2026年にソフトウェアがどのように構築されるかを定義する8つのトレンド

Eight trends defining how software gets built in 2026

How is AI changing the way software gets built—and what should engineering leaders expect in 2026? We analyzed the patterns emerging across the industry.

CategoryAgentsClaude Code

ProductClaude Code

DateJanuary 21, 2026

Reading time5min

ShareCopy linkhttps://claude.com/blog/eight-trends-defining-how-software-gets-built-in-2026

Coding agents are now collaborators.

In 2025, engineering teams discovered AI could handle entire implementation workflows: writing tests, debugging failures, navigating complex codebases. In 2026, we predict these capabilities will expand significantly.

Our new report identifies eight trends we predict will define agentic coding this year, organized into three categories: foundation trends that change how development happens, capability trends expanding what agents accomplish, and impact trends affecting business outcomes.

The organizations pulling ahead aren't removing engineers from the loop, they're making engineer expertise count where it matters most.

What we're seeing

The software development lifecycle is undergoing one of its most significant changes since the graphical user interface. Engineers are shifting from writing code to coordinating agents that write code, focusing their own expertise on architecture, system design, and strategic decisions.

A critical nuance has emerged from studying how developers actually work with AI: this transformation relies on active collaboration.

Research from our Societal Impacts team reveals that while developers use AI in roughly 60% of their work, they report being able to "fully delegate" only 0-20% of tasks. AI serves as a constant collaborator, but using it effectively requires supervision, validation, and human judgment.

What this looks like in practice

Organizations across industries are putting these patterns into practice, balancing agent autonomy with human oversight to ship faster without sacrificing quality.

Rakuten engineers tested Claude Code on a complex technical task: implementing an activation vector extraction method in vLLM, a 12.5-million-line codebase. Claude Code finished the job in seven hours of autonomous work, achieving 99.9% numerical accuracy.

TELUS teams created over 13,000 custom AI solutions while shipping engineering code 30% faster, saving over 500,000 hours total.

Zapier achieved 89% AI adoption across their entire organization with 800+ agents deployed internally.

The path forward

For organizations planning their 2026 priorities, four areas demand immediate attention: mastering multi-agent coordination, scaling human-agent oversight through AI-automated review, extending agentic coding beyond engineering teams, and embedding security architecture from the earliest stages. Organizations that treat agentic coding as a strategic priority will define what becomes possible.

Read the full 2026 Agentic Coding Trends Report here.

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