AI can enhance programming experiences for a diverse set of programmers: from professional developers and data scientists (proficient programmers) who need help in software engineering and data wrangling, all the way to spreadsheet users (low-code programmers) who need help in authoring formulas, and students (novice programmers) who seek hints when stuck with their programming homework. To communicate their need to AI, users can express their intent explicitly—as input-output examples or natural-language specification—or implicitly—where they encounter a bug (and expect AI to suggest a fix), or simply allow AI to observe their last few lines of code or edits (to have it suggest the next steps).

The task of synthesizing an intended program snippet from the user’s intent is both a search and a ranking problem. Search is required to discover candidate programs that correspond to the (often ambiguous) intent, and ranking is required to pick the best program from multiple plausible alternatives. This creates a fertile playground for combining symbolic-reasoning techniques, which model the semantics of programming operators, and machine-learning techniques, which can model human preferences in programming. Recent advances in large language models like Codex offer further promise to advance such neuro-symbolic techniques.

Finally, a few critical requirements in AI-assisted programming are usability, precision, and trust; and they create opportunities for innovative user experiences and interactivity paradigms. In this talk, I will explain these concepts using some existing successes, including the Flash Fill feature in Excel, Data Connectors in PowerQuery, and IntelliCode/CoPilot in Visual Studio. I will also describe several new opportunities in AI-assisted programming, which can drive the next set of foundational neuro-symbolic advances.

Sumit Gulwani is a computer scientist seeking connections: between ideas, between research & practice, and with people with varied roles. He is the inventor of many intent-understanding technologies including the popular Flash Fill feature in Excel. He founded the PROSE research and engineering team at Microsoft that develops APIs for program synthesis and has incorporated them into various products including Office, Visual Studio, SQL, PowerQuery, and Powershell. He has co-authored 10 award winning papers and a total of 125+ peer-reviewed papers across multiple computer science areas, delivered 50+ keynotes and invited talks at various forums, and authored 65+ patent applications. He is a recipient of the ACM SIGPLAN Robin Milner Young Researcher Award (for pioneering contributions to program synthesis and intelligent tutoring systems), ACM SIGPLAN Outstanding Doctoral Dissertation Award, and the President’s Gold Medal from IIT Kanpur.