Key takeaways SlashData is launching SlashData Intelligence for Software Engineering Leaders, a recurring research programme for CTOs, CPTOs, CEOs, VPs and SVPs of Engineering. Each Developer Nation wave will examine a major decision facing engineering organisations, combining open-access research with deeper premium intelligence. The first release explored AI ROI measurement. The next will investigate the future of developer teams, combining quantitative evidence with recurring interviews with software engineering leaders. Readers can follow the research, speak directly with SlashData analysts, and help shape future topics. Internal telemetry cannot tell you where the market is Engineering leaders are confident about AI. Their evidence is thinner than their confidence. The questions facing software engineering leaders are becoming harder to answer from inside their own organisations. Which AI investments are actually delivering value? How should that value be measured? How will AI change the structure of development teams? Which skills will become more important? Where are other engineering organisations investing, experimenting or pulling back? Internal metrics can answer part of this. Vendor information can answer another part. But leaders also need an independent view of what is happening across the software industry and how their organisation compares. That is the idea behind SlashData Intelligence for Software Engineering Leaders: a recurring research programme designed around the decisions senior engineering leaders are being asked to make. SlashData has been studying developers and the software economy for 20 years. The Developer Nation survey provides a global view of how software is built, which technologies developers adopt and how practices change over time across more than 10 different technology branches. Each wave reaches more than 10,000 developers worldwide, with its 31st edition alone reaching more than 11,880+. This new intelligence series takes that evidence and focuses it specifically on the questions that matter at the engineering leadership level. Explore SlashData Intelligence for Software Engineering Leaders The first question: can engineering organisations prove AI is paying off? The first research release examined a question that has quickly moved from experimentation to the boardroom: how do organisations know whether their AI investments are delivering? The free report, The AI ROI Measurement Gap, and the deeper premium report, The State of AI ROI Measurement in Software Teams, analysed responses from 2,341 professional developers in leadership positions. The findings revealed an important distinction between confidence and evidence. According to SlashData's 31st Developer Nation survey of 2,341 professional developers in leadership positions, 80% use AI-assisted tools and 75% of those consider them valuable relative to cost and effort. Our data suggests that although 88% say their organisation measures AI impact or ROI, only 39% of those measuring use formal or automated processes such as recurring KPI tracking, dashboards or automated monitoring. The accompanying webinar explored what that gap means for engineering leaders trying to justify investment, compare their measurement maturity with peers, and build an ROI case that finance and executive leadership will accept. This is the role the new series is intended to play: helping leaders understand where the market actually is, what separates common practice from more mature practice, and what that means for their next decision. The next wave: how AI is changing team size, structure, and roles The next research wave will turn to a broader organisational question: the future of developer teams. AI is changing more than individual workflows. Engineering leaders are now considering what it means for team size, role composition, seniority, governance, validation, productivity expectations and the capabilities their organisations will need over the next several years. SlashData will examine these changes using large-scale Developer Nation survey data alongside recurring qualitative interviews with software engineering leaders. The aim is to connect measurable shifts across the market with the reasoning behind the decisions leaders are making inside their organisations. The research will explore questions such as how AI may reshape team structures, which engineering skills and roles are likely to become more important, how organisations are balancing automation with review and governance, where junior developers fit in the process, and how expectations of software teams are changing. One research wave is not enough The value of this product line is intended to compound over time. Each Developer Nation wave will bring a new topic relevant to senior engineering leadership, with open-access findings alongside deeper premium intelligence, supported by formats such as webinars, analyst briefings, blogs, or other content. Over successive waves, that creates something more useful than a collection of standalone reports: a continuing view of how engineering organisations are responding to AI and the wider changes reshaping software development. For leaders making decisions in a market that is moving quickly, the goal is simple: provide an independent benchmark outside their own company, their vendors, and their immediate peer group. Learn more about SlashData Intelligence for Software Engineering Leaders If your organisation is currently making decisions around AI investment, engineering productivity or the future structure of software teams, speak directly with SlashData’s sales team and analysts. And the research agenda itself is open to input. If there is a question you think software engineering leaders need better independent evidence on, suggest a topic for a future research wave.

