As this year comes to a close, many experts have begun to look ahead to next year. Here are several predictions for trends in software development in 2026.
Bennie Grant, COO of Percona
The open source community continues the fight against restrictive relicensing
It’s unclear if or when another open source company will change its license, but what’s become abundantly clear is how the community will react. Every time a company attempts to impose restrictions, developers and enterprises respond with innovation and collective action. Moving forward, the community will continue to create alternatives, influence licensing decisions, and ensure that openness and freedom remain the defining principles of the ecosystem. Transparency isn’t just a standard; it’s the bedrock of open source.
Gloria Ramchandani, SVP of product at Copado
Lines for dev roles will blur
By 2026, the boundaries between traditional tech roles will blur. The days of rigid titles like “Developer” or “UX Designer” are giving way to hybrid roles that blend disciplines, bridging technical, analytical, and strategic skill sets. These blended roles will be the glue connecting business intent with technical execution. Job descriptions will focus less on specialization and more on adaptability, integration, and creative problem solving. As DevOps practices mature, the ecosystem needs roles that bridge DevOps and product, professionals who understand not just how to deploy, but why they’re deploying and how it impacts the broader business objectives.
Cameron von Orman, chief strategy officer and GM of Automotive Solutions at Planview
RIP Agile, hello product-oriented transformation
2026 is the year that agile transformations cease to exist – and for good reason! In its place, organizations will turn to hybrid, flexible, and modern ways of working. The prophecies of agile and output-optimization will increasingly be substituted for product-oriented operating models focused on tangible outcomes.
Itzik Levy, CEO of vcita
The end of the disjointed tech stack
“App fatigue” is a challenge for most businesses, with a majority of SMBs using 6+ core apps while 91% prefer an all-in-one solution. Enterprise service providers including telcos, banks, and payment processors will stop supporting fragmented, Ã la carte app ecosystems. In 2026 they will shift from providing a variety of individual apps to offering a single, AI-powered Unified Business OS, integrating business workflows like lead capture, scheduling, payments, and billing.
Steve Fenton, director of DevRel at Octopus Deploy
Platform budgets will come under pressure
This will intensify for teams that haven’t tracked their platform’s impact and for organizations that are accustomed to delivering projects rather than committing to long-term product development. When technology leaders don’t see a competitive benefit to the platform, they are likely to start reallocating platform team members to other areas. Development teams will be left stranded on a platform that may not be able to respond to their ongoing needs.
Dr. Marelene Wolfgruber, Document AI lead and computational linguist at ABBYY
Human judgment becomes the real engineering superpower
By 2026, autonomous agents and AI-driven workflows will take over most repetitive tasks. What’s left for humans—especially developers—is the work that requires judgment, context, and strategic thinking.
As AI handles boilerplate code, testing, and routine implementation, engineers will shift toward system architecture, constraint design, debugging emergent AI behavior, and translating ambiguous business goals into technical reality. The developers who stand out will be those who challenge assumptions, think across system boundaries, and understand why a solution matters—not just how to build it.
Critical thinking will be central in every human–AI loop: legal teams validating anomalies, compliance teams assessing flagged risks, and developers investigating odd model outputs, tightening prompts, and designing safe fallback logic.
Automation will scale the work. Human insight will keep it accurate, trustworthy, and aligned. In an AI-saturated world, deep thinking—not raw coding speed—becomes the core developer advantage.
Ben Potter, VP of product at Coder
Developer platform teams must take on AI governance and enablement
As AI coding tools shift from experiments to production workloads, platform engineering teams will become the primary stewards of AI in software development. Just as these teams already standardize tooling and infrastructure, they’ll now make AI tools both secure and productive at scale.
These teams will define and enforce AI policies, setting boundaries for agent access, approved models, and data flows. They’ll provision secure AI infrastructure, creating compliant environments where humans and agents work safely within corporate guardrails. They’ll enable golden paths by pre-configuring approved AI tools, MCP servers, and authentication in managed workspaces. They’ll monitor usage and costs, tracking productivity gains and identifying where AI adds value versus risk. And they’ll maintain visibility, ensuring every AI interaction is logged, traceable, and auditable.
The same teams that built self-service infrastructure for humans will now extend that mission to AI agents. While some may label it as “AgentOps,” it isn’t a separate discipline. It’s platform engineering evolving to meet the next wave of software development.
Karen Cohen, VP of product management at Apiiro
AI coding assistants will only replace portions of traditional coding work when they can hold and enforce full architectural and business context – not just syntax
That means understanding an organization’s system architecture, data flows, localization, privacy/compliance requirements, security policies, coding standards, and writing code that conforms to all of it. We’ll see more companies train agents on their own codebases and connect them to production/runtime context and business metadata. When those pieces are in place, agents can reliably take over menial and junior tasks like scaffolding and standards-based fixes, while humans focus on architecture, domain intent, and policy. In other words, agents won’t replace developers wholesale; they’ll replace tasks. The people who deeply understand systems – architecture, data, and constraints – will direct and govern the agents, and the agents will do more of the typing once they can consistently produce production-grade, policy-compliant code.
Shannon Mason, chief strategy officer at Tempo Software
Development teams will break the cycle of unnecessary complexity
In 2026, software teams will begin challenging the rising complexity of their own development environments, shifting from simply executing work to questioning why that work exists in the first place. After years of accumulating tools, rituals, and dependencies, developers will increasingly pause to ask whether a feature, deadline, or workflow actually warrants the effort. Strategic portfolio management (SPM) – born from the chaos of large, interdependent software portfolios – will evolve into a practical way for engineering organizations to reconnect strategic intent with the reality of shipping code. Instead of massive transformations, teams will adopt SPM practices in targeted, incremental ways that help them see capacity, surface bottlenecks, and make smarter tradeoffs. The software teams that get ahead will be the ones that empower developers to influence not just how code gets delivered, but which work deserves to be built at all.
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