63% of Developers Engage With AI-Assisted Development ![rw-book-cover](https://static.wixstatic.com/media/998325_2f7fdcd2efd24cdba5fc60fc99968841~mv2.jpg/v1/fill/w_1000,h_563,al_c,q_85,usm_0.66_1.00_0.01/998325_2f7fdcd2efd24cdba5fc60fc99968841~mv2.jpg) ## Metadata - Author: [[Eleonora Fanouraki]] - Full Title: 63% of Developers Engage With AI-Assisted Development - Category: #articles - Document Note: --- tags: - #developer-survey - #ai-assisted-development - #generative-ai Author: Eleonora Fanouraki Source: DevRelX Reference: https://www.devrelx.com/post/ai-spotlight-63-of-developers-engage-with-ai-assisted-development date created: 2025-08-22 00:00 --- # Title: 63% of Developers Engage with AI-Assisted Development ## Table of Contents: - [📚 Summary](#-summary) - [🧠 Main Content](#-main-content) - [🗒️ Notes](#-notes) - [🔗 References](#-references) - [🗣️ Paraphrase](#-paraphrase) - [📰 Newsletter](#-newsletter) - [✅ Action Items](#-action-items) - [🧪 Hypotheses](#-hypotheses) - [📊 Methodology](#-methodology) - [❓ Questions](#-questions) - [🔮 Future Research](#-future-research) - [💡 Implications](#-implications) - [🧠 Learning Styles Assessment](#-learning-styles-assessment) - [♿ Accessibility Assessment](#-accessibility-assessment) - [🌍 DEIB Assessment](#-deib-assessment) - [✅ Logical Validity](#-logical-validity) - [🔍 DARVO Analysis](#-darvo-analysis) - [🔎 SEO Evaluation](#-seo-evaluation) - [🎯 Conclusion](#-conclusion) ### References: - SlashData, State of the Developer Nation (24th edition) — referenced throughout the article - Nylas DevRel practices referenced via Ash Ryan Arnwine - apidays New York talk reference by Ash Ryan Arnwine Note: You’ve read as far as 92% in this article. ## 📝 Summary: The article highlights findings from SlashData’s State of the Developer Nation (24th edition), emphasizing that 63% of developers engage with AI-assisted development. While overall engagement dipped by 4% year-over-year, active involvement (working on or learning) rose by 6%, and latent interest fell by 6%, suggesting maturation and practical applicability. Generative AI shows strong interest (57% actively involved or interested), with adoption patterns ranging from tool usage to API integration and model creation. DevRel leaders like Ash Ryan Arnwine share frameworks and principles for adopting AI responsibly—“experiment aggressively in private; ship with care.” Adoption barriers include trust for critical/security tasks and data requirements for training, partially mitigated by fine-tuning on pre-trained models. Leadership buy-in correlates with higher engagement, and broader trends show a cycle: overall interest down 5%, adoption up 4 points. ## 📖 Main Content: - Context and scope - The piece positions AI-assisted development as mainstream, citing 63% engagement, and frames generative AI as a rising adjacent trend with 57% interest. It references the State of the Developer Nation (24th edition) as the empirical basis. - Shifts in engagement quality - Although engagement slipped 4%, more developers are actively building or learning (+6%), with latent interest down (-6%). This implies movement from curiosity to practice. - Generative AI adoption modes - Developers use AI as a tool in their workflow, integrate AI via APIs, or build/extend models themselves. Engagement outpaces production adoption: AI-assisted tools lead with 17% adoption; generative AI projects draw 14% of engaged developers. - DevRel adoption principles (Nylas/Ash Ryan Arnwine) - Two guiding principles: AI as a “bicycle for the mind”; experiment privately, ship carefully. Practical example: using ChatGPT and GitHub Copilot to create sample code for an AI-enhanced spam filter, and enabling developers to “talk” to OpenAPI specs. - Barriers and mitigations - Hesitance for critical/security tasks; growing comfort for visual assets where risk is lower. Data scarcity for model training is mitigated by fine-tuning pre-trained models. - Leadership effects - Higher engagement among budget approvers (about 49–50%). Leadership is a key driver of AI adoption. - Macro trend - A cyclical adoption pattern: overall developer interest down 5%, while adoption rises by 4 points—suggesting consolidation from hype to implementation. - Call to action - Invites readers to download the full report covering topics beyond AI (e.g., female coders’ roles, API quality, embedded development). ### 🗒️ Notes - Adoption snapshot - 63% of developers engage in AI-assisted development. - Engagement type shifting from latent interest to hands-on learning/building (+6%). - Overall engagement down 4% YoY, possibly reflecting hype normalization. - Generative AI specifics - 57% actively involved or interested. - Adoption channels: - As a productivity tool in dev workflows. - API-based integration into projects. - Model creation/fine-tuning for specific tasks. - Adoption levels: AI-assisted tools at 17%, generative AI projects at 14% of engaged devs. - DevRel best practices (Nylas) - Principles: - Treat generative AI as augmentative, not all-encompassing. - “Experiment aggressively in private; ship with care” to protect developer trust. - Examples: - AI-enhanced spam filter sample code using ChatGPT/GitHub Copilot. - Let developers “talk” to OpenAPI specs to improve DX and discovery. - Risks and mitigations - Reliability/security concerns limit use for critical paths. - Visual asset generation reduces exposure to security risk. - Training data demands addressed