Key takeaways 79% of developers adding AI functionality to their applications use open models, ahead of 71% for closed models. The two are largely complementary. Half of developers use both at the same time, while 29% use only open models, and 21% use only closed models. The production gap: only 51% of developers using open models run them in production, compared with 63% for closed models. Production rates for closed models climb steeply with organisation size, from 54% at small businesses to 73% at large enterprises. Rates for open models barely move, from 53% to 57%. What developers using open models actually struggle with: deployment, scaling, maintenance Among developers adding AI functionality to their applications, more use open models today than closed ones, 79% against 71%. However, open models lag in production. Only 51% of developers using open models run them in production, compared with 63% for closed models, and open models trail slightly at the pilot stage as well (60% vs 65%). Developers are ready for open models, but the ecosystem around them may not be. According to the global survey that SlashData and Mozilla ran together in May 2026, covering 1,494 developers adding AI functionality to their applications, open models are the most widely used of the two families. It is important to note, though, that for many developers this is not a choice between one and the other: 50% of developers use both, while 29% use open models only, and 21% use closed models only. Adoption of open models is highest in Greater China and East Asia, at 89% each, against a global average of 79%. However, production rates for open models (51%) are noticeably lower than for closed models (63%). The data reveals that model performance is not what explains the difference, as it ranks among the least cited challenges for developers using open models. Some of the most common difficulties reported are the complexity of deployment and scaling, ongoing maintenance and updates, and managing the infrastructure and its costs. All of these point to the operational side rather than the models: the burden of owning the stack. That ownership brings real benefits, but it also introduces a set of problems that a hosted API absorbs on the developer's behalf. Additionally, SlashData found that, among professional developers, production rates for closed models climb steeply with organisation size, from 54% at small businesses (2 to 50 employees) to 73% at large enterprises (1,001 or more). For open models, however, production rates remain relatively flat across organisation sizes (from 53% to 57%). Open models lead on adoption, 79% against 71%, but reach production less often, 51% against 63%. Production rates for closed models climb with company size, from 54% at small businesses to 73% at large enterprises, while open models stay flat, 53% to 57%. SlashData and Mozilla global survey, May 2026, 1,494 developers adding AI functionality to their applications; the company size split is based on 954 professional developers. The next gains sit around the model, not inside it If the barrier were resources or in-house expertise, large enterprises would show the same lift for open models that they show for closed ones. They do not, which suggests this is not a gap that individual organisations can buy their way out of. For open model providers, foundations and tooling vendors, that flat line is the finding to act on. The demand side is already there: 79% of developers adding AI functionality to their applications are using open models. The loss happens further down the funnel, between working with a model and running it in production. The work likely to move production rates for open models sits around the model rather than inside it: the harness, hosting and serving infrastructure, upgrade and versioning paths, and better tooling. These map closely onto what developers using open models report as their main challenges, while model performance ranks among the least cited. Based on the data from this survey, those areas are likely to shift production rates further than additional gains in model quality. Commission your own research Need data-backed insights for your next thought leadership report?

The 32nd Developer Nation survey is now in the field, gathering insights from more than 15,000 software developers worldwide. Here are some of the key trends and insights you can expect from SlashData in Q3 2026, including builders, developer productivity, cloud adoption, and the future of software development. Meet the builders: shipping software without a developer background The biggest change on our 32nd wave is the onboarding of “builders” into our survey, a new group we’re tracking for the first time. Builders are people without traditional developer experience or backgrounds who are using AI tooling to build applications or services. As we discussed in our whitepaper, we’re looking at those building for personal use, those augmenting their internal workflows, and those building consumer-facing applications. Builders represent an emerging segment of the wider developer ecosystem rather than a replacement for traditional software developers. SlashData will be able to provide a picture of who these people are, how they engage with AI tools and the ecosystem, how AI has changed their working lives, and where they overlap with the traditional developer audience. How AI is reshaping the day-to-day Beyond builders, this research wave also digs into how AI is changing the way existing developers work. Spec-driven development, where developers define detailed requirements, constraints, and expected outcomes before AI-assisted code generation, is one of the new “buzzwords” being pushed to describe this shift. Our research will provide a clearer read on how prevalent the approach actually is, and for those doing it, what goes into their specs and how they feel about the approach philosophically. There’s also a lot of talk about the developer role shifting from writing code to reviewing it. It’s unlikely many developers dreamed of reviewing code all day, so SlashData is aiming to understand how prevalent AI code review really is, and who’s sending developers this AI-generated code (other developers, management, non-developer staff), and whether they integrate it, correct it, or scrap it outright. The future of developer teams: skills, seniority, and the junior developer squeeze With so much focus on how AI is reshaping developer life, we’re asking developers directly where they think the future of development teams is going: what skills they expect to matter, how they feel the current implementation is going, and the impact on junior and emerging developers. Combined with expanded developer wellbeing metrics, the aim isn’t just to say where developers think the future is heading, but how they’re feeling as they cruise towards it. Why DORA metrics stop short of developer productivity Where the future-of-teams work captures what developers predict and feel, SlashData is also going deeper on how effectiveness itself gets measured. This wave continues our move into metrics that extend beyond traditional DORA software delivery metrics, looking at what actually drives developer productivity, happiness, and effectiveness within organisations — split across organisational practices and benefits, and the value and meaning developers draw from their work. The goal is a wider, more holistic understanding of what it means to be an effective, happy developer, not just a faster one. Tracking the technology developers rely on: cloud provider preference and on-device AI SlashData continues to track the technologies developers use and integrate release over release, and this wave adds two areas we see as important drivers of where things are headed. Small, on-device models have fallen out of the spotlight as large open-weight models capture media attention (such as DeepSeek and Moonshot AI’s Kimi K3), but for many analysts, on-device AI is where the future of LLMs actually lies, so we’re assessing its scale in 2026 and asking developers where they see the best use cases emerging. Alongside this, we’re interrogating cloud provider preference across application types (including AI agents and generative AI services, alongside web/mobile applications, data analytics, CDNs, and serverless), aiming to sidestep vendor benchmarks and spec-sheet marketing in favour of what developers actually choose when given a free hand. Want early access? Reach out to the SlashData team, a leading research firm focused on the developer economy, to flag which of these you’d like to hear about first, or to make sure you’re kept in the loop when the data lands.

