Agentic AI for Software Teams: Building the Next Horizon of SWE Agents for Society with Atlassian

Primary supervisor

Kla Tantithamthavorn

Co-supervisors

  • Atlassian

Research area

Vision and Language

🎯 Research Vision

The next generation of software engineering tools will move beyond autocomplete and static code generation toward autonomous, agentic systems — AI developers capable of planning, reasoning, and improving software iteratively. This project explores the development of agentic AI systems that act as intelligent collaborators: understanding project goals, decomposing problems, writing and testing code, and learning from feedback.

🔍 Research Objectives

  1. Design an Agentic SWE Framework

    • Model an AI system that combines reasoning, planning, and self-correction for software engineering tasks.

    • Integrate components such as task decomposition, code synthesis, test generation, and evaluation.

  2. Evaluate Agentic Behavior in Code Generation

    • Assess how agentic systems (e.g., those using LLMs with reflection or reinforcement loops) compare to static code generators.

    • Metrics: code quality, correctness, maintainability, and speed of convergence.

  3. Develop Benchmark Tasks for AI Developers

    • Curate open-source software tasks (bug fixing, refactoring, unit test creation) for empirical evaluation.

    • Measure human-AI collaboration efficiency.

  4. Investigate Trust and Explainability

    • Explore how developers interact with autonomous AI coders.

    • Build explainability modules to visualize agent reasoning and decisions.

🧪 Expected Outcomes

  • Prototype of an agentic code generation framework capable of self-directed code improvement.

  • Empirical evidence of productivity gains and trust challenges.

  • Publications in venues like ASE, ICSE, or ESEC/FSE (for advanced master’s work).

đź”® Future Impact

This research contributes to the emerging field of Agentic Software Engineering (Agentic SWE) — redefining what it means to “develop software.” Students will gain exposure to autonomous AI systems, software intelligence architectures, and human-in-the-loop development — core technologies for the next decade of AI-powered engineering.

This is a collaborative research project with Atlassian. Check out some recent work:

- https://www.atlassian.com/software/rovo-dev

- https://www.atlassian.com/blog/atlassian-engineering/hula-blog-autodev-paper-human-in-the-loop-software-development-agents

- https://arxiv.org/abs/2411.12924

Learn more about minimum entry requirements.

Primary supervisor