through fine-tuning. - Leadership engagement - ~49–50% of budget approvers are involved in AI-assisted development. - Leadership acts as an adoption accelerant. - Broader landscape - Interest down 5%, adoption up 4 points—sign of maturation. - Non-AI areas of interest persist: crypto, API quality, embedded systems, compensation, language communities, diversity topics. ## 📖 References: - SlashData, State of the Developer Nation (24th edition) — AI-assisted and generative AI engagement statistics. - Ash Ryan Arnwine (Nylas), DevRel principles and examples for AI adoption. - apidays New York talk reference (OpenAPI conversational interfaces). ## 🗣️ Paraphrase: 1) Original idea: “The data from the survey suggest that 63% of developers engaged in some aspect of AI-assisted development… While overall engagement has experienced a slight decline of 4% over the past year, the nature of developer involvement has undergone a fascinating shift… More developers are actively working on or learning about AI-assisted development (+6%), while latent interest decreased by 6%.” - Paraphrase: Survey results indicate that nearly two-thirds of developers are now using AI-assisted approaches. Although participation dipped modestly compared to last year, the composition of that participation evolved: hands-on work and learning increased, and passive curiosity fell by a comparable margin, pointing to a move from interest to application. 2) Original idea: “Some developers may be hesitant to rely solely on generative models for critical or security-conscious tasks… tools offer the ability to fine-tune pre-trained models… leaders who approve budgets show higher engagement… interest dropped by 5% overall, while adoption increased by 4 percentage points.” - Paraphrase: Developers remain cautious about deploying generative systems in sensitive or mission-critical contexts, but fine-tuning established models can lower barriers. Decision-makers are comparatively more active in experimenting, and although general curiosity waned, actual deployment ticked upward. ## 📰 Newsletter: Learning web dev this week? AI is your new pair-programmer. Fresh data from SlashData shows 63% of developers are hands-on with AI-assisted tools, with generative AI close behind. Practical wins lead the way: code suggestions, docs drafting, and even “talk to your OpenAPI spec” prototypes are making DX smoother. Caution persists for security-critical paths, but fine-tuning pre-trained models lowers the bar for safe experimentation. Community highlights: DevRel teams like Nylas stress “experiment in private; ship with care”—wise words for plugin authors and platform teams. WordPress devs: keep an eye on AI-enabled linting, test-gen, and content scaffolding in your workflows. New tools and plugins we’re watching: - GitHub Copilot for PR reviews and test hints - Prompt-based OpenAPI explorers - Image generation pipelines for UI assets Recommended read: SlashData’s State of the Developer Nation (24th ed.) for the full picture. If you’re - Summary: The 24th edition of State of Developer Nation report from SlashData shows that 63% of developers engage with AI-assisted development, which shows that AI technology is maturing and turning into a valuable tool for software development. The report also highlights that generative AI is a new and exciting technology that attracted 57% of developers and is used to enhance visual assets in software development, making critical and security-conscious tasks risk-free. Besides, leaders in C-suite positions show higher engagement rates in emerging technologies, which can drive growth in AI-assisted and generative AI technologies. - URL: https://www.devrelx.com/post/ai-spotlight-63-of-developers-engage-with-ai-assisted-development You’re familiar with at least one AI-assisted development tool; That’s right, the ChatGPT. Its popularity has skyrocketed in the last few months and with good reason. It is designed to assist users in generating human-like text but it’s been helpful to developers too, as they can leverage ChatGPT to automate certain tasks, generate code snippets, assist in writing documentation, or even prototype conversational interfaces. While ChatGPT is primarily a language model, it can be used in the development process to aid in various aspects of software development. In SlashData's [24th edition of State of Developer Nation](https://slashdata.co/free-resources/state-of-the-developer-nation-24th-edition?utm_source=free_resources&utm_medium=sd_blog&utm_campaign=ai_son), we asked developers if they use AI and how. This led to a dedicated chapter on all the new technologies that captivate developers’ imaginations. The data from the survey suggest that **63% of developers engaged in some aspect of AI-assisted development,** making it evident that this technology is rapidly maturing and transforming from a mere trend to a valuable tool. While overall engagement has experienced a slight decline of 4% over the past year, the nature of developer involvement has undergone a fascinating shift. More developers are actively working on or learning about AI-assisted development, showing a **6% increase in engagement.** Simultaneously, the number of developers with latent interest has decreased by 6%. This dynamic suggests that *AI-assisted development is maturing and gaining **practical** applicability in the development landscape.