Independent market intelligence for CTOs and VPs of Engineering: defend AI investment decisions, prove ROI, and see where your organisation stands against the market.

Trusted by leading tech companies for 20+ years, SlashData is the leading research and analyst firm for AI software development and developer ecosystems. About More Best-in-class research firm on how AI is reshaping software development For over 20 years, SlashData has helped the world’s leading technology companies understand developers, software ecosystems, and how software development is changing in the AI era. Boost developer adoption by making the right strategy investments Our analysts can help you drive decision-making with confidence TALK TO OUR ANALYSTS Recent Webinars 30 July 2026 AI Is Transforming Developer Work. But Not Replacing Developers GET THE RESOURCES Just in: New AI insights Developer Ecosystem Insights - Adapting mobile apps beyond the smartphone (Jun 2026) GET THE INSIGHTS At Least 16 Million People Are Building Software Without Knowing How to Code (Jun 2026) GET THE INSIGHTS The 2026 State of Developer Adoption (Jun 2026) GET THE INSIGHTS Developer Ecosystem Insights - Autonomous AI agents in development (May 2026) GET THE INSIGHTS Cloud Repatriation: Not the Story We've Been Told (May 2026) GET THE INSIGHTS Developer Ecosystem Insights - The role of AI in software security (May 2026) GET THE INSIGHTS Choosing the right AI coding tools for your team SEE THE REPORT AI Coding Tools Benchmark: A comparison of 20 most prominent AI developer tools (Apr 2026) SEE THE LEADERS The State Of AI ROI Measurement In Software Teams (Apr 2026) GET THE INSIGHTS Blog Latest Who we are & what we do SlashData is an AI analyst firm which has been working with the top Tech brands to provide clarity and confidence in their decision-making. For 20 years, we have been tracking software technology trends and helping technology brands make product and marketing investment decisions. We challenge assumptions and reframe market trends to empower industry leaders to drive the world towards the future, by talking to developers, the early adopters and predictors of AI tech. They trust us Explore the developer economy, talk to an analyst. Contact us First name* Last name* Work Email* Company * Message SUBMIT

Make the most of your budget: Turn developers into high-conversion leads by investing on what they actually need. Don't waste budget on developer marketing activities that don't convert. Developer attention is expensive in the fast AI market. Let our analysts guide you on how to engage with developers. BOOK A CALL Make the most of your budget: Turn developers into high-conversion leads by investing on what they actually need. Here’s how independent developer research, analyst insight, and forward-looking signals help you engage the right developers. Then turn attention into qualified leads. 💡 Handy for: Professionals in Product, Marketing, DevRel trying to engage a software developer audience. Clear messaging, based on real developer priorities It's relevance that converts, not feature claims. Developer research reveals switching triggers, untapped needs, trust barriers, and must-have capabilities. In order to increase engagement and reduce friction, your campaigns must reflect what developers genuinely care about. Differentiate with credible, third-party insight In AI, everyone claims leadership. Also, everyone uses the saturated sources and tools. Original, independently validated data positions your brand as evidence-led, not self-promotional. This builds authority with both developers and internal stakeholders and improves brand awareness and lead quality. Allocate budget where it drives measurable impact Without clear insight, channel decisions become guesswork. Awareness tracking, engagement benchmarks, and competitive positioning data show where spend moves the needle. You redirect budget toward the activities that generate engagement, defensible ROI and industry-leading results you will be asked to present in conferences. Maximise your results. Talk to our team about your high-engagement needs. BOOK A CALL Trust SlashData for all your awareness, engagement and lead-gen needs 20+ years of surveying the developer space Our long experience in speaking to developers, ensures that you will get the promised results. We are paranoid about our methodology and have the largest data library from 20+ years of surveying developers. Analyst foresight Our team of analysts are subject-matter experts on AI and software development. They unlock trends in the data, foresee where the industry is heading and produce actionable insights you can immediately start applying. 24/7 Access to your data, the way you want it Access your insights in a within our Research Space. Make it work smart and hard for you by creating a personalised space with your favourite reports and dashboards, for you and your whole team. Have a look > Don't waste marketing budget. Target the right audience with a smaller budget. BOOK A CALL