes leading indicators to predict engagement, such as tracking users who create a learning plan and finish at least one lesson. Finally, they evaluate strong indicators by identifying users who complete 50% or more of a course, as this action signifies a deeper commitment to the platform. By combining these metrics, the team gains a well-rounded understanding of user behavior and actionable insights to improve product experience.

A guide to AI prototyping for product managers

Pretty cool. But what’s cooler is that you can use these tools to build functional prototypes from a Figma design, convert a rough hand-drawn sketch to a working app, translate a PRD document into an interactive prototype, or even build a usable internal tool for your team, with no coding ability. In this post, I’ll cover the basics of AI prototyping, show how to get good results out of the most popular tools, and walk through an end-to-end example of building a prototype in less than 10 minutes.

Who is Tim Herbig?

As a Product Management Coach, I guide Product Teams to measure the real progress of their evidence-informed decisions.

I focus on better practices to connect the dots of Product Strategy, Product OKRs, and Product Discovery.

Product Practice Newsletter

1 tip & 3 resources per week to improve your Strategy, OKRs, and Discovery practices in less than 5 minutes.

Read more from Product Practice Newsletter

Product Practice #358 Why your Users don't careabout your Product Strategy READ ON HERBIG.CO PUBLISHED Apr 11, 2025 READING TIME 3 min & 24 sec Dear Reader, One of the most powerful ways to spot and stop Alibi Progress is to start treating our practices like products. This means clearly defining three elements: Audience: For whom is this practice meant? Problem: What core problem does this practice aim to solve? Success: How would we know this practice has delivered value? The question then...

Product Practice #357 B2B vs. B2C Product Strategy READ ON HERBIG.CO PUBLISHED Apr 4, 2025 READING TIME 3 min & 30 sec Dear Reader, When I switched from B2C to B2B product management, I had to unlearn many tactical approaches - but the strategic fundamentals remained surprisingly consistent. The truth is that B2B and B2C product strategies share core patterns while differing primarily in execution. Key Similarities 1. Blended Audience Considerations Even dedicated B2C companies must consider...

Product Practice #356 4 Opportunities to Layer AI into Your Product Discovery Activities READ ON HERBIG.CO PUBLISHED Mar 28, 2025 READING TIME 4 min & 32 sec Dear Reader, To use AI to shorten your lead time and reduce uncertainty, consider it a layer to supercharge your existing workflow. Instead of generating with AI, think about supercharging with AI. Here are four common Product Discovery activities where thoughtful AI integration can dramatically reduce uncertainty without sacrificing...