New Guy

Karma: 30

New Guy 22 Sep 2026 8:21 UTC
2 points
0 ∶ 0
on: Total Safety Transparency?
The objections section feels pretty strawmanny here.
1. It empowers your enemies
True. But it empowers your friends as well. Truth is an asymmetric weapon; if what you are working on is good, you will have more friends than enemies.
In the linked essay, truth is called “assymetric weapon” in the context of a logical debate. Unfortunately, the vast majority of the world doesn’t form opinions based on logical debate. Storytelling and rhetoric prevail, especially in the short term.
For storytelling, truth (or rather data) is also asymmetric but in the exact opposite way. The more you share (especially of “raw” internal comms), the easier it is to cherrypick parts that make you look bad.
Debunking misleading claims takes significantly more effort than making those claims in the first place. Just take a look at the rise of alt-right or anti-vaccine movement.
The objections you stated as 2, 4 and 5 are logically flowing from this:
(Objection 1) Your enemies can use your transparency against you ->
(4) this can damage the reputation of the org and anyone who works with it → a mix of two outcomes happens:
- (2) The org accepts the risk, this can sometimes result in materially bad outcomes (e.g. withdrawn funding or another org refusing to collaborate due to perceived hazard)
- (5) The org (and the people in it) tries to mitigate the risk by investing more time to craft communication in a way that is less prone to be misused
I think that especially the last point is severely underestimated by calls for radical transparency. To be efficient, internal comms hugely rely on shared context, mutual good faith and short loop for asking clarifying questions. External comms have none of those benefits so crafting them takes significantly more effort—one needs to explain the context, pre-empt questions and account for the possible bad faith interpretations.

New Guy 21 Sep 2026 20:15 UTC
3 points
0 ∶ 0
on: YCombinator companies still aren’t growing faster due to AI
Some thoughts from a product manager working in tech:
1. AI increasing productivity allows startups to do more with less. I wouldn’t necessarily expect it to significantly accelerate growth in general as coding speed is rarely the bottleneck for scaling products. You still need to grow your team, reach your target audience, find product-market fit, build your brand, convince customers to change habits, etc. This all takes time and effort. Coding is a surprisingly small part of it in most cases, especially for startups that aren’t lacking funds for hiring engineers (which I’d expect to encompass ~all of the YC-backed ones).
2. None of your metrics is actually measuring the rate of growth. You are measuring the absolute size (valuation) of a company after a certain amount of time passes. It’s entirely possible that the startups are indeed growing faster but are smaller than before, sold off earlier or taking less investment (making the post-YC valuation less accurate).
  A few effects that would incentivize this:
  (1) AI enables doing the same work with a smaller team, decreasing the need for external investment and therefore founder dilution, lowering founder incentives for high valuation (for a founder 30% share in a $50M company is actually better than a 10% share in $150M one, as they maintain more steering power)
  (2) AI makes copying a product easier, increasing the bargaining power of larger incumbents offering acquisition
  (3) Advances in general-purpose AI are reshaping markets and societies faster than any technological change before, increasing the risk of a startup becoming irrelevant despite early success.
3. AI capable of significantly accelerating coding in non-trivial use cases has only been available since mid 2025 - early 2026, depending on who you ask. The benefits of AI for coding that we’re discussing today would not be visible in your data yet anyway.

New Guy 21 Sep 2026 13:30 UTC
7 points
2 ∶ 0
on: Do AI safety talent programmes work? Nobody has run the study that would tell us.
I think this is looking too narrowly at the talent programmes’ potential impact. To my understanding their overarching goal is getting more high-quality talent working on AI Safety faster. Counterfactually getting people hired is not the only action that can contribute to this. Off the top of my head I can think of:
1. Getting people hired counterfactually faster (as called out by @Ryan Kidd below)
2. Pre-filtering applicants for orgs with limited recruiting manpower (someone getting into a competitive programme is a decent signal, in the same way as a prestigious university or work at FAANG)
3. Reaching out to talent outside of the ecosystem who wouldn’t even consider AI Safety otherwise
4. Connecting people who then go on to build new organizations
5. Getting people hired into counterfactually higher-impact positions than they would otherwise go for (e.g. many people seem to default to technical research even while they have transferrable skills to work in a more senior role in ops or governance)

New Guy 21 Sep 2026 12:52 UTC
1 point
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in reply to: Jen baik’s comment on: Jenba’s Quick takes
To add to that comparison: Google invests into actively helping the applicants get in. They:
- Have a standardized recruitment process that applicants can prepare for ahead of time
- Point at resources which can be used to prepare
- Offer mock interviews
- Offer a grade of sorts, even to failing candidates (e.g. “Your interviews would put you at L5 level but right now we are looking for L6+”)
- Offer detailed feedback
- Actively reach out to past candidates
This is based on my experiences with Google in Europe, might not generalize to the US. At the same time I’d expect Europe to be more talent-constrained, i.e. closer to the realities of the AI Safety ecosystem.

