AI Is Writing More Code. Releases Haven't Kept Up
Blog post from Harness
The "State of AI-Driven Software Releases 2026" report highlights how AI coding tools have accelerated the pace of code production but reveals a lag in the processes needed to safely release that code into production. The report, based on feedback from over 500,000 engineers, identifies code review as a significant bottleneck, with 57% of organizations still requiring human intervention for AI-generated code, thus slowing down the release process. It emphasizes the necessity of adopting progressive delivery practices like feature flags to decouple deployment from release and mitigate risks through controlled exposure. Additionally, the report points out that only half of the organizations have implemented specific guardrails for AI-generated code, indicating a gap in adapting traditional SDLC rigor to AI-driven development. While there is an uptick in experimentation facilitated by AI tools, the lack of adequate metrics to measure the impact of these tools is a challenge, with only 29% of organizations evaluating their effect. The report concludes that to harness AI velocity effectively, teams need to integrate progressive delivery, automated guardrails, and connect experimentation with actionable insights, ensuring AI's potential does not compromise software quality and safety.
No tracked trend matches for this post yet.
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.