Reread Patrick McKenzie (patio11)'s inspirational oral history of VaccinateCA and thought to pull out a few quotes for my own edification. (Patrick posted about this on the forum awhile back, that's worth reading too.)

The following is what it looks like to bake in triage into org decision-making from the top down:

We had an internal culture of counting the passage of time from Day 0, the day (in California) we started working on the project. We made the first calls and published our first vaccine availability on Day 1. I instituted this little meme mostly to keep up the perception of urgency among everyone. 

We repeated a mantra: Every day matters. Every dose matters. 

Where other orgs would say, ‘Yeah I think we can have a meeting about that this coming Monday,’ I would say, ‘It is Day 4. On what day do you expect this to ship?’ and if told you would have your first meeting on Day 8, would ask, ‘Is there a reason that meeting could not be on Day 4 so that this could ship no later than Day 5?’

I started every meeting and status report to the team by reminding them what Day it was. Our internal stats dashboard had a counter of what Day it was. I had a whiteboard in my apartment showing what Day it was. I wrote that every morning as soon as I woke up, and updated the other two numbers right before I went to sleep. Those were: the number of locations we had published to Californians where they could currently get the vaccine, and the number we knew about elsewhere across the United States with the vaccine. 

The latter was zero at this point, of course. I brushed my teeth, wrote my emails, ate my meals, did media interviews, called my family, negotiated with funders, and said my prayers with the zero where I could see it.

A photo of the non-computer version of VaccinateCA’s dashboard, taken on Day 39. It shows VaccinateCA’s then-current understanding of where to find the vaccine: 1,025 sites in California and 0 sites outside of California. Image by Patrick McKenzie. 

I think in absolute terms plenty of orgs do this, Patrick just so happens to be a good writer. But in relative terms it's quite rare, and very meaningful to see, especially for folks like me with a bit of mission orientation. Also this:

After the workday was over and pharmacies stopped answering their phones, the workday began again immediately, as much of our engineering team turned off their day job computers and logged on to Discord to digest what we had learned. We worked into the night, and not infrequently through it, to be ready for 9:30am the next morning.

It was often a brutal crunch. I told the team to take care of themselves and keep an eye on one another. The mission wouldn’t be served by anyone ending up in the hospital. But subject to that constraint, we worked like men and women possessed, because people were dying.

On entrepreneurship:

Part of entrepreneurship is having a vision of something that is possible and figuring out what is necessary to bring it into the world. A cynic would say that the world has a secret: Building things is not actually possible, because different organizations have different timelines allowing access to different resources, and it is impossible to correctly sequence things to satisfy all the requirements in order to build anything. An entrepreneur would tell the cynic a secret in return: You can carefully titrate the amount of truth to various parties to dissolve these deadlocks.

Your donor-advised fund won’t let you donate unless we’re a 501(c)(3)? Well, you’d donate if we were a 501(c)(3), right? Great. We’re applying for approval as a 501(c)(3) from the IRS. Can I put you down for $25,000? Dear IRS examiners: I have a written commitment from a charitable allocator for a $25,000 donation contingent on 501(c)(3) status. As you are aware, IRS procedure says that this qualifies for expedited processing. Oh, yes, government actor whose cooperation we need, we’re a nonprofit. Look at this official paperwork from Delaware. It says that the State of Delaware is officially aware that I say we’re a nonprofit. Not good enough? Our 501(c)(3) status? The IRS is busy approving it, on an expedited basis.

This is somewhat reminiscent of what Scott Alexander wrote about a very different person, although what Patrick calls "carefully titrating the amount of truth to various parties" Scott outright labeled "blatant lies"; my takeaway is that it's possible to do a more ethical version of the description below: 

I started the book with the question: what exactly do real estate developers do? They don’t design buildings; they hire an architect for that part. They don’t construct the buildings; they hire a construction company for that part. They don’t manage the buildings; they hire a management company for that part. They’re not even the capitalist who funds the whole thing; they get a loan from a bank for that. So what do they do? Why don’t you or I take out a $100 million loan from a bank, hire a company to build a $100 million skyscraper, and then rent it out for somewhat more than $100 million and become rich?

As best I can tell, the developer’s job is coordination. This often means blatant lies. The usual process goes like this: the bank would be happy to lend you the money as long as you have guaranteed renters. The renters would be happy to sign up as long as you show them a design. The architect would be happy to design the building as long as you tell them what the government’s allowing. The government would be happy to give you your permit as long as you have a construction company lined up. And the construction company would be happy to sign on with you as long as you have the money from the bank in your pocket. Or some kind of complicated multi-step catch-22 like that. The solution – or at least Trump’s solution – is to tell everybody that all the other players have agreed and the deal is completely done except for their signature. The trick is to lie to the right people in the right order, so that by the time somebody checks to see whether they’ve been conned, you actually do have the signatures you told them that you had. The whole thing sounds very stressful.

But I digress. Relatedly:

That’s life in a start-up: trying to create enough impact very quickly to convince people to give you more resources, while understanding that the default case is running out of resources, and, by the way, everything is broken all the time.

On do-gooder precocity:

We saw peer projects sprout up in many states, with varying levels of effort and success. Many credited us as an inspiration. One peer project was ILVaccine.org, a project of Eli Coustan. We were working with him for a while before I learned he was in middle school. When I later blanked on his name and asked someone about the public health infrastructure coordinator who was a middle school student I was asked to be more specific.

