In 2025 AI reshaped how teams think, build, and deliver software. We’re now at a point where “AI coding assistants have quickly moved from novelty to necessity [with] up to 90% of software engineers us[ing] some kind of AI for coding,” Addy Osmani writes. That’s a very different world to the one we were in 12 months ago. As we look ahead to 2026, here are three key trends we have seen driving change and how we think developers and architects can prepare for what’s ahead.

Evolving Coding Workflows

New AI tools changed coding workflows in 2025, enabling developers to write and work with code faster than ever before. This doesn’t mean AI is replacing developers. It’s opening up new frontiers to be explored and skills to be mastered, something we explored at our first AI Codecon in May.

AI tools in the IDE and on the command line have revived the debate about the IDE’s future, echoing past arguments (e.g., VS Code versus Vim). It’s more useful to focus on the tools’ purpose. As Kent Beck and Tim O’Reilly discussed in November, developers are ultimately responsible for the code their chosen AI tool produces. We know that LLMs “actively reward existing top tier software engineering practices” and “amplify existing expertise,” as Simon Willison has pointed out. And a good coder will “factor in” questions that AI doesn’t. Does it really matter which tool is used?

The critical transferable skill for working with any of these tools is understanding how to communicate effectively with the underlying model. AI tools generate better code if they’re given all the relevant background on a project. Managing what the AI knows about your project (context engineering) and communicating it (prompt engineering) are going to be key to doing good work.

The core skills for working effectively with code won’t change in the face of AI. Understanding code review, design patterns, debugging, testing, and documentation and applying those to the work you do with AI tools will be the differential.

The Rise of Agentic AI

With the rise of agents and Model Context Protocol (MCP) in the second half of 2025, developers gained the ability to use AI not just as a pair programmer but as an entire team of developers. The speakers at our Coding for the Agentic World live AI Codecon event in September 2025 explored new tools, workflows, and hacks that are shaping this emerging discipline of agentic AI.

Software engineers aren’t just working with single coding agents. They’re building and deploying their own custom agents, often within complex setups involving multi-agent scenarios, teams of coding agents, and agent swarms. This shift from conducting AI to orchestrating AI elevates the importance of truly understanding how good software is built and maintained.

We know that AI generates better code with context, and this is also true of agents. As with coding workflows, this means understanding context engineering is essential. However, the differential for senior engineers in 2026 will be how well they apply intermediate skills such as product thinking, advanced testing, system design, and architecture to their work with agentic systems.

AI and Software Architecture

We began 2025 with our January Superstream, Software Architecture in the Age of AI, where speaker Rebecca Parsons explored the architectural implications of AI, dryly noting that “given the pace of change, this could be out of date by Friday.” By the time of our Superstream in August, things had solidified a little more and our speakers were able to share AI-based patterns and antipatterns and explain how they intersect with software architecture. Our December 9 event will look at enterprise architecture and how architects can navigate the impact of AI on systems, processes, and governance. (Registration is still open—save your seat.) As these events show, AI has progressed from being something architects might have to consider to something that is now essential to their work.

We’re seeing successful AI-enhanced architectures using event-driven models, enabling AI agents to act on incoming triggers rather than fixed prompts. This means it’s more important than ever to understand event-driven architecture concepts and trade-offs. In 2026, topics that align with evolving architectures (evolutionary architectures, fitness functions) will also become more important as architects look to find ways to modernize existing systems for AI without derailing them. AI-native architectures will also bring new considerations and patterns for system design next year, as will the trend toward agentic AI.

As was the case for their engineer coworkers, architects still have to know the basics: when to add an agent or a microservice, how to consider cost, how to define boundaries, and how to act on the knowledge they already have. They also need to understand how an AI element relates to other parts of their system: What are the inputs and outputs? And how can they measure performance, scalability, cost, and other cross-functional requirements?

Companies will continue to decentralize responsibilities across different functions this year, and AI brings new sets of trade-offs to be considered. It’s true that regulated industries remain understandably wary of granting access to their systems. They’re rolling out AI more carefully with greater guardrails and governance, but they are still rolling it out. So there’s never been a better time to understand the foundations of software architecture. It will prepare you for the complexity on the horizon.

Strong Foundations Matter

AI has changed the way software is built, but it hasn’t changed what makes good software. As we enter 2026, the most important developer and architecture skills won’t be defined by the tool you know. They’ll be defined by how effectively you apply judgment, communicate intent, and handle complexity when working with (and sometimes against) intelligent assistants and agents. AI rewards strong engineering; it doesn’t replace it. It’s an exciting time to be involved.

Join us at the Software Architecture Superstream on December 9 to learn how to better navigate the impact of AI on systems, processes, and governance. Over four hours, host Neal Ford and our lineup of experts including Metro Bank’s Anjali Jain and Philip O’Shaughnessy, Vercel’s Dom Sipowicz, Intel’s Brian Rogers, Microsoft’s Ron Abellera, and Equal Experts’ Lewis Crawford will share their hard-won insights about building adaptive, AI-ready architectures that support continuous innovation, ensure governance and security, and align seamlessly with business goals.

O’Reilly members can register here. Not a member? Sign up for a 10-day free trial before the event to attend—and explore all the other resources on O’Reilly.