In 2025 AI reshaped how groups suppose, construct, and ship software program. We’re now at some extent the place “AI coding assistants have rapidly moved from novelty to necessity [with] as much as 90% of software program engineers us[ing] some sort of AI for coding,” Addy Osmani writes. That’s a really completely different world to the one we had been in 12 months in the past. As we stay up for 2026, listed here are three key traits now we have seen driving change and the way we predict builders and designers can put together for what’s forward.
Evolving Coding Workflows
New AI instruments modified coding workflows in 2025, enabling builders to put in writing and work with code quicker than ever earlier than. This doesn’t imply AI is changing builders. It’s opening up new frontiers to be explored and expertise to be mastered, one thing we explored at our first AI Codecon in Could.
AI instruments within the IDE and on the command line have revived the controversy in regards to the IDE’s future, echoing previous arguments (e.g., VS Code versus Vim). It’s extra helpful to give attention to the instruments’ function. As Kent Beck and Tim O’Reilly mentioned in November, builders are in the end chargeable for the code their chosen AI software produces. We all know that LLMs “actively reward present prime tier software program engineering practices” and “amplify present experience,” as Simon Willison has identified. And a superb coder will “consider” questions that AI doesn’t. Does it actually matter which software is used?
The vital transferable ability for working with any of those instruments is knowing how one can talk successfully with the underlying mannequin. AI instruments generate higher code in the event that they’re given all of the related background on a challenge. Managing what the AI is aware of about your challenge (context engineering) and speaking it (immediate engineering) are going to be key to doing good work.
The core expertise for working successfully with code received’t change within the face of AI. Understanding code assessment, design patterns, debugging, testing, and documentation and making use of these to the work you do with AI instruments would be the differential.
The Rise of Agentic AI
With the rise of brokers and Mannequin Context Protocol (MCP) within the second half of 2025, builders gained the flexibility to make use of AI not simply as a pair programmer however as a complete group of builders. The audio system at our Coding for the Agentic World stay AI Codecon occasion in September 2025 explored new instruments, workflows, and hacks which might be shaping this rising self-discipline of agentic AI.
Software program engineers aren’t simply working with single coding brokers. They’re constructing and deploying their very own customized brokers, typically inside advanced setups involving multi-agent eventualities, groups of coding brokers, and agent swarms. This shift from conducting AI to orchestrating AI elevates the significance of really understanding how good software program is constructed and maintained.
We all know that AI generates higher code with context, and that is additionally true of brokers. As with coding workflows, this implies understanding context engineering is important. Nevertheless, the differential for senior engineers in 2026 shall be how properly they apply intermediate expertise resembling product pondering, superior testing, system design, and structure to their work with agentic programs.
AI and Software program Structure
We started 2025 with our January Superstream, Software program Structure within the Age of AI, the place speaker Rebecca Parsons explored the architectural implications of AI, dryly noting that “given the tempo of change, this might be outdated by Friday.” By the point of our Superstream in August, issues had solidified a bit of extra and our audio system had been in a position to share AI-based patterns and antipatterns and clarify how they intersect with software program structure. Our December 9 occasion will have a look at enterprise structure and the way architects can navigate the impression of AI on programs, processes, and governance. (Registration continues to be open—save your seat.) As these occasions present, AI has progressed from being one thing architects may need to contemplate to one thing that’s now important to their work.
We’re seeing profitable AI-enhanced architectures utilizing event-driven fashions, enabling AI brokers to behave on incoming triggers fairly than fastened prompts. This implies it’s extra vital than ever to know event-driven structure ideas and trade-offs. In 2026, subjects that align with evolving architectures (evolutionary architectures, health capabilities) may even grow to be extra vital as architects look to seek out methods to modernize present programs for AI with out derailing them. AI-native architectures may even deliver new issues and patterns for system design subsequent 12 months, as will the pattern towards agentic AI.
As was the case for his or her engineer coworkers, architects nonetheless should know the fundamentals: when so as to add an agent or a microservice, how one can take into account value, how one can outline boundaries, and how one can act on the information they have already got. As Thomas Betts, Sarah Wells, Eran Stiller, and Daniel Bryant word on InfoQ, in addition they “nee[d] to know how an AI component pertains to different elements of their system: What are the inputs and outputs? How can they measure efficiency, scalability, value, and different cross-functional necessities?”
Corporations will proceed to decentralize duties throughout completely different capabilities this 12 months, and AI brings new units of trade-offs to be thought-about. It’s true that regulated industries stay understandably cautious of granting entry to their programs. They’re rolling out AI extra rigorously with higher guardrails and governance, however they are nonetheless rolling it out. So there’s by no means been a greater time to know the foundations of software program structure. It’ll put together you for the complexity on the horizon.
Robust Foundations Matter
AI has modified the best way software program is constructed, however it hasn’t modified what makes good software program. As we enter 2026, crucial developer and structure expertise received’t be outlined by the software you understand. They’ll be outlined by how successfully you apply judgment, talk intent, and deal with complexity when working with (and typically towards) clever assistants and brokers. AI rewards robust engineering; it doesn’t substitute it. It’s an thrilling time to be concerned.
Be a part of us on the Software program Structure Superstream on December 9 to discover ways to higher navigate the impression of AI on programs, processes, and governance. Over 4 hours, host Neal Ford and our lineup of specialists together with Metro Financial institution’s Anjali Jain and Philip O’Shaughnessy, Vercel’s Dom Sipowicz, Intel’s Brian Rogers, Microsoft’s Ron Abellera, and Equal Consultants’ Lewis Crawford will share their hard-won insights about constructing adaptive, AI-ready architectures that help steady innovation, guarantee governance and safety, and align seamlessly with enterprise objectives.
O’Reilly members can register right here. Not a member? Join a 10-day free trial earlier than the occasion to attend—and discover all the opposite sources on O’Reilly.
