TLDR; AI DevEx tooling improves developer experience by automating repetitive, manual tasks, giving developers more time to focus on development.
Good developer experience isn’t a luxury reserved for big companies with specialized teams. It doesn’t require an entire team of platform engineers or months of process overhauls. For most small to mid-sized engineering organizations, great internal DevEx is within reach with a couple of process tweaks and internal automations to minimize distractions and manual work. But the time required to implement these changes can be limited (and by limited, I mean non-existent).
This is where AI tooling can be extremely helpful. AI tools that “automate the automations” can handle repetitive, manual tasks and time sinks, giving development teams more time to focus on building and writing code. Common developer pain points like digging through CI logs to debug a flaky test or dealing with increasingly slow CI pipelines are partially or completely automated with good DevEx tooling and processes.
What is “good” developer experience?
If you ask 10 different developers what developer experience means, you might get 10 different answers - from quick onboarding and environment setup, reducing time spent debugging and fighting issues, proper internal documentation, and minimal meetings.
All of these answers relate to the principles of good developer experience:
Increase developer flow state: Allow developers to focus on deep and engaging work without getting distracted and context switching.
Reduce the cognitive load: Make processes simple, code understandable, and deployments easy.
Quick feedback loops: Minimize the time it takes to get PR feedback and answer questions ASAP so developers spend less time stuck or blocked.
At the heart of these principles is one thing: time. Good developer experience means that developers spend more time… developing!
In 2024, GitHub published a study that (finally) shows how good DevEx impacts development teams.

It shows that teams that invest in good processes and tooling to limit distractions, reduce context switching, and speed up feedback time have happier and more productive developers. Developers who can focus on deep and interesting projects report a 50% increase in productivity, devs who understand their codebase well are 42% more productive, and intuitive processes help developers feel 50% more innovative.
These are staggering numbers, but finding time to change how your team or organization works and build automations can be difficult, especially if your organization doesn’t already have a DevEx team.
That’s what Trunk is trying to change.
What is Trunk doing to bring good DevEx to dev teams?
At Trunk, we’ve been thinking about how dev teams of all sizes can get the benefits of a great DevEx without having to build everything from scratch or hire a dedicated team. The AI DevOps Agent is our answer to that.
The agent connects to your existing tools like Slack, Linear, and GitHub, and uses webhooks and cron jobs to schedule repetitive asynchronous tasks that require context switching and take time away from actually building products.
It’s built to help you reclaim time that is better spent on coding and building. Not just by automating repetitive tasks, but by automating tasks that normally require manual investigation and providing developers with the information necessary to quickly solve problems.
Some example use cases for an AI DevOps Agent include:
Automating flaky test detection and quarantining, while providing root cause analysis for quick fixes.
Pinpointing inefficiencies in CI processes, for example, when tests are running slower compared to last month.
Running tasks from CI events automatically, like updating PMs and managers with a weekly summary of what has shipped.
Integrate with your existing tooling, for example, annotating your GitHub PRs with root cause analysis when CI fails, sending Slack alerts when CI is failing, or auto-creating Linear tickets containing relevant debugging info when a test is detected as flaky so it can be fixed for good.
Enforce code quality standards, such as in open source repos, where contributors may or may not follow all the contribution guidelines.
The result is that dev teams can spend less time chasing down pipeline failures, tracing through logs, and fighting test flakes, and more time solving the problems users actually care about. The AI DevOps Agent supports developers’ flow state, reduces cognitive load when debugging, and shortens the feedback loop by collecting and sending relevant information right away.
For teams that don’t have the luxury of full-time DevEx resources, this is a real upgrade. You can make your workflow faster, cleaner, and more enjoyable without trying to become a DevEx expert yourself.
Trunk’s AI DevOps Agent won’t sit in your standups or write your quarterly OKRs (yet!). But it can help make sure your CI jobs run smoothly, your tests are reliable, and your codebase stays healthy. It doesn’t take over your job. It just gets the mess out of your way so you can do it better.
The best developer experience isn’t just about tools. It’s about time. More time spent writing code, solving hard problems, and building things that matter. And now, with the right kind of AI, that’s something every team can finally have.