14 software developer trends & insights you need to know in Q1 2026
- Stathis Georgakopoulos
- 7 minutes ago
- 9 min read
The AI transformation currently taking over the software development industry has already shown that many aspects of this revolution are here to stay. Amidst rapidly changing landscapes, we have always found solace in the reality of data, sourced through best-in-class research.
The software/AI industry is drowning in noise: Hype cycles, vendor-spin, conflicting “evidence”, model benchmarks that don't reflect real-world use, and adoption statistics that are basically…marketing.
Executives in this space have been burned repeatedly by analysis that turned out to be extrapolation dressed up as data. CTOs, CPOs, and VPs of Engineering make daily build/buy/partner decisions, AI adoption strategies, and platform bets. These are high-stakes, high-regret decisions. The cost of acting on bad analysis is enormous.
We’re proud to be able to tell them what's actually happening: how software gets built, what developers need, what teams prioritise, and how AI is actually adopted.
With that in mind, this article is a “highlight reel” of the top findings we discovered over the past few months.
A new, updated batch of insights is coming in within the next few weeks. Join the newsletter to get updated first.
Here’s what you need to know, now (with sources because we’re into insights, not clickbait). If you want to know something very specific, we're here for you.
Artificial Intelligence in software development highlights in Q1 2026
AI on Edge: An on-device focus
What we found:
Smartphones and tablets are rapidly evolving edge AI targets, driving demand for NPU-optimised on-device models.
Edge devices are becoming an increasingly important way for artificial intelligence (AI) to reach end users, from smartphones and laptops to wearables, industrial machines, and connected vehicles. This report aims to understand how developers are currently integrating AI models into edge devices and where the main opportunities to reduce friction lie. Based on a global survey of professional software developers who reported building or implementing AI functionality in the 30th edition of our global Developer Nation survey, the analysis details the widespread usage of edgeAI among these developers, regional differences, the devices they target, the approaches they use, and the main challenges they face when deploying models on the edge.
AI in Game Development
What we found:
Over half of game developers fear AI will further reduce job opportunities amid an already fragile industry marked by widespread layoffs
In this report, we take a look at today’s landscape of game development. We examine who game developers are, the technologies, engines, and programming languages they rely on, the platforms they target, and the types of games they create. The report also explores how game developers perceive the impact of AI in the industry, shedding light on both the opportunities and the challenges it introduces.
AI tool usage across professional developers (full report free to access)
What we found:
As of Q3 2025, ChatGPT and GitHub Copilot lead in adoption and satisfaction as AI-assisted coding tools among professional developers, reinforcing their position as the safest bets for large-scale rollouts.
The rapid rise of AI-assisted coding tools marks a pivotal moment in software development. What began as experimental add-ons has quickly evolved into a crowded market of products, each claiming to boost productivity and transform workflows. Yet with so many options and so much noise, it can be difficult to know which tools are truly delivering value. By examining adoption, satisfaction, and trust-related attributes such as accuracy, support, and security, this report provides a data-driven benchmark of which AI coding tools developers are embracing and which they rate most highly.
The analysis reveals where usage aligns with satisfaction, where trust is earned through consistent delivery, and where gaps remain between expectations and reality. For engineering leaders making decisions about which tools to integrate and scale across their teams, the insights in this report help distinguish the coding tools that enable productivity from those that are still struggling to meet developer needs.
AI Blockers: why developers don’t build GenAI apps
What we found:
Most developers remain open to using generative AI if key concerns are addressed. However, stronger privacy and security controls are at the top of confidence drivers, especially for those facing data and compliance barriers.
The aim of this report is to understand what prevents developers from integrating generative AI functionality into their applications and what could increase their confidence to do so. For vendors of generative AI platforms and APIs, these findings highlight the areas where developers most need reassurance and support, from robust data protection and clear documentation to seamless integration paths.
Agentic AI in software projects (full report free to access)
What we found:
Agentic AI is moving beyond the experimental stage. Of those integrating AI into their applications, half have already deployed agentic AI architectures to production
Agentic AI is emerging as one of the most transformative shifts in how companies design and deploy intelligent systems. This mini-report analyses insights from over 8,400 professional developers to help CTOs and engineering leaders navigate the rapidly evolving agentic AI landscape and make informed architecture and use case decisions. We’ll explore how the implementation of agentic AI varies by company size and project type as well as looking at the types of agentic architectures that are being deployed to production, along with the use cases developers are targeting.
Programming language communities and software developer population size
There are 48.4 million developers around the world
“How Many Developers Are There in the World?” is our most frequently asked question here at SlashData, both from Product and Marketing people who want to measure adoption, executives who care about their Target Addressable Market (TAM), and software industry journalists and enthusiasts.
To help them all with their goals, we happily share this number and update it as new data becomes available. Go ahead and confidently use this number in your pitch, BoD presentation, or article. We follow a strict methodology to ensure that this is the most accurate estimate you can get.
JavaScript is the most popular language for software development (full report free to access)
What we found:
As of Q3 2025, JavaScript was the largest language community, with approximately 27M developers worldwide.
Programming languages sit at the heart of the software development ecosystem, shaping not only the kinds of projects developers work on but also the communities they become part of. For product executives, understanding language adoption is more than an academic exercise as it directly informs decisions about which SDKs, APIs, and platform features to prioritise. Choosing the right languages to support can expand the reach of your platform, lower barriers for developers, and ultimately drive product adoption.
Assessing how widely used a programming language is and estimating the size of each language community in absolute terms remains a challenge. The estimates presented here are based on two key data sources. First is our independent estimate of the global number of software developers, which we have been publishing for more than eight years. Second is our large-scale surveys, which reach tens of thousands of developers every six months.
