The main thing I expect busy people want when receiving an EAG cold message is:
My recommended message structure:
This advice is for messaging busy people, who will get more requests than they have time for, and need to prioritise, for less established people you can be way more chill.
I’m writing this because I think cold messages can be really valuable, and I hope this gives you the confidence to reach out to busy people, and helps create a community where busy people talk to the people they can most help.
I imagine a lot of people are currently on Swapcard for EAG London, and are writing cold messages to people they don't know asking for help (eg advice or mentorship). I have a bunch of takes about what makes for a good cold message and what makes me more likely to respond/engage, so I thought it might be useful if I wrote some of them up. This is heavily informed by my own experience, but I hope it is more broadly relevant to people who get overbooked at conferences (e.g. speakers, experienced people in a popular career path, etc), as they get more requests than they have time for, and need info to help them prioritise.
At a high level, when I receive a cold message my goal is to estimate the expected impact I can have via helping you in the conversation. This is obviously very hard to estimate on such limited info. My ideal cold message gives as much useful info as possible to help me estimate that[1], and otherwise cuts everything not useful to that, to be concise and quick to read. I'm very happy to have chats where there’s no direct benefit to me beyond being helpful, so there’s no need to sell me on anything else – I like being helpful! But I tend to get more requests than I have time for and, you know, it’s an EA conference – what else would I be prioritising by?
I generally think reaching out to people is high expected value and recommend it. A norm of EAGs is that it is normal and encouraged to send cold messages to people you don’t know! Try not to waste people’s time, but IMO so long as you’re clear up front about how mutually valuable the conversation would be, it’s fine to send whatever you want. For most busy people it's pretty cheap to receive and decline a well-written message, and helpful to get a message from someone they want to meet, so please don't feel discouraged to reach out! In particular, messages that follow the tips here should be easy to skim.
I’m writing this because cold messages can be really valuable! As an example, when my co-author Jemima was an undergraduate at Durham University attending her first EAG, she reached out to an expert on covid and China, and the advice she received led her to change her plans to study abroad in China that year. (She applied for Taiwan instead, and China stayed closed.) Similarly, talking to people in the UK civil service changed her graduate plans of joining the foreign office.
This can be awkward to write and feel like bragging - I’m personally pretty fine with this and value directness[2], but others may vary.
One good framing can be beginning with “More context on my abilities/background - apologies for the directness, but I thought this would be useful info on how to prioritise meetings:”
Hi Neel!
I'm a final year undergraduate at University of Texas in Austin, and am interning at Microsoft over the summer.
In my spare time, I've replicated the paper 'refusal is mediated by a single direction' and wrote up a blog post here: [link]. I did the same for a couple of other concepts, and you can find the positive and negative results on my blog.
I'd really appreciate talking to you because I'd like to go into a career in mech interp and I'm scoping about a more ambitious next project, building on your paper on empirically eliciting latent knowledge. I'd love to show you what I've done so far and hear your thoughts on this.
In particular, I’d love to get your thoughts on whether linear probes or sparse autoencoders are the right tool here.
Hey Neel,
I’m a software engineer. I’ve worked in startups for a few years, and I want to have more of an impact by moving into AI Safety.
I don’t have much ML experience, but in my previous role I was able to set up a pipeline to process incoming requests 30% faster while preserving privacy, using LLaMA 3.3 8B, with about two week’s work and upskilling.
I’m finding the career transition a bit difficult to navigate, and I’d love to get your thoughts on how I should approach upskilling, demonstrating my skills to employers, and the best places to apply. I’m most interested in mechanistic interpretability, but happy to find wherever I can have the most impact.
In particular, I dropped out of uni to join this startup, and seem to often fail resume screens and never even get invited to interview, how can I get past this? Should I be networking more?
Everyone at EAG was once sending their first cold message. If you're unsure whether to reach out, I recommend erring on the side of doing it! The worst case is a polite 'no,' and the best case could be genuinely helpful for your journey – in my opinion, the main reasons conferences exist are to help new connections happen, and cold messages are a crucial part of that.