TL;DR: The first round of the Generator Residency went very well.
Our residents created and ran several large-scale fieldbuilding, talent infrastructure, and operational projects that have already had important impacts on the ecosystem.
Six weeks after the program ended, 12 of our 27 residents have been hired to full-time roles at core AI safety orgs, and most have received several offers.
We wrote this because we noticed that organizations across the ecosystem were struggling to hire for key non-research roles. While these roles were often getting many applicants, candidates didn’t meet basic requirements.
The original memo we wrote (that became the post above) inspired us to create the Generator Residency as an intervention to support more generalists trying to break into AI safety.
The program concluded six weeks ago, and this post details the successes we’ve seen from the first round of Generator, which have inspired us to launch a second round of the program.
Programs and projects from Generator
Programs residents started:
Talent Commons, a cross-organization talent directory now run as a Kairos product, which will include data from participants in SPAR, Pathfinder, GCP, Generator, BlueDot courses, Astra and MATS,. Constellation, BlueDot, and MATS have already signed on.
Praxis, a retreat bringing top national debaters into contact with AI safety: about 40 debaters, including 20 national champions.
Lateral, a three-day workshop bringing mid-career professionals to Berkeley to work with AI safety professionals: 705 applications for about 35 seats, and a likelihood to recommend of 9.7 out of 10 from attendees.
Gen Stream, a one-week program in London funded through Generator.
Longitude DC, an eight-day policy intensive for 15 early-to-mid-career technical AI safety professionals with more than 20 speakers, running October 6 to 13.
M3, an AI security matching fellowship, which raised $200k from BlueDot on top of Generator funding.
Residents working with mentors at established organizations contributed to:
Lab engagement through Nightingale and Constellation.
A one-week AI safety world-modeling bootcamp with 25 attendees covering ML fundamentals, futurism, and the technical case for alignment.
A workshop series on improving management within AI safety (interviews with more than 10 managers and three workshops).
AI safety founder support (meetings with 32 founders, with 6 given deeper support).
Support for mid-career operations people transitioning into AI safety (leading to hundreds of referrals across more than 50 roles).
A map of the work on AI character and model specs.
12 SPAR generalist projects that came out of the residency.
Resident Outcomes
Generator was designed as a path into full-time generalist roles in AI safety. Six weeks after the program ended, 12 of the 27 residents have been hired into full-time positions. Their employers include BlueDot Impact, Guidelight, Constellation, Kairos, METR, Eleos, CBAI, and CEA. In several of these cases, the hiring organization began working with the resident during Generator.
Of the residents who have not yet taken a full-time role, some are running programs that came out of the residency or AI safety university groups at Harvard, Princeton, MIT, and Stanford. Others have received offers, including from Coefficient Giving, Quorum, and ARENA, and are deciding between options. A few residents have been pitched by funders on turning their one-time project into a much larger, recurring program.
Below are a couple of selected testimonials from previous residents:
Additional testimonials and information are available on the Generator website.
Reflections
We stood Generator up in three months. It was the first multi-month in-person program Kairos had run. Most of what we learned was about what residents needed from us, and we think most of it applies to other programs that support people rather than research outputs.
Some key lessons we learned:
1. Candidate selection shaped the program more than anything else.
Candidate selection is, of course, an incredibly important part of any program. However, we were surprised by just how much of our planned programming changed based on the proactivity of our participants.
Residents discovered who the other residents were before the program started and created a group chat and had calls with each other. Once they arrived, they ran hikes, game nights, regular reflection sessions, and informal peer check-ins. When we asked what made them feel integrated, residents pointed to these resident-run activities far more often than anything we scheduled. In both our midway and final surveys, the most common answer to “what was your favorite part” was the other residents.
