AI beats us at coding. But it’s also better and faster at nearly everything else: planning, QA, working with all The post How to delegate 40% of tickets to AI appeared first on The New Stack .
Advances in AI models and agentic frameworks are making automated task execution in software development increasingly viable, shifting from theoretical to practical application.
This development indicates a significant productivity leverage point for software engineering teams, potentially redefining personnel resource allocation and development cycles.
Software development roles are less about manual coding and more about AI supervision and orchestration, leading to substantial gains in efficiency and speed.
- · AI software vendors
- · Early adopter technology companies
- · Software engineers proficient in AI orchestration
- · Managed service providers
- · Entry-level software developers
- · Traditional software development consultancies
- · Companies slow to adopt AI tools
Significant portions of routine software development tasks are automated, expediting project timelines.
Demand for AI-native software engineering talent increases, while demand for traditional coding roles decreases, leading to workforce retraining pressures.
The overall cost of software development could drop dramatically, enabling more ambitious and complex projects to be undertaken with fewer resources.
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