Published via [GitHub Executive Insights](https://github.com/solutions/executive-insights "Executive insights, curated just for you") | Authored by [Bronte Van der Hoorn ](https://github.com/brontevdh)

Artificial intelligence is changing the software development lifecycle. From code completion to test generation and documentation, tools like GitHub Copilot are undeniably powerful. And so, amidst this technological acceleration, a quieter—and perhaps more enduring—question deserves attention:

__Are we creating the right conditions for AI to achieve maximum impact?__

It’s tempting to fixate on measuring progress in terms of usage or how many suggestions are being accepted. But the real question isn’t about your acceptance rate. You should be asking how well-aligned are your AI solutions and the work that matters most for your business.
To make this concept actionable, consider this Venn diagram.

### The three circles that matter
![engineering value venn diagram](//images.ctfassets.net/wfutmusr1t3h/1j2PVTkR7oqp1gHKEjyBLC/b7989cf22d45700f352af01bb82b452c/Screenshot_2025-05-15_at_2.33.51_PM.png)

This diagram brings together three intersecting ideas:

**1\. Work that’s worth doing: High-impact work**  
In software engineering, this is the work that drives improved business outcomes. Think: increased reliability, solving customer pain points, enhanced security and privacy posture, and faster time to market. It’s not just what's on the to-do list—it’s what contributes to the business’s short-term and long-term success.

**2\. Work that benefits from AI: AI-tool capability**  
This includes many familiar tasks such as code generation, reviewing pull requests, identifying edge cases, and writing tests. These are areas where AI can accelerate, suggest, and assist, sometimes dramatically so.

**3\. Conditions that enable effective AI use: Success conditions**  
The third circle is about creating the conditions that make AI genuinely effective. As [GitHub’s guidance on scaling Copilot](https://github.com/resources/whitepapers/scaling-github-copilot-across-your-organization) shows, success with AI isn’t just about tool capability. It’s about organizational readiness. It’s about:

* having clear intent and psychological safety around AI use.   
* delivering training that aligns with intent, is relevant to the team’s work, and shows what success looks like in practice.  
* incentivizing experimentation, not just efficiency.   
* having policies and procedures that guide responsible use.   
* updating engineering processes or responsibilities that account for changes introduced as part of the AI workflow. 

In short, you need to do more than make AI available—you need to create the right conditions to maximize its impact.

### The power zone: Where it all comes together

When all three circles overlap and we have all these elements—doing the right work, having the right tools, creating the right conditions—we enter what I call the **AI Power Nexus**.

**Test case development is a great way to see the AI Power Nexus in action**. It’s high-impact work. Check. AI is a capable partner. Check. To ensure we check success conditions:

* we know the behaviours and edge cases that matter most.   
* our engineers know how to use AI to generate the test cases.   
* we know of any regulatory conditions that we must test for.  
* test cases are integrated into an automated CI/CD pipeline. 

With all three circles checked, we’re in the AI Power Nexus. 

### The frustration areas: When a circle is missing

If you're not in the nexus, you're likely in frustration due to the misalignment between impact, tooling, and the conditions:

* **Tool frustration**: You’ve got valuable work and the right conditions, but the tools fall short for your use case.   
* **Conditions frustration**: You have valuable work and powerful AI tools, but teams lack training, trust, or clarity regarding how the tools fit within other processes. This is sometimes a case of “Copilot is installed, but no one’s sure what to do with it” problem.   
* **Impact frustration**: The tools are working, and your organization has created the right conditions, but the team could be using the AI on higher-impact tasks. This is where efficiency gains might be measurable, but untapped potential remains.

### The real opportunity for leaders

When it comes down to it, you need to adopt a mindset that prioritizes the creation of the conditions for your team to use AI for maximum impact.So ask yourself:

* Are we enabling the right conditions, and not just deploying tools? *(Success conditions)*  
* Are teams clear on what work actually moves the needle? *(Valuable work)*  
* Are we using AI where it has the potential to meaningfully assist? *(AI-tool capability)*

And the sooner you direct energy toward creating those conditions, the better. This means deeper satisfaction and greater long-term impact realization from this wave of transformation. So consider today how you can create the conditions for your team to use AI to achieve maximum impact.

---

Want to learn more about the strategic role of AI and other innovations at GitHub? Explore [Executive Insights](https://github.com/solutions/executive-insights) for more thought leadership on the future of technology and business.


Are we creating the right conditions for AI to achieve maximum impact?

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How to unlock the real value of AI in software engineering

Published via [GitHub Executive Insights](https://github.com/solutions/executive-insights "Executive insights, curated just for you")

The traditional approach to measuring productivity, and in turn velocity, is the number of lines of code. It's the most straightforward way to both understand and collect from a data perspective. Unfortunately, having this as our primary focus is a flawed approach. It both incentivizes the wrong behavior and doesn't provide a full picture of what a developer does in a day.