2. Residents' career goals strongly informed their preferences for projects and advisors.
The cohort included three broad groups:
University organizers looking for their first formal work experience
Early-career professionals looking for a final stepping stone into the field
Mid-career professionals looking for the context they needed to transition
Over time, we realized that, in addition to accommodating residents with different experience levels, we needed to accommodate residents with different intentions for how Generator could forward their career. Some residents strongly preferred to use the Generator residency to explore multiple roles, while others were using the residency to deliver a legible product that could help them make a career transition or get hired. Residents aiming to transition wanted advisors invested in their growth and career, not only in the project.
Based on feedback, we’ve decided to implement two tracks in our next residency. We plan to work with our residents from the start to determine what projects and tracks best suit their goals.
3. Our residents asked for the most support with project scoping, structured management, and navigating interpersonal conflict.
For many residents, their Generator project was the largest or most complex project they had ever planned. Moreover, their projects typically aimed to address large, poorly defined problems in the AI safety ecosystem, such as mid-career talent pipelines. Accordingly, they wanted support in determining the most ambitious, yet feasible project that could enable their vision.
Several early-career residents benefited from structured management, reporting that they grew from an advisor who had them estimate how long each planned task would take or a short written template before each check-in.
Co-leading a Generator project was quite similar to co-founding, which led to a lot of interpersonal work for some residents who had previously mostly worked independently. These residents benefitted from clear norms around sharing feedback.
4. We need to be more explicit that we're betting on people, not projects.
While many residents worked on impactful projects, the main focus of Generator was always on the people we chose to support. The projects matter, and many of them helped the field, but we mostly saw them as a way for residents to grow quickly into the generalists AI safety needs. We didn't say this clearly enough at the start, and many residents felt stressed about picking the single most impactful project.
When we asked them how the program changed their thinking, the most common answers were about learning field context, clarifying their career direction, and developing self-knowledge. Few people directly mentioned their project outcomes.
Generator 2.0
We’ve been really happy with the outcomes that we saw from the first round of Generator and, as a result, have decided to run a second round!
Applications for the winter 2027 Generator Residency open on October 12, 2026, and close at the end of the day on November 1, 2026, Anywhere on Earth. The program begins on January 18 and will run until April 9, 2027, with a possible 3-month extension.
Residents at Generator receive $8,500 per month and are funded for travel to and from Berkeley. Once they arrive in Berkeley, they work from Constellation, are paired with experienced advisors from the AI safety ecosystem, and are offered budgets to pursue their projects.
Applicants do not need to be U.S. citizens. For most international applicants, we can sponsor a J-1 visa for the program’s duration, though we cannot guarantee obtaining one. Additionally, we strongly recommend that international applicants apply early (ideally by October 26th) so we can meet deadlines for visa applications.
TL;DR: The first round of the Generator Residency went very well.
Our residents created and ran several large-scale fieldbuilding, talent infrastructure, and operational projects that have already had important impacts on the ecosystem.
Six weeks after the program ended, 12 of our 27 residents have been hired to full-time roles at core AI safety orgs, and most have received several offers.
Kairos and Constellation are running a second round from January to April 2027. Apply to the next round of the Generator Residency by November 1st.
Introduction
In April, we wrote AI Safety's Biggest Talent Gap Isn't Researchers. It's Generalists.
We wrote this because we noticed that organizations across the ecosystem were struggling to hire for key non-research roles. While these roles were often getting many applicants, candidates didn’t meet basic requirements.
The original memo we wrote (that became the post above) inspired us to create the Generator Residency as an intervention to support more generalists trying to break into AI safety.
The program concluded six weeks ago, and this post details the successes we’ve seen from the first round of Generator, which have inspired us to launch a second round of the program.
Programs and projects from Generator
Programs residents started:
Residents working with mentors at established organizations contributed to:
Other notable projects included:
Resident Outcomes
Generator was designed as a path into full-time generalist roles in AI safety. Six weeks after the program ended, 12 of the 27 residents have been hired into full-time positions. Their employers include BlueDot Impact, Guidelight, Constellation, Kairos, METR, Eleos, CBAI, and CEA. In several of these cases, the hiring organization began working with the resident during Generator.
