A catalyst fund for research software in the age of AI # Supporting the practices that make AI-assisted research software trustworthy. Grants for the people building, verifying, and teaching research software, and for the norms, tools, methods, and training the community needs to use generative AI well. [Sign up to be notified →][1] [Read the guidelines](/apply/) ## Exploratory grants At a glance * **Award**: up to $50,000 * **Duration**: 3–6 months * **Deadline**: late October 2026 * **Eligibility**: Worldwide What this fund supports ## Two tracks, one year, community-set priorities. Track 01 Coming soon ### Catalyst Exploratory Fund Small, fast grants for work that is ready to begin: writing sprints, tool-building sessions, conference workshops, communities of practice. * **Award**: up to $50,000 * **Duration**: 3–6 months * **Total available**: to be confirmed * **Deadline**: late October 2026 Track 02 Planned ### Catalyst Impact Fund Larger, longer awards for work with community-wide reach: building shared tools and infrastructure, studying how practice is changing, delivering training at scale. * **Award**: up to $200k * **Duration**: 9–12 months * **Total available**: to be confirmed * **Opens**: late 2026 / early 2027 What a grant might look like ## Examples, not categories. 1. Agentic verification tools that scaffold software testing and review ~$50k 2. Agent workflows that take on routine maintenance: issue triage, dependency updates, release chores ~$30k 3. A public, searchable collection of case studies from real AI-assisted projects ~$25k 4. A writing sprint to produce a costs-and-benefits framework ~$20k 5. A playbook for research team leaders navigating AI adoption ~$15k ### The common requirement Everything funded here should leave something others can use: a tool, a curriculum, a dataset, a document, a report of what happened. Illustrative, not prescriptive. [More on what we fund ](/what-we-fund/) ## Why this fund exists AI-assisted coding can bypass two checks research software has long relied on: the engineering judgment a person acquires through training or experience, and the understanding they build by writing the code themselves. Adoption is moving quickly, and the practices for using these tools well are still taking shape. This fund supports the work of developing them. 1. Used with care, these tools can improve software quality; used without it, they can erode it. The evidence on how this is playing out is still emerging. 2. When code and tests are both generated, validation risks becoming circular. 3. Teams and institutions are making adoption decisions with few shared frameworks to draw on. 4. Training and access to capable tools remain uneven across institutions and regions. 5. The decisions and reasoning behind generated code are often not recorded, which makes results harder to reproduce. [More on why this fund exists →](/why/) ## What this fund supports The range of potential activities this fund could support is broad, and many individuals and groups have already been discussing what needs working on. The clearest example so far is a workshop in Edinburgh in March 2026, which produced forty-six candidate activities across nine working groups, with two published documents setting out the thinking behind them. Feel free to use these for inspiration (or not). What counts is that you propose the work you believe in. [ Edinburgh workshop report · May 2026 Research Software Engineering in the Age of Generative AI: Building a Community Vision Forty-six candidate activities across nine working groups, ranked by impact and effort. Read it → ][2] [ Vision and principles · May 2026 Research Software in an Age of AI-Assisted Development: Reflections from Edinburgh The community principles the workshop was built on, and the risks it named. Read it → ][3] [ Community position statement · 2025 Generative AI in the RSE Workplace ADSA and US-RSE, drawn from conversations with more than 200 research software engineers. Read it → ][4] Good proposals may cut across several themes. Just tell us why the work matters and who it helps. ## Unsure whether an idea fits? Questions about scope, budget, or eligibility are welcome before you write anything. [Read the frequently asked questions](/faq/), or email the programme. [Email the programme ](mailto:contact@researchsoftwarecatalyst.fund) For prospective funders ## Join the fund. Interested in supporting trustworthy AI-assisted research software? We welcome conversations with prospective funders. Tell us a little about yourself or your organisation and what you would like to support. [Discuss joining the fund ](mailto:contact@researchsoftwarecatalyst.fund?subject=Joining%20the%20Catalyst%20Fund) [1]: https://docs.google.com/forms/d/e/1FAIpQLSdXRGZoXbOI-vz2LrqkIs06icDaFl_hlSDYa27AouKWeinb8Q/viewform [2]: https://doi.org/10.5281/zenodo.20320884 [3]: https://doi.org/10.5281/zenodo.20321134 [4]: https://github.com/Academic-Data-Science-Alliance/rse-ai-position-statement/blob/main/RSE-AI-Final_Statement.md STATUS: Announced. Applications open soon [View this page on the website](/)