Hi Vasco,
Thanks for the question, happy to answer.
The CEAs were built with different levels of involvement from the fellows, our team, and LLM support. Claude being the main supporting tool.
The template and overall structure of the CEAs were developed outside of Claude, based on our methodology (and heavily comparing different templates from different organizations).
As for the content of the models:
Once the models were completed, we held review sessions with each team to revisit key assumptions and refine the models. For example, asking whether certain implied assumptions made sense for the real world, and because the fellows themselves know their context and intervention details, many things were changed. However, the models are far from being final, but the template structure was created for them to be used as a planning tool (not only a fundraising tool), so teams will definitely adjust them with time and with their internal evidence, once available.
In full honesty, building the models was the part of the incubation process that scared me the most, so I’m very glad Claude appeared at the right time, and it also made me more confident in that using templates like this is a way to make CEAs more accessible: once organizations have clear cost structures (and many orgs have detailed budgets), assumptions, and external evidence, building a first model becomes much more feasible. It’s not perfect, but it’s a strong starting point.
Very happy to share the template or walk through it together, we’re very keen to improve it and learn further with feedback.
Hi Gabrielle,
Thank you for your thoughtful reflection.
Regarding the research question: while fellows are making the decisions, they are doing so within a fairly structured methodology (we provide the tools, templates, and step-by-step process). For example, problem selection is guided by specific thresholds (e.g. Only selecting problems that are affecting >600k people or ~6M animals in the first country of implementation), alongside other criteria like depth, breadth, and trajectory of the problem in the region.
Similarly, intervention selection is constrained by requirements such as being evidence-based (e.g. supported by RCTs, meta-analyses, or strong evidence equivalents for animal welfare), proven to be cost-effective in other contexts, and feasible to adapt locally. We also have a (small) research support team helping throughout the process. And of course, we have used the help of certain LLMs (like Elicit and Perplexity).
Additionally, fellows go through theoretical training (e.g. M&E principles) to guide their reasoning, and we have the support from IPA Colombia, who provided lectures and office hours to review parts of the work.
We don’t think this replaces the depth of a trained researcher, but in a resource-constrained setting, it allows for reasonably rigorous, structured decision-making. It also has the advantage of making the reasoning process explicit so if something doesn’t work (as it sometimes happens in the real world, while implementing), fellows can revisit and iterate more effectively.
Always happy to receive feedback on how to improve things!
Hi Tony, thanks for the thoughtful questions!
Regarding Ambitious Impact/CEIP, we’ve definitely drawn inspiration from their model and have received direct mentoring from them throughout our implementation. They have been very generous with their knowledge and support! Some key differences:
Thanks for wanting to support! We are hosting a Meet the Founder session on April 9th to facilitate this; connections, mentorship, and feedback are exactly what we’re looking for. If you’d like to join, please fill out this short form (≈3 minutes), and we’ll share the meeting link and details: https://forms.gle/sb5bYBUihReiexJv8
It would be great to have you there!
As for the Laboratory of Social Entrepreneurship, we are a relatively new organization (~1 year), and this is our first cohort, but it builds on prior experience in the sector (M&E, program design, and implementation) and in the region.
Happy to share more if helpful, and thanks again for engaging!
Hi John,
Thanks for the comment and for flagging the issues.
Happy to talk if you would like more information!
Awesome! Will do, thank you!!!