Can AI code? Study maps the roadblocks to autonomous software engineering (www.csail.mit.edu)

A new study from MIT CSAIL and collaborating institutions offers a comprehensive assessment of the current challenges blocking AI from fully automating software engineering beyond simple code generation. While recent advancements have enabled AI to handle smaller programming tasks, the research highlights that real-world software engineering involves much more complex activities such as large-scale refactoring, legacy system migration, concurrency bug detection, continuous testing, and performance optimization—areas where AI still struggles. The paper critiques popular narratives that oversimplify coding as merely writing small functions and stresses the need for AI tools to understand broader engineering contexts and workflows. Key technical hurdles include inadequate benchmarks that fail to measure AI performance on large, interconnected codebases and complex tasks, along with poor human-AI communication channels that limit developers’ ability to guide and verify AI-generated code. Current models frequently hallucinate plausible but incorrect code, especially when faced with proprietary or specialized codebases that differ significantly from public training data. The researchers call for community-wide efforts to build richer datasets capturing developer workflows, develop comprehensive evaluation metrics focusing on practical aspects like refactor quality and bug-fix longevity, and design AI systems that transparently express uncertainty and seek human input for clarification. By addressing these multifaceted roadblocks, the field can gradually move AI from a mere autocomplete assistant toward a true engineering partner, capable of alleviating the tedious and error-prone aspects of software development. This shift holds significant implications for the AI/ML community, promising to boost productivity across industries dependent on complex software, freeing human engineers to focus on higher-level design, creativity, and ethical considerations.