Developer Experience (DevEx) as a Key Driver of Productivity

Developer experience (DevEx) refers to all aspects of interactions between developers and the tools, platforms, processes and people they work with to deliver software products and services.

Creating a superior DevEx requires an environment where developers can thrive and do their best work to achieve optimal productivity with minimal friction and maximum flow. Providing a high-quality developer experience has become a top priority for software engineering leaders as they face pressure to improve their teams’ productivity and retain top talent. 

Gartner research shows teams with a high-quality developer experience are:​

• 33% more likely to attain their target business outcomes​

• 31% more likely to improve delivery flow​

• 20% more likely to intend to stay with their employer

Gartner predicts that through 2027, organizations that establish formal developer experience initiatives will be twice as likely to retain their developers from their current levels. But to achieve these outcomes, software engineering leaders must monitor the quality of their developer experience and drive continuous improvement. 

Gartner’s view of DevEx extends beyond developer tools and technologies into nontechnology factors such as having dedicated time for creative, meaningful work, as well as more flexibility and autonomy to try new things without the fear of failure. 

But tools used in day-to-day work certainly play a role in improving the quality of developer workflows — for example, onboarding platforms, self-service internal developer portals, environment management and collaborative tools.

To succeed, software engineering leaders must:

• Identify pain points for their teams and determine the best way to plug gaps in the desired experience. The idea is to discover points of friction and prioritize eliminating the ones that pose the greatest constraint to the flow of value.

• Go beyond optimizing development workflows and provide focus time for deep, creative work along with the freedom to fail and experiment.

• Streamline software delivery workflows across multiple product teams with a platform engineering practice that is focused on DevEx.

AI-augmented software development is the use of AI technologies, such as large language models and other generative AI (GenAI) models, to aid software engineers and designers in creating and delivering applications. It commonly integrates with an engineer’s existing toolset to provide them with real-time, intelligent feedback and suggestions.

GenAI tools that assist with writing, documenting and testing code improve developer productivity. However, these activities are just one aspect of productivity. 

To realize the greatest gains in developer productivity, use GenAI tools to:

• Augment coding and testing activities

• Enhance developer experience by removing constraints to developer satisfaction, collaboration and flow.

• Achieve more valuable outcomes.

Gartner predicts that by 2028, 75% of enterprise software engineers will use AI coding assistants, up from less than 10% in 2023.

Design-to-code tools automatically generate near production quality front-end code from screen designs on a digital design platform. AI coding assistants automatically generate code based on the intent of the developer and by using surrounding comments and code as input. AI-driven testing tools automate application testing from the creation of acceptance criteria, test scenarios, automation scripts and customized testing reports.

Software engineering leaders must prepare a plan for their teams to adapt their workflows — not only to utilize these tools but to adjust the application development efforts to reduce the amount of time spent on lower-level tasks to allow for more complex software engineering tasks.

Justify the value of AI augmenting your teams by establishing value-based productivity metrics and explaining how this technology is not a cost reduction tool or a replacement for staff, but a force multiplier that will enhance the productivity and efficiency of software engineering teams.

Many software engineering leaders seek to measure and improve the productivity of their developers, but it’s notoriously hard to do so in practice. Value-based productivity metrics will give teams the tools and information they need for self improvement, and focus software development teams on creating value by producing good solutions to important problems.

The first step for software engineering leaders is to dissuade stakeholders from relying on conventional productivity metrics, such as lines of code written or agile team velocity. Doing more of certain activities per day does not necessarily lead to more valuable software being produced. Value-based metrics, by contrast, help teams to inspect and analyze their ways of working to achieve a shared goal of higher productivity. 

Value can be calculated in advance, verified in production and applied at a fine-grained level, such as features, instead of entire products.

Developers must create the right software in order to produce value. The desired outcome of a software engineering process is not simply “some software” but “a good solution to an important problem” or “a good way to achieve a business outcome.” 

Key considerations about the value of what software developers produce:

• Value is derived both from the importance of the problem and from the “goodness” of the solution. 

• Each case is unique, even if we get some reuse from past solutions, so we must recalculate value each time. 

• A “good solution” is one that not only solves the problem or achieves the intended business outcome, but does so in the way that produces optimal value for all its stakeholders, including those that must operate and maintain it.

• While the business outcome itself is paramount, usability, security, reliability and many other aspects contribute to a solution’s value. 

  • These aspects can be weighted, based on how significant each is for the case in question. 

  • The value the solution delivers in each aspect can then be scored relative to other solutions the team has created in the past. 

  • The total of the weighted scores is the value of the solution.

Tactics that software engineering leaders can use to help teams improve their productivity include:

• Providing teams with access to the metrics they need and with the tools required to gather and analyze them

• Setting value-based productivity goals and granting teams the autonomy to find their optimal way of working

• Endorsing and chartering communities of practice that provide teams with a way to share insights and practices

• Supplying the coaching, mentoring and learning resources that the teams request