New Guy 27 Aug 2026 17:51 UTC
1 point
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in reply to: Carol N’s comment on: Impact markets made concrete
maybe previously a charity would have sold 20% of their impact for $1 million, but now they sell it for $5 million because lots of impact investors are competing.
What you are describing here is demand for funding shifting due to increased supply. But that demand isn’t infinitely elastic. Scaling an organization is much more complex than just throwing money at it (this recent article has a good overview of the problem). That’s why I’m talking about a demand-constrained market.
charities would also be able to set their own terms, so they could choose between selling 20% for $5 million or a smaller amount for $2 million.
I don’t understand that part. How would they pick the number? To my understanding the “impact credits” are internet points with no inherent value.

New Guy 27 Aug 2026 10:25 UTC
1 point
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on: Impact markets made concrete
If I understand the 1/(t+5) schedule correctly, it means the price of capital can’t move in response to supply. In the for-profits investment markets it does: more investors competing to invest = less equity for the same dollars, because capital that’s easy to replace has less counterfactual value.
If AI money suddenly makes funding abundant while vetting capacity doesn’t grow accordingly (which seems to be the most likely scenario right now), we end up precisely in this sort of demand-constrained market. I’m curious how you’d adjust to account for that.

New Guy 27 Aug 2026 10:06 UTC
1 point
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in reply to: Carol N’s comment on: Impact markets made concrete
This article was brought to my attention by a discussion with @Austin here. My main critique is in line with @harfe, cross-posting here:
[In the proposed impact market model] An org’s valuation is implied by how much money it raises later. This measures how well a funder anticipated other funders, not the actual impact.
At a surface level this appears congruent with how the for-profit world operates. Startup valuations are also set by the money raised in later rounds. However there’s a crucial difference—the value of firms is ultimately grounded in the expectations of future output in a way that value of non-profits can’t be. Equity prices are guesses about very concrete future cash flows from people buying things the firm offers. The accuracy of those guesses can be ultimately checked against something that isn’t another investor’s opinion. The output is uniform—a dollar earned on a grocery store chain is the same as a dollar earned on an AI company^[1].
In contrast, EA orgs aim for “positive impact” which can be quantified only by a very subjective evaluation with multiple assumptions, not by any market mechanism. The output is not uniform. Even if we had perfect measurement (we don’t) I might value 1 human QALY above 1000 shrimp QALYs while you do the opposite.
This results in money invested being a much worse proxy for outcomes in a non-profit world than in the for-profit one. If I invest $1 M in Uber instead of Intel, I signal to everyone that I believe Uber is more likely than Intel to be worth more in some time horizon. If I invest $1 M in AMF instead of AWF, the signal is not clear. I might consider AMF to be more efficient than AWF but I might instead assign a higher value to human lives or simply have funds which are earmarked for GHD.
1. ^
  At least to a good approximation. Individual investors may choose to price in externalities, e.g. treat a grocery store dollar as “better” than the same dollar coming from an oil or tobacco company.

New Guy 27 Aug 2026 10:02 UTC
3 points
0 ∶ 0
in reply to: Austin’s comment on: Money, taste, dealflow, hustle, trust
I think we’re talking past each other on one specific thing: input dollars and output dollars aren’t the same dollars.
Firms compete for earned dollars. That’s the output, and it’s what credits the firm for the value it creates (by spending money, customers signal that they value what the firm provides above its monetary cost). Invested dollars are an input. They happen to share a unit with the output, but that doesn’t mean that they measure the same thing.
I read the recent substack post on impact markets and I think this is where it runs into trouble. An org’s valuation is implied by how much money it raises later. This measures how well a funder anticipated other funders, not the actual impact.
At a surface level this appears congruent with how the for-profit world operates. Startup valuations are also set by the money raised in later rounds. However there’s a crucial difference—the value of firms is ultimately grounded in the expectations of future output in a way that value of non-profits can’t be. Equity prices are guesses about very concrete future cash flows from people buying things the firm offers. The accuracy of those guesses can be ultimately checked against something that isn’t another investor’s opinion. The output is uniform—a dollar earned on a grocery store chain is the same as a dollar earned on an AI company^[1].
In contrast, EA orgs aim for “positive impact” which can be quantified only by a very subjective evaluation with multiple assumptions, not by any market mechanism. The output is not uniform. Even if we had perfect measurement (we don’t) I might value 1 human QALY above 1000 shrimp QALYs while you do the opposite.
This results in money invested being a much worse proxy for outcomes in a non-profit world than in the for-profit one. If I invest $1 M in Uber instead of Intel, I signal to everyone that I believe Uber is more likely than Intel to be worth more in some time horizon. If I invest $1 M in AMF instead of AWF, the signal is not clear. I might consider AMF to be more efficient than AWF but I might instead assign a higher value to human lives or simply have funds which are earmarked for GHD.
Coming back to your original post—it considers Money, Taste and Dealflow as separate components, but in our discussion you seem to propose to base the attribution primarily on Money. VC doesn’t do that. Limited Partners supply the capital and get returns proportional to capital. General Partners supply taste and dealflow and get carry. The carry exists precisely because “whose money was it” and “who found the deal” are understood to be different things. A regrantor is a GP, not an LP.
So I stand by my point that it’s more relevant to look at how attribution works inside firms (which also cannot rely on markets here) than to default to the amount of money invested, just because it happens to come in a familiar unit.
1. ^
  At least to a good approximation. Individual investors may choose to price in externalities, e.g. treat a grocery store dollar as “better” than the same dollar coming from an oil or tobacco company.

