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Behind the code: How developers work in 2025 - Help Net Security
How are developers working in 2025? Docker surveyed over 4,500 people to find out, and the answers are a mix of progress and ongoing pain points. AI is gaining ground but still unevenly used. Security is now baked into everyday workflows. Most devs have left local setups behind in favor of cloud environments. And while tools are improving, coordination, planning, and time estimation still slow teams down. … ### Productivity and inner-loop friction Developers continue to struggle with coordination tasks. It’s hard to estimate time, plan work, review pull requests, and debug production issues. These are the top blockers across roles. Time estimation is the biggest challenge, flagged by 31% of IT professionals. Planning and pull request reviews are also common pain points.
Related Pain Points5件
Data quality and preparation for AI/ML applications
726% of AI builders lack confidence in dataset preparation and trustworthiness of their data. This upstream bottleneck cascades into time-to-delivery delays, poor model performance, and suboptimal user experience.
Time estimation across development workflows
6Estimating task duration is the most consistent pain point across all developer roles (31% of IT professionals, 42% of experienced developers, 49% of decision-makers). This affects sprint planning and project delivery prediction.
Non-local development environment complexity
664% of developers now use non-local cloud environments as primary setup, but this introduces coordination and debugging challenges that weren't present in local-only workflows, requiring new tooling and practices.
Pull request review bottlenecks
6Pull request review is flagged as a top workflow blocker (25% of developers), slowing team coordination and delaying merges. No structured tooling has effectively reduced this friction point.
Task planning and work coordination
526% of developers struggle with task planning and resource allocation. Container users specifically need better tools for task planning (18%), yet existing solutions don't adequately address this need.