Of the residents who have not yet taken a full-time role, some are running programs that came out of the residency or AI safety university groups at Harvard, Princeton, MIT, and Stanford. Others have received offers, including from Coefficient Giving, Quorum, and ARENA, and are deciding between options. A few residents have been pitched by funders on turning their one-time project into a much larger, recurring program.
Below are a couple of selected testimonials from previous residents:
Additional testimonials and information are available on the Generator website.
Reflections
We stood Generator up in three months. It was the first multi-month in-person program Kairos had run. Most of what we learned was about what residents needed from us, and we think most of it applies to other programs that support people rather than research outputs.
Some key lessons we learned:
1. Candidate selection shaped the program more than anything else.
Candidate selection is, of course, an incredibly important part of any program. However, we were surprised by just how much of our planned programming changed based on the proactivity of our participants.
Residents discovered who the other residents were before the program started and created a group chat and had calls with each other. Once they arrived, they ran hikes, game nights, regular reflection sessions, and informal peer check-ins. When we asked what made them feel integrated, residents pointed to these resident-run activities far more often than anything we scheduled. In both our midway and final surveys, the most common answer to “what was your favorite part” was the other residents.
2. Residents' career goals strongly informed their preferences for projects and advisors.
The cohort included three broad groups:
Over time, we realized that, in addition to accommodating residents with different experience levels, we needed to accommodate residents with different intentions for how Generator could forward their career. Some residents strongly preferred to use the Generator residency to explore multiple roles, while others were using the residency to deliver a legible product that could help them make a career transition or get hired. Residents aiming to transition wanted advisors invested in their growth and career, not only in the project.
Based on feedback, we’ve decided to implement two tracks in our next residency. We plan to work with our residents from the start to determine what projects and tracks best suit their goals.
3. Our residents asked for the most support with project scoping, structured management, and navigating interpersonal conflict.
For many residents, their Generator project was the largest or most complex project they had ever planned. Moreover, their projects typically aimed to address large, poorly defined problems in the AI safety ecosystem, such as mid-career talent pipelines. Accordingly, they wanted support in determining the most ambitious, yet feasible project that could enable their vision.
Several early-career residents benefited from structured management, reporting that they grew from an advisor who had them estimate how long each planned task would take or a short written template before each check-in.
Co-leading a Generator project was quite similar to co-founding, which led to a lot of interpersonal work for some residents who had previously mostly worked independently. These residents benefitted from clear norms around sharing feedback.
4. We need to be more explicit that we're betting on people, not projects.
While many residents worked on impactful projects, the main focus of Generator was always on the people we chose to support. The projects matter, and many of them helped the field, but we mostly saw them as a way for residents to grow quickly into the generalists AI safety needs. We didn't say this clearly enough at the start, and many residents felt stressed about picking the single most impactful project.
When we asked them how the program changed their thinking, the most common answers were about learning field context, clarifying their career direction, and developing self-knowledge. Few people directly mentioned their project outcomes.
Generator 2.0
We’ve been really happy with the outcomes that we saw from the first round of Generator and, as a result, have decided to run a second round!
Applications for the winter 2027 Generator Residency open on October 12, 2026, and close at the end of the day on November 1, 2026, Anywhere on Earth. The program begins on January 18 and will run until April 9, 2027, with a possible 3-month extension.
Learn more and apply here
Residents at Generator receive $8,500 per month and are funded for travel to and from Berkeley. Once they arrive in Berkeley, they work from Constellation, are paired with experienced advisors from the AI safety ecosystem, and are offered budgets to pursue their projects.
Applicants do not need to be U.S. citizens. For most international applicants, we can sponsor a J-1 visa for the program’s duration, though we cannot guarantee obtaining one. Additionally, we strongly recommend that international applicants apply early (ideally by October 26th) so we can meet deadlines for visa applications.