# GitLab's internal playbook to foster AI-fluent technical teams

DevFeed: [GitLab's internal playbook to foster AI-fluent technical teams](<https://devfeed.tech/articles/gitlab-s-internal-playbook-to-foster-ai-fluent-technical-teams-96.md>)

Original publisher: [Read original article](<https://about.gitlab.com/blog/how-gitlab-fosters-ai-fluent-teams/>)

Author: Rob Allen

Published: 2026-09-02T00:00:00Z

Content type: article

Language: en

Sources: [GitLab](<https://devfeed.tech/sources/gitlab.md>)

Topics: [AI Strategy](<https://devfeed.tech/topics/ai-strategy.md>), [GitLab](<https://devfeed.tech/topics/gitlab.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-adoption](<https://devfeed.tech/tags/ai-adoption.md>), [ai-strategy](<https://devfeed.tech/tags/ai-strategy.md>), [collaboration](<https://devfeed.tech/tags/collaboration.md>), [compliance](<https://devfeed.tech/tags/compliance.md>), [enablement](<https://devfeed.tech/tags/enablement.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [workflows](<https://devfeed.tech/tags/workflows.md>)

## AI overview

GitLab shares an internal playbook for building AI fluency in technical teams. It describes a federated governance model that centrally manages foundational AI tools while allowing local experimentation and functional strategy.

## Source excerpt

Give two engineering teams the same AI tool and you can end up with two very different outcomes. One team ships faster with fewer bugs, while the other gets burned by an agent that confidently generates the wrong output. At GitLab, our team had AI tools at their fingertips and some found real value fast, working faster and catching issues earlier. Meanwhile, others hadn't quite found an entry point yet to develop effective AI-native workflows. We learned that building AI fluency -- how our team members know what to delegate to AI, how to build the right AI-native processes, and how to judge what comes back -- was just as important as AI tool adoption and access. Building that fluency across GitLab was both an operational and technical challenge requiring close partnership between our Enterprise Technology and Talent Development teams. We're sharing our internal playbook so other technical leaders gain another perspective on how to encourage the right kinds of AI adoption across their own organizations. An AI strategy built for the pace of our work Part of building the right paths for our technical teams was predicated on establishing smart foundational infrastructure. Enterprise Technology considered a few different structures to our governance. The first was a fully centralized team, but we worried that with the speed of AI technology, shipping approvals from one group could end up as a bottleneck. As a result, team members could become impatient and try to circumvent governance infrastructure to experiment with AI. The second was a fully decentralized approach, but that could fragment efforts across the company, which adds complexity and makes guardrail consistency challenging. We landed on a hybrid model, building governance and enablement into a model that used the best aspects of centralized and decentralized strategies: Enterprise AI acts as a central governance and technology hub: Based out of our Enterprise Technology team, Enterprise AI operates as the platfo