London Interface for AI Safety (LIAISE)

London, UK

Liaise helps close the generalist talent gap in AI safety by helping motivated non‑technical people enter with fluency, alignment, and a trusted network.

Endorsed by+1

Liaise helps close the generalist talent gap in AI safety by helping motivated non‑technical people enter with fluency, alignment, and a trusted network.

Endorsed by+1

Project Details

We are currently running Liaise (https://liaiseai.xyz/) as a volunteer-driven project. It is a structured bridge for generalists entering AI safety. Most non-technical people analyse their fit in the space on the go, and it takes them months to understand where they can make the most impact. Liaise expedites this through bringing fluency (context), alignment and a network they can rely on early on so the move is more intentional and easier.
We recently organised the generalists mixer in central London - https://luma.com/3bc7capv

Over the next 6 months - We will be working on

Regular mixers and easy networking for generalists exploring their fit in London. The baseline is people with at least some previous work skills and who care about AI risk but don’t yet have fluency or a network. (organising an informal mixer in London on 16th July 2026 https://luma.com/3bc7capv)
Two generalist‑focused hackathons: One of the hackathons is currently WIP; a one-day hackathon with Frame fellowship in London (end of July 2026) to bring content creators and communicators in the space
Design and get feedback on the LI(ai)SE incubator fellowship: a short, cohort‑based programme where a small group of generalists get structured content, a scoped project, and support applying to roles or programmes or starting their own projects to help AI go well.

We currently have a team of 5 volunteers helping organise the work in London and have 3 advisors from EA and AI Safety adjacent organisations (currently working on making this official).

Right now I’m the lead for running the project (design, website, outreach, logistics, facilitation, comms), with a small set of advisors and core team volunteers along with AIS organisations offering mentoring, feedback, and occasional co‑hosting.

We are raising our first funding to cover ops (team+working) costs along with the costs of organising the outputs. The concrete outputs are:

- 2-3/per month low friction mixers and events for people to test their context and ecosystem understanding, (thematic and general mixers)

- at least one hackathon a month with real outputs produced, \

a 3-month documented fellowship pilot (including curriculum and example projects),

- and a small but growing group of generalists who can point to LI(ai)SE as part of how they became legible candidates for non‑technical AI safety roles.

Team's track:

Rohan, Co founder (https://robarad.my.canva.site/)

Ex policy and programs for Science & Tech office in Government/Prime Minister's Office, India
BlueDot Impact AGI Strategy & AI Governance courses
Arcadia Gov Fellowship
Raised rapid grant through BlueDot to run Liaise ops
Built Liaise's online presence of 2k+ on LinkedIn in 2 months

Look at our team profile here: https://liaiseai.xyz/

Theory of Impact

Li(ai)se reduces x‑risk from AI by fixing a specific bottleneck: the shortage of high context generalists in non‑technical AI safety roles (ops, comms, governance, policy‑ops, fieldbuilding). If we can reliably turn 'motivated, slightly lost generalist' into credible, well‑networked candidate with real work under their belt, AI safety orgs can hire and scale faster, and existing technical and policy work has a much better chance of being implemented well.

In practice, LI(ai)SE does three things: it gives people basic fluency in AI safety and governance, helps them ship a first concrete project (e.g. ops improvement, comms product, governance memo), and connects them with mentors and hiring managers who can vouch for them. That combination makes it more likely that they end up running evaluations, incident processes, fieldbuilding programmes, and governance projects at the orgs that matter.

Over time, having more of these people in the right places strengthens the institutional and operational “scaffolding” around advanced AI systems, which is critical for actually preventing and responding to catastrophic failures, not just talking about them. If LI(ai)SE succeeds, more aligned generalists end up in key non‑technical roles at AI safety orgs, which makes those orgs better at actually implementing safety, governance, and fieldbuilding work that reduces x‑risk from advanced AI.

