What's changing in 2026
Last updated: March 2026
Quarterly analysis of what matters in software delivery. Industry benchmarks, emerging patterns, and practical takeaways for CTOs, CFOs, and CISOs navigating the shift from AI co-pilot tools to autonomous delivery teams.
trend 01
From Vibe coding to Agentic Engineering
$32B market by 2034
What started as ad-hoc prompting — sometimes called vibe coding — is maturing into governed, multi-step workflows. Industry analysts project the AI-powered software delivery market will reach $32 billion by 2034, driven by the shift from autocomplete-style assistants to autonomous systems that plan, execute, and validate tasks.
The differentiator is governance. Basic assistants need constant direction. The next generation operates under defined guardrails with human approval at critical gates — delivering productivity gains without sacrificing oversight.
trend 02
Agentic tooling is converging on open standards
Weeks → hours setup time
A wave of open standards is reshaping how AI agents connect to enterprise systems. Connectivity protocols like MCP handle tool-to-system integration. Orchestration frameworks coordinate multi-step agent workflows. Observability platforms like Langfuse trace every decision for audit and compliance.
We built our delivery stack on these open standards rather than proprietary integrations. Setup times shrink from weeks to hours, agents are swappable without rework, and every action is logged and auditable.
trend 03
AI is reshaping delivery economics
40 hours → 4 hours per task
AI agents compress delivery timelines. A task that once took 40 hours can now take 4 with agent assistance. This shift forces a rethink of how software projects are scoped, priced, and measured.
trend 04
Technique mastery outweighs tool access
Tools are table stakes
Access to AI tools is table stakes — Claude, GPT, Llama, and dozens of open models are available to everyone. The real advantage lies in knowing which model fits the task, how to validate its output, and when not to use AI at all.
We run company-wide programmes that go beyond tool access. Our engineers build and share replayable techniques: prompt strategies, validation layers, model selection criteria for cost and quality, and structured experimentation across security and privacy dimensions.
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