New Guy 26 Aug 2026 23:19 UTC
1 point
0 ∶ 0
on: The animal welfare movement could scale fast. Have you made a plan?
- Build low-commitment on-ramps: paid advisory engagements, board seats, fractional/interim senior roles, and short fellowships that let a mid-career professional contribute without a full career leap.
Is there evidence that “fractional/interim senior roles and short fellowships” actually help bring mid-career professionals on board? My intuition as a mid-career professional is the opposite—quitting my job to take on a time-bound opportunity feels significantly riskier than taking a permanent position. Double so if I’m aware that the ecosystem I’m trying to join has a strong preference for hiring from within.

New Guy 26 Aug 2026 18:16 UTC
3 points
0 ∶ 0
in reply to: Austin’s comment on: Money, taste, dealflow, hustle, trust
As a bit of a tangent:
nonprofit grantmakers should approximate their own assessment of impact as a function of “what fraction of the best nonprofits did I fund? For what size? How early?”—aka the same considerations that a for-profit vc considers for return on investment.
This approach only makes sense if you consider your available funding as a VC/grantmaker to be ~unlimited. In the VC world this might work for a16z or YC. Your regular VC fund/angel investor doesn’t ultimately care what fraction of good deals they pass on or how early they joined on a deal but what literal ROI they get: net profit divided by money invested.

New Guy 26 Aug 2026 17:58 UTC
3 points
0 ∶ 0
in reply to: Austin’s comment on: Money, taste, dealflow, hustle, trust
I fully agree that attributing the impact is very important as a signaling mechanism. However I don’t get why we should prioritize “who gave the money” over “who identified the opportunity” for this attribution.
Admittedly, I have zero background in non-profit grantmaking. I’m coming from the for-profit world of software products. In my world what counts as impact is counterfactual outcomes, not resources spent.
Imagine that John, the leader of team A, identifies a gap that is turning customers away, gets team B to deliver a fix and as a result the sales double. I’d say that John made the biggest counterfactual impact here, even if he didn’t lift a finger on the delivery part. Without further context, I’d also consider John leveraging team B, rather than his own, as a positive signal, showcasing that he can think outside the box to deliver desirable outcomes.
Yeah, such solution does lead to more credit being claimed in total for the same work across the entire organization. It’s the inherent cost of collaboration on anything non-trivial. There’s very few environments where that cost would outweigh the benefits of collaboration and, at least in my intuition, non-profit grantmaking ecosystem isn’t likely to be one of them.

New Guy 26 Aug 2026 12:27 UTC
3 points
1 ∶ 0
on: Money, taste, dealflow, hustle, trust
Nice framework!
I have one important caveat for the topic of dealflow. While I agree that the EA community has a lot to learn from VCs, there’s one crucial difference: startup funding has a much larger competitive component.
A for-profit investor wants the company they invest in to succeed, while maintaining an equity stake in it to profit from that success. This means they can win only if the company accepts their investment.
In contrast, a non-profit grantmaker is (or at least should be) concerned almost exclusively with helping the organization succeed. Whether it’s their or someone else’s money isn’t very relevant.
This makes some lessons to be learned from the VC community irrelevant or actively harmful (if grantmakers start competing for the same projects). At the same time, it enables a level of collaboration and common infrastructure that wouldn’t make sense in the for-profit world and which needs its playbook written from scratch.