People

Rohan Barad

Team Member

Funding Details

Start Date: -
End Date: -
Expected Duration: 1 year
Funding Raised to Date: -
Annual Budget: -
Monthly Burn Rate: -
Current Runway: -
Funding Goal: -
Funding Stage: Seeking first grant
Fiscal Sponsor: -

Track Record

What have we built:
\

Liaise slack community of 150+ active users looking to move into AI Safety space as generalists + 10 mentors from AIS fieldbuilding orgs - https://airtable.com/appwtUZEqcHCOky5k/pagQi8XRtWtgYDQuq/form
An in-person generalists mixer in central London with 30+ people from diverse backgrounds pivoting into AIS - https://luma.com/3bc7capv
LinkedIn presence: 2k+
3 core team members pivoting to AI Safety within the first month of joining the volunteer core team
CRM of high-impact professionals with 8+ years of experience and matching them with mentors and orgs
A WIP document of 'template for how to pivot into AI safety as a generalist'
Designing a hackathon with Frame Fellowship on content and communications for AI Safety
Building a database of who gets hired most often across top AI safety orgs, and what those people’s backgrounds look like. It’s a way to make the field easier to navigate for candidates and hiring teams

Grants Received– no grants recorded

Add grant

Funding Asks

grantmaking.ai Launch Round

Applied

Minimum

$25,000

Ideal

$150,000

What this ask is

I am currently running Liaise as a volunteer-driven project. It is a structured bridge for generalists entering AI safety. Most non-technical people analyse their fit in the space on the go, and it takes them months to understand where they can make the most impact. Liaise expedites this through bringing fluency (context), alignment and a network they can rely on early on so the move is more intentional and easier.

Over the next 6 months - I will be working on

Regular mixers and easy networking for generalists exploring their fit in London. The baseline is people with at least some previous work skills and who care about AI risk but don’t yet have fluency or a network. (organising an informal mixer in London on 16th July 2026)
One or two generalist‑focused hackathons - we are currently designing a one-day hackathon with Frame fellowship in London (end of July 2026) to bring content creators and communicators in the space
Design and get feedback on the LI(ai)SE incubator fellowship: a short, cohort‑based programme where a small group of generalists get structured content, a scoped project, and support applying to roles or programmes or starting their own projects to help AI go well.

We currently have a team of 5 people helping organise the work in London and have 3 advisors from EA and AI Safety adjacent organisations (currently working on making this official).

We are raising our first funding to cover ops (team+working) costs along with the costs of organising the outputs. The concrete outputs are:

- 2-3/per month low friction mixers and events for people to test their context and ecosystem understanding, (thematic and general mixers)

- at least one hackathon a month with real outputs produced,

a 3-month documented fellowship pilot (including curriculum and example projects),

- and a small but growing group of generalists who can point to LI(ai)SE as part of how they became legible candidates for non‑technical AI safety roles.

Theory of impact

Over time, having more of these people in the right places strengthens the institutional and operational “scaffolding” around advanced AI systems, which is critical for actually preventing and responding to catastrophic failures, not just talking about them.

If LI(ai)SE succeeds, more aligned generalists end up in key non‑technical roles at AI safety orgs, which makes those orgs better at actually implementing safety, governance, and fieldbuilding work that reduces x‑risk from advanced AI.

How the money will be spent

For the ideal ($150k):

Core team (founder + 1–2 part‑time staff): 40% – $60,000
Fellow stipends & participant support: 25% – $37,500
Events & programming (venues, catering, prizes, honoraria): 20% – $30,000
Ops, tools & overhead: 10% – $15,000
Flex/experimentation buffer: 5% – $7,500

For the minimum ($25k):

Founder time: 60% – $15,000
Events & small pilot cohort: 30% – $7,500
Ops & tools: 10% – $2,500

Discussion

Ammara DurraniEndorsement11d

I'm a generalist who's now a part of LI(ai)SE's growing AI safety community!

Rohan Barad3d

thanks for your comment and support to the community @Ammara Durrani