* ![](https://static.wixstatic.com/media/998325_e74a83ef4580412cad13a581532e0177~mv2.jpeg/v1/fill/w_1812,h_1020,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/998325_e74a83ef4580412cad13a581532e0177~mv2.jpeg) #### Generative AI: Unleashing Creative Possibilities Alongside AI-assisted development, **generative AI** has emerged as a new and exciting technology. With **57%** of developers actively involved or interested in generative AI, curiosity and excitement abound. While AI-assisted development still leads in adoption at **17%**, generative AI projects attract **14%** of engaged developers. * as a helpful tool for their development process * by integrating it into projects through APIs * or even by creating the models themselves. Ongoing investigations are exploring these usage patterns to uncover more insights into this groundbreaking technology. We also wanted to take a closer look into how Developer Relations are adopting AI in their work. We asked our [**DevRelX Community**](https://www.devrelx.com/community?utm_source=DevRelX_Blog&utm_medium=AI_Spotlight&utm_campaign=DevRelX_Blog) members to share their take on how AI technologies are affecting DevRel and developer communities. [Ash Ryan Arnwine](https://www.linkedin.com/in/ashryan/), Director of Developer Relations, Nylas, shared inspirational ideas for experimenting with these new technologies. [Ash also wrote a blog post about how DevRel teams can start using AI.](https://www.ashryan.io/experimenting-with-ai-in-devrel/?utm_source=DevRelX_Blog&utm_medium=AI_Spotlight&utm_campaign=DevRelX_Blog) **Ash:** At Nylas, our DevRel team is using [a framework of four questions](https://www.idratherbescripting.com/episode/ai-chatgpt-devrel?utm_source=DevRelX_Blog&utm_medium=AI_Spotlight&utm_campaign=DevRelX_Blog) to help us explore where AI can be useful in key areas of our work. My hope is that our team can grapple with emerging AI capabilities while keeping a couple of guiding principles in mind. > ***First, the current wave of generative AI is the newest "bicycle for the mind"; it doesn't need to solve every problem perfectly to be a valuable tool. It's on us to learn this tool and wield it constructively in the service of our developers.*** The second principle is related: we experiment aggressively in private; we ship to developers with care and consideration. As an example of our framework in practice, we've used ChatGPT and GitHub Copilot to aid in writing a code sample showing developers how to build an AI-enhanced email spam filter. In other words, we're using AI to aid in completing the meta task of inspiring developers on ways to enhance their Nylas integrations with AI. On the developer experience side, it feels like the possibilities are almost infinite—as a simple example, I gave a talk at *apidays New York* a couple of weeks ago that highlighted the potential of enabling developers to "talk" to your OpenAPI spec. It's all so much fun. And the more we play, the better informed our product ideas and AI-enhanced DevRel work can become." Although generative AI is gaining high engagement, there are factors that affect its adoption among developers. Some developers may be hesitant to rely solely on generative models for critical or security-conscious tasks. However, there is a growing adoption of generative AI for **visual assets** in software development, which reduces the risks of errors and security vulnerabilities. Developers who work on generative AI models face the challenge of **needing a large amount of training data.** However, certain tools offer the ability to fine-tune pre-trained models for specific tasks, making this challenge easier to overcome. As developers become more familiar with assistive and generative AI technologies, we can expect a surge in their adoption, leading to innovation and creativity. Interestingly, leaders in C-suite and other leadership positions show higher engagement rates with emerging technologies. About **49%** and **50%** of those who approve tool expenses or budgets are actively involved in AI-assisted development. > ***This trend suggests that the revolution in AI-assisted development is driven by leaders who recognize its potential.*** When we take a broader view, we see a cyclical pattern in the adoption and interest in emerging technologies. *Developer interest has dropped by **5%** overall, while adoption has increased by 4 percentage points.* This contrast indicates a dynamic shift in developer preferences, marking a change from previous trends. In summary, AI-assisted development is rapidly evolving and attracting developers’ attention. Generative AI opens up exciting possibilities, and leadership engagement plays a crucial role in driving its growth. Cryptocurrencies continue to be intriguing, and the landscape of emerging technologies is constantly shifting. Did you find this article interesting? Download the [full free report](https://slashdata.co/free-resources/state-of-the-developer-nation-24th-edition?utm_source=free_resources&utm_medium=sd_blog&utm_campaign=ai_son) to learn about: * The rest of the technologies that capture the developers’ imagination * The Role of female coders in software development * An update on language communities * How well-paid developers feel * What makes a high-quality API * An Overview of embedded software development ![](https://static.wixstatic.com/media/998325_1f1e889c279743d88be63f1d03328791~mv2.gif), 63% of Developers Engage With AI-Assisted Development, Eleonora Fanouraki, 01h1vmvdxbx89rrj0jq7avwh4n.