<div class="embed-responsive embed-responsive-16by9">
<iframe title="Beyond green squares: Effectively driving productivity" src="https://www.youtube.com/embed/5i9UGeCwl5s?si=TK05djX_-e1GFDR_" width="640" height="480" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe></div>

In this episode of Beyond the Commit, __[Eirini Nathan](https://github.com/ikaliam)__, staff researcher at GitHub, sat down with host __[Christopher Harrison](https://github.com/geektrainer)__ to help us better understand developer productivity. She explains that no developer sits down for a day's work with a goal of writing a certain amount of code. Instead they work to implement features, fix bugs, and design architectures — activities that aren't reflected in the green squares that appear on a developer's profile.

There are established frameworks, such as [DORA](https://dora.dev/) and [SPACE](https://queue.acm.org/detail.cfm?id=3454124), which are designed to provide a holistic overview of productivity. However, if you're new on this journey, these might not be the best approach. A better place to start is figuring out what goals you’re trying to meet by measuring, then have conversations with developers to determine any barriers they may be facing.

During the episode, Staff Product Manager __[Bronte Van der Hoorn](https://github.com/brontevdh)__ calls in to add her perspective on the importance of goals. After all, it's impossible to determine success if there isn't a clear definition of what success looks like. Once you establish goals, you both have a direction and a topic of conversation for your developers.

Talking to your developers should take many forms, including surveys, focus groups, and one-on-one conversations. Eirini recommends taking a three-step approach: listen, act, and learn. As you talk to your developers, listen to their experience and the blockers they face. Act on that feedback, working to make changes to improve both the developer experience and their productivity. Finally learn from that journey, see what worked and didn't, then make the appropriate adjustments.

To learn more and continue your journey, explore the resources below:

## Insights

- [Developer experience: What is it and why should you care?](https://github.blog/enterprise-software/collaboration/developer-experience-what-is-it-and-why-should-you-care/)   
- [The ultimate guide to developer happiness](https://github.blog/engineering/engineering-principles/the-ultimate-guide-to-developer-happiness/)   
- [Yes, good DevEx increases productivity. Here is the data.](https://github.blog/news-insights/research/good-devex-increases-productivity/)  
- [Survey reveals AI's impact on the developer experience](https://github.blog/news-insights/research/survey-reveals-ais-impact-on-the-developer-experience/)  
- [Research: quantifying GitHub Copilot's impact on developer productivity and happiness](https://github.blog/news-insights/research/research-quantifying-github-copilots-impact-on-developer-productivity-and-happiness/)

---

Want to learn more about the strategic role of AI and other innovations at GitHub? Explore [Executive Insights](https://github.com/solutions/executive-insights) for more thought leadership on the future of technology and business.

Before we can determine the impact of tools on productivity, we need to ensure we're asking the right questions.

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Beyond green squares: Effectively driving productivity

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The future of software development is evolving fast—are you ready to stay ahead? Join us for an exclusive look at GitHub’s latest innovations and a sneak peek at what’s coming next. From AI-powered code reviews and enhanced IDE support to advanced security features and new collaboration tools, this session is designed to help your team build, ship, and scale faster than ever.

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- Insights from product leaders on how AI and automation are shaping the future of software development.
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The future of software development is evolving fast—are you ready to stay ahead? Join us for an exclusive look at GitHub’s latest innovations and a sneak peek at what’s coming next. From AI-powered code reviews and enhanced IDE support to advanced security features and new collaboration tools, this session is designed to help your team build, ship, and scale faster than ever.

What’s in store for you: 
- A look at GitHub’s upcoming features and enhancements—plus the strategy driving their development.
- Insights from product leaders on how AI and automation are shaping the future of software development.
- Best practices to boost security, collaboration, and developer productivity.

Don’t miss this opportunity to stay ahead of the curve and see how GitHub can help your organization drive efficiency, security, and innovation.


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The future of software development is evolving fast—are you ready to stay ahead? Join us for an exclusive look at GitHub’s latest innovations and a sneak peek at what’s coming next. From AI-powered code reviews and enhanced IDE support to advanced security features and new collaboration tools, this session is designed to help your team build, ship, and scale faster than ever.

What’s in store for you: 
- A look at GitHub’s upcoming features and enhancements—plus the strategy driving their development.
- Insights from product leaders on how AI and automation are shaping the future of software development.
- Best practices to boost security, collaboration, and developer productivity.

Don’t miss this opportunity to stay ahead of the curve and see how GitHub can help your organization drive efficiency, security, and innovation.


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