A look into DevOps
DevOps: Lack of standardisation is connected to less security
What we found:
Organisations without DevOps standardisation show between two and three times lower rates of integrating security practices into their CI/CD pipelines
This report examines the security practices that developers integrate into their CI/CD pipelines, with a particular focus on how platform standardisation approaches influence which security tools see adoption and success. In this report, platform standardisation refers to organisation-wide standardisation strategies for DevOps practices, and we categorise platform configurations into five distinct groups: specialised internal developer platforms (IDPs), dedicated teams or individuals responsible for developer experience, unified systems for managing DevOps processes, curated lists of approved tools, and organisations engaging in none of these approaches. This report is based on data from SlashData’s 30th edition of the Developer Nation survey and represents the adoption patterns of more than 4,700 professional developers using CI/CD pipelines.
Company size and industry shape affect deployment strategies (full report free to access)
What we found:
As organisations grow in size, two overarching strategies to backend DevOps maturity emerge, with some empowering their developers to use a wide range of advanced technologies effectively, while others abstract away infrastructure behind internal development platforms leading developers to prioritise business needs
This report examines cloud and server-side technology adoption patterns across organisation sizes and industry sectors, revealing insights that challenge conventional wisdom about technology maturity.We explore how multi-environment strategies evolve with organisational scale, why container adoption varies across company sizes, and how platform teams create infrastructure capabilities that are frequently invisible to their developers.
Through analysis of deployment strategies, modern architecture adoption, and industry-specific technology leadership, we provide IT executives with frameworks for evaluating their technology strategies against relevant peer organisations rather than generic industry trends.The findings reveal that successful technology adoption depends lesson following best practices and more on aligning technology choices with organisational capabilities, industry requirements, and strategic priorities.
Cloud updates you should know in Q1 2026
Cloud-native development (update coming in March 2026)
What we found:
There are 15.6M cloud native developers, of which 9.3M are backend developers
This report explores the current state and scale of cloud native development in Q3 2025. The report provides approximations of the cloud-native developer population in backend services, machine learning or AI, and throughout the entire developer population. The report also provides information on the popularity of different cloud native technologies or approaches among backend developers, to reveal the sophistication path organisations often go through.
In addition, the report explores the trends in cloud deployment approaches, as well as the technologies that developers are using in their backend or cloud development processes and services. We also provide estimates for the proportion of cloud nativeness throughout the range of types of development (e.g. mobile, desktop, DevOps, etc.).
Data residency: Compliance in practice
What we found:
Collaboration between developers and legal teams is the leading challenge developers cite.
This report provides an examination of how organisations are coping with data residency compliance in practice. It explores the primary challenges developers face when building compliant services, how these challenges vary by region and organisation size, and where responsibility for compliance tasks falls within organisations. The analysis reveals significant regional differences in both the nature of compliance challenges and how organisations structure accountability, offering insights for how cloud service providers (CSPs) should design their compliance offerings and which capabilities matter most to customers in different markets.
FinOps beyond cost-cutting (full report free to access)
What we found:
Mid-sized organisations lead in FinOps adoption, likely due to scaling cloud complexity. Budget monitoring and reporting are the most common FinOps activities, highlighting the importance of visibility into cloud spending.
Source: The State of FinOps in 2025
Cloud spending can become one of the largest operational expenses for tech companies. It is often unpredictable due to elastic consumption models, hundreds of services and pricing models, and decentralised purchasing by developer teams (particularly in large companies). Cloud financial management (FinOps) sits at the intersection of finance, engineering, and product, ensuring that cloud resources are used efficiently, focusing on aligning cloud spending with business value, not just cost-cutting.
In this report, we examine insights from over 6,300 professional developers working for companies with at least 2 employees who use cloud services. We’ll explore the adoption rate of FinOps practices among developer teams and how it varies by company size and region. Additionally, we’ll cover how teams implement FinOps by looking at the specific practices they have embraced. The report is designed to help technical leaders benchmark their organisations against industry peers and make informed decisions about where to focus their FinOps efforts.
AR, VR and IIoT software developer trends
AR and VR: ARVR practitioner numbers remain stable
What we found:
There are approximately five million AR/VR practitioners worldwide, a figure that has remained relatively stable over the past two years. 83% of AR/VR practitioners are leveraging AI across multiple use cases, from coding to content creation.
This report provides a detailed examination of today’s XR landscape. It explores how many practitioners there are, how they participate in the ecosystem, the types of projects they are building, and the platforms they target. It also investigates how XR practitioners are leveraging AI and which other technologies make up their stack. Finally, the report looks at the main challenges XR practitioners face today and looks ahead to the future of the AR and VR industries, capturing XR practitioners’ and other developers’ perspectives on its direction for the next decade.
IIoT onboarding is frictionless
What we found:
First IIoT development board onboarding is largely frictionless, as 65+% of professional developers involved in IIoT projects find “setting up the hardware” and “running a basic project” easy.
Source: IIoT accessibility
This report explores how developers begin their IIoT journey: which development boards they start with, how they experience onboarding across tasks and ecosystems, and how these patterns differ by professional status, experience level, and region. The findings highlight where the industry is lowering technical barriers and where better documentation, community support, or learning pathways are still needed. Insights come from the 30th edition of the Developer Nation survey, which ran from June to August 2025 and reached 830 developers worldwide involved in IIoT projects.
After 20+ years of researching the software industry, we have a huge (HUGE) data library we can tap into to answer your questions. Our analysts are subject-matter experts on software development topics and can foresee trends and help you power your strategy with evidence.
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About the author
Stathis Georgakopoulos, Marketing Manager at SlashData
Stathis leads SlashData's marketing activities and product marketing and loves building helpful content that turns complex research into practical decisions. He focuses on setting the table for launches and campaigns, and has a soft spot for content marketing and terrible puns.