New Guy 11 Jun 2026 17:09 UTC
3 points
0 ∶ 0
in reply to: Cathy Bogaart’s comment on: Experience of a ‘generalist’ transitioning into AI safety in 2026
Is THAT the problem? Not being involved in the hiring, I actually didn’t know WHO was getting hired. If they are the most qualified and the most capable of creating the positive outcome I’m hoping for, then I’m happy for them and the system.
If we frame the problem as a talent gap, it’s more about which roles aren’t filled—not only in the sense of positions remaining vacant but also including cases where the process takes a long time, seniority gets lowered or organizations work around the lack of talent, e.g. by shifting tasks to other roles or resigning from certain growth directions.
Who is getting hired (and more importantly: who isn’t) is a highly correlated but a different issue in my eyes. Even if all the vacancies got easily filled by people perceived as the most qualified, I’d argue that keeping the ecosystem closed to outsiders is still a major problem. Beyond the obvious equitability angle, it also encourages the homogeneity of thought and reinforces the perception of EA living in a bubble.
Overall I feel like communications is a very specific edge case here. Forgive me if I oversimplify but “understanding what and how to signal in order to convince a group of people from a different culture to take certain action” sounds exactly like the job description of a communications specialist, especially for an area like AI safety.
A recruitment process requiring this skillset to navigate does actually optimize for good comms specialists. At the same time, it will filter out talented software engineers, project managers, subject matter experts, etc. based on gaps in an area that has little impact on their actual on the job performance.

New Guy 10 Jun 2026 18:39 UTC
4 points
0 ∶ 0
on: Experience of a ‘generalist’ transitioning into AI safety in 2026
I feel like it’s a circular problem. The hiring pipelines within EA are heavily optimized towards “traditional” hires—fresh grads of elite universities and people jumping from one EA org to another. Recruiting experienced professionals from the outside world requires a significantly different approach. In organizations comprised primarily of traditional hires, few people can even see that problem, much less solve it.
I don’t think the EA community at large really understands just how insulated this ecosystem is.

New Guy 15 Aug 2025 16:30 UTC
2 points
0 ∶ 0
on: The relative range heuristic
This doesn’t make any sense to me at all. There’s a ton of hidden assumptions there that are glossed over, e.g.
Larger animals might have more capacity for suffering, but intuitively they might have 10x more or 100x more at most. Meanwhile, small animals are 1000x or 10000x more numerous than large animals. So the scale advantage of small animals is more important, and thus we should prioritize small animals.
This implicitly assumes that whatever resources we have will (a) help the same percentage of global population, no matter which animals we select and (b) reduce their suffering by the same percentage.

> Higher-frequency information is valuable, but a quarterly survey is 4x more expensive than an annual survey, and its information is probably not 4x more valuable. So the cost advantage of less frequent surveys is more important, and thus we should fund the survey annually rather than quarterly.
This assumes that the value of the information from the survey is only slightly higher than its cost. Let’s imagine that the cost to conduct the survey is $10k and the information gained is worth $1M. In that case doing the survey quarterly (+$30k) would only need to increase the value of the information gained by 3% to break even

New Guy 25 Apr 2025 15:40 UTC
6 points
0 ∶ 0
in reply to: Ozzie Gooen’s comment on: Ozzie Gooen’s Shortform
I’ve just ran into this, so excuse a bit of grave digging. As someone who has entered the EA community with prior career experience I disagree with your premise
“It’s very awkward to go from “manager of a small team” to “intern,” but that can be necessary if you want to learn a new domain, for instance.”
To me this kind of situation just shouldn’t happen. It’s not a question of status, it’s a question of inefficiency. If I have managerial experience and the organization I’d be joining can only offer me the exact same job they’d be offering to a fresh grad, then they are simply wasting my potential. I’d be better off at a place which can appreciate what I bring and the organization would be better off with someone who has a fresher mind and less tempting alternatives.
IMO the problem is not with the fact that people are unwilling to take a step down. The problem is with EA orgs unwilling or unable to leverage the transferrable skills of experienced professionals, forcing them into entry-level positions instead.

New Guy 20 Oct 2024 14:56 UTC
3 points
1 ∶ 0
in reply to: Sarah Reed’s comment on: Bad Omens in Current Community Building
While the post and this comment are now both ancient, I feel compelled to at least leave a short note here after reading them.
My background is in many ways similar to Sarah’s and I’ve came into the contact with the EA community about half a year ago. Unfortunately, 2.5 years later, most of the points raised here resonate heavily with my experiences. Especially the hive mentality, heavy focus on students (with little efforts towards professionals) and overemphasis on AI safety (or more generally—highly-specialized cause areas overshadowing the overall philosophy).
I don’t know what the solutions are but the problem seems to be still present.

New Guy

1. It empowers your enemies