OKRs and Product Strategy: New Version of the Skill in Skill Arena

Why a new version

In June 2026 we published the first version of this skill: measuring the change that work causes (the outcome) rather than the work delivered (the output), building well-formed objectives and key results, aligning and prioritizing with them, and sustaining them through check-ins and learning. That skeleton remains valid. When we reviewed it against current sources, we found two gaps and quite a few things that needed clarifying.

The first gap was in the name itself. The skill promised product strategy but did not explain where the objectives come from. The second is artificial intelligence, which the first version presented as something to watch. In October, Marty Cagan also offered a reading worth keeping in mind: the focus on output comes from the desire for predictability, and with AI making building cheaper, the problem of abundant output with scarce outcomes has never been more visible.

What's new

The skill keeps its four blocks and grows from thirteen to fifteen topics, each with its own chapter in the development guide.

• The paradigm, outcome over output: the cornerstone of the framework, OKRs as a tool to empower the team, the feature factory and its version within OKRs, and the epidemic of delivery dates.
• The anatomy of an OKR: the qualitative objective, the key result with a baseline and formula, leading and lagging metrics, now with the metric tree and the north star metric, and the types of OKRs.
• From strategy to OKR: a new topic, product strategy as the origin of OKRs, alongside bidirectional alignment versus cascading, OKRs as a filter for the roadmap, and the two-buckets technique.
• Operations: the check-in as a decision session, the trust system, closing the cycle, and a new topic, AI in drafting and tracking OKRs, which we present as an emerging trend.

All topics have been reviewed against their sources, and the guide now links to the Scrum Manager BoK pages that cover each concept.

Three ideas the new version brings to the foreground

Without strategy, OKRs are a wish list. Cagan describes product strategy as focus, insights, action, and management, and places team objectives at the step that turns insights into action. When that prior step is missing, OKRs fill up with whatever each department wants or with the usual requests dressed up as objectives. The guide proposes tracing each OKR back to the strategic decision it comes from, and recognizing the symptoms of OKRs that have no such origin.

Believing you already master the framework is part of the problem. Felipe Castro tells the story of a CEO who considered himself advanced in OKRs: in an initial review, 8 of the 19 key results in his company were projects with dates. If a key result can be marked as done on a specific day, it is a task. The guide teaches how to detect this and convert it, and presents Castro's criterion for deciding which work should not be in OKRs: if its outcome cannot be measured, at least for now, it is managed by dates, as a project.

AI proposes and the team decides. AI assistants are already built into OKR tools, but the evidence is scarce. The only available usage data, from a vendor, indicates that 83% of 222 technology companies use AI in their OKR process and that 13% accept its suggestions without review. The guide presents this as an indication rather than a measurement, and proposes a simple principle: every key result suggested by an assistant must pass the same tests as any other before the team makes it its own.

What we have corrected

A new version is also an opportunity to correct. In reviewing the first version against its sources, we have clarified:

• Who originated each type of OKR. Committed and aspirational OKRs, with their expected scores of 1.0 and 0.7, are Google's distinction; the third type, learning OKRs, is proposed by What Matters, the organization founded by John Doerr.
• The trust system. Christina Wodtke's original formulation is a trust scale from 1 to 10; the green, amber, and red traffic light is the common variant used in teams and tools.
• The two buckets. Castro's criterion for separating them is whether the outcome can be measured; the practical question we had proposed is an application of that criterion, and we now present it that way.
• Attributions and sources. The term feature factory was popularized by John Cutler in 2016; the Cagan quote about feature teams now links to the article that contains it; the number of key results per objective follows Google's recommendation, around three, and we have replaced links that led to home pages or to texts that did not address what was attributed to them.

Who it's for and what it certifies

This skill is for Product Owners, product managers, Scrum Masters, team leads, and any professional involved in defining or tracking objectives. It complements other Skill Arena skills:

• Agile product operating model, which addresses the place of strategy in the operating model,
• Product discovery and customer validation, which covers how to find out which solutions work,
• and AI applied to agile work.

The Skill Arena diploma certifies the ability to distinguish outcome from delivery, translate strategy into measurable objectives, and manage the OKR cycle with decisions and learning. The training and assessment banks have been fully regenerated from the new guide, at two difficulty levels.

The new version is available in Spanish and, for the first time, in English.

How to access it

The State of the Art, the development guide, and the training and assessment platform are on the skill's page in Skill Arena: OKRs and Product Strategy.

Read, practice, and tell us what you think. Every contribution, criticism, or suggestion helps us prepare the next version.