On ownership and accountability, a case study:

Our scripts instructed callers to take down notes from pharmacists as to how to get an appointment for doses they had, when they had them. A Rite Aid pharmacy in San Bernardino asked our caller to sign up for an appointment at the county health department’s website. Our caller, who had been calling into San Bernardino frequently and had seen that website frequently, remarked that he had seen no Rite Aid listed as a possible vaccination location.

The pharmacist then swore into the telephone, hung up, and immediately called the county health department.

I want you to visualize the operations of county health offices during the middle of the pandemic. A stressed staff are busy coordinating a logistical challenge larger than any they’ve faced in their careers. Their phones are ringing off the hook. The consultancy that won the bid finally delivered the freaking appointment website, thank god. It is crappy and barely works but at least it is finally here. You just have to download all of the email attachments from the pharmacy chain corporate offices, maybe fix a few in Excel because those jokers can’t read clear instructions, then upload them into the administrative side of the portal, and finally people can register for appointments to get the doses sitting in pharmacy freezers.

Rite Aid’s data never made it into the system. Maybe Rite Aid forgot to send it and nobody followed up. Maybe it got eaten by the county’s spam filter. Maybe a public health worker with a million things to do did 999,999.

There were 13 Rite-Aids in San Bernardino county. None of them, despite being in possession of the most desirable object in the world, had received a single appointment. No pharmacist, with years of training in healthcare, noticed this before we told them.

Why would they? Every pharmacy has lots of tiny glass vials and bottles of pills and satchels of powder. Patients were coming in and getting healthcare. It was no one’s job to check that any particular vials got distributed quickly. Pharmacists are not pharmaceutical sales representatives; they do not generate demand. Pharmacists service appointments and prescriptions, deliver healthcare, and go on to the next patient. If you walked up to the counter or called in and asked about Covid appointments, they’d tell you to book one with the county and move on to the next customer. Just another day at the pharmacy.

You might object and say that it must have been someone’s job to actually get those doses injected. Someone who worked . . . at the White House? Okay, no, but at the CDC? Okay, no, but at the California Office of the Governor? Okay, no, but at the county health department? Okay, no, county health departments do not track individual SKU inventory levels at individual pharmacies, that’s actually not a thing. OK, then, Rite Aid – some logistics manager at Rite Aid should have opened a spreadsheet, seen an SKU like #DJFKJDF3285325 with 50 doses available out of 50 shipped at a location in San Bernardino, and immediately said, ‘Oh, #$*#(%. That drug being in supply is equivalent to a life-threatening medical emergency. I will now get out my emergency procedures binder.’ Nope, that is also not a reasonable expectation.

Each of these organizations wants someone else to be responsible for catching errors like this, and they want them to be effective at doing so. They want, and the nation wants, an organization to be accountable for delivering the vaccine.

VaccinateCA considered this bug, and anything else that kept vaccines in freezers while patients were still waiting, to be our problem.

This problem was fixed because a caller from VaccinateCA thought to say, ‘Wait, I notice that I am confused’. It was fixed within about half an hour of being noticed. We estimate more than 500 doses were quickly taken out of freezers, thawed, and injected into waiting arms. Those arms were often attached to people who had been refreshing the county website every few minutes hoping new appointments would finally open up.

This was early and dramatic evidence to me that California was benefiting from having an organization that felt itself accountable for delivering the vaccine.

On how much of Patrick's job in the early days as CEO was bringing in funding:

VaccinateCA had an extremely effective team, as good as any I have ever had the privilege of working with. They were instrumental in almost everything I did and probably could have done almost all of it without me. The main thing I uniquely brought to the table, and spent a lot of my cycles on, was finding the money.

Our earliest funding source was a prepaid debit card I spun up and posted in our public Discord, with $20,000 of my own savings on it. That would cover servers and software and similar for a while. That was not going to be sufficient to get a proper nonprofit with a paid staff off the ground, and I knew we would both need that and need to be read as that to get cooperation from some quarters.

I called in favors and plead our case up and down the tech industry, and scraped together about $1.2 million in funding.

This was below what I initially thought I could reasonably raise, and below what I thought we likely needed. For better or worse, it would have been a lot easier if I had pitched it as: ‘Just make a small angel investment in a promising technology company whose CEO thinks his job is burning through investor dollars as quickly as possible while driving the total addressable market to zero. You won’t make any money on it, but think of the story.’

But while that tech company would probably have been well funded, it would have smelled like a tech company to potential partners. To accelerate shots in arms we urgently needed the cooperation of people who, if confronted with the proposition ‘Big Tech is bringing about the end of constitutional democracy so that it can gather more of your data to sell’, would like that tweet from their iPhone. I have a different point of view, but debating would not have put shots in arms.

We were approximately the most privileged nascent nonprofit imaginable in terms of access to funding, and given that it directly unlocked our ability to help people find the vaccine, I don’t want to complain too much about the process of getting it. I will record, for the benefit of future charitable founders, that probably half of my time from Day 8 to Day 160 was spent chasing funding, dealing with funders and the nonprofit industrial complex, pitching (