Developer Experience (also called “DevEx” or “DX”) has a direct positive correlation with productivity and innovation.
Elsewhere, I wrote about how to spot the telltale signs of subpar developer experience.
In that post, I suggested
Invest in resources and processes that make life easier, and nurture a sense of ownership.
Work toward seamless collaboration to reduce data silos, improve visibility and enable more efficient workflows.
Optimize the development environment to reduce friction and automate repetitive tasks.
Be conscious about culture to create a supportive, inclusive environment where people feel trusted and appreciated.
AI is ready to solve some major DX problems.
Teams that get this right can expect to unlock substantial competitive advantages.
I want to share how I think that can work.
This category of tools is all about exposing high-quality information in the right places.
That’s everything from creating useful, accurate resources to ensuring the right information reaches the right people at the right time.
The first use case for AI is perhaps one of the more obvious use cases – generative AI for creating resources.
These kinds of AI can do things like write code documentation for you automatically or summarize meetings so you don’t have to rewatch the whole thing.
Pick 1: Meeting summarization with
Pick 2:
The second use case for AI in this category is for surfacing what matters.
As far as I’m aware, there’s only one tool that observes and reflects on everything that happens across the tools you use and surfaces what matters in a bespoke, personalized way.
It’s called Stepsize AI, and I’m building it with my team at Stepsize.
Pick 3:
It deeply understands the context of what your projects and goals are and can even answer questions about what’s happening. Here’s what that looks like:
We have to invest in reducing friction in the development environment if we want to boost productivity and satisfaction.
AI has come on leaps and bounds in the last year in developing specific niches of the engineering process.
Ask any developer, and they'll tell you - coding is often the stage where ideas take form but also where major bottlenecks occur. Too often, teams lose precious hours to syntax errors, library issues, and bugs that just won't squash.
This hurdle can feel like a steep climb, causing unnecessary delays and frustration.
Furthermore, codebases are living, evolving organisms. Your team's work isn't just about implementing new features, but also about understanding and navigating existing code.
Annotating and understanding complex codebases can be a Herculean task, especially if the original author isn't around.
AI Pick 4:
Honorable mentions:
It's often a time sink because it's easy to get lost in endless lines of code, particularly if you're working on a complex project or a large team.
Moreover, non-technical team members often find themselves left out of the loop. When your developers, product managers, and stakeholders aren't on the same page, it can cause confusion and delay decisions.
AI Pick 5:
It’s also great for keeping non-technical team members in the loop and works really well with tools like
Honorable mention:
Let me guess. Nobody on your team lives for maintenance. But you have to deal with dependencies and migrate code.
If only there were a way to do that hands-free.
AI Pick 6:
AI for software developers isn't a silver bullet that's going to solve all your DX issues with DX tools overnight.
It's a facilitator. It’s about leveraging the power of artificial intelligence to bolster the creative and innovative elements of software development.
That's where the real competitive advantage lies.
Adapting to an AI-driven Developer Experience (DX) requires more than just selecting the right tools. It's a holistic process that impacts your team's workflows, skillsets, and overall development culture.
As leaders, our roles in this transition extend beyond decision-making to driving the necessary change.
Firstly, ensure your engineering team is trained and well-equipped to work with AI tools.
Next, reevaluate your development workflows.
Lastly, and perhaps most importantly, nurture that culture of continuous learning and innovation. The AI landscape is continuously evolving, and to make the most of it, your team should too.
Encourage your software engineering teams to stay updated with the latest AI trends, offer regular training, and create a safe space for experimentation.
Remember, AI's potential is best unlocked when human creativity and machine intelligence are blended.
That’s why I created Stepsize AI, the AI Operational Intelligence Engine that takes all the manual work out of keeping informed about what matters.
By integrating with Jira, Slack, GitHub, and more, Stepsize AI deeply understands the context of your projects and goals, providing bespoke, personalized updates for any person or team depending on what matters to them.
We believe Stepsize AI is a game-changer. I’d love for you to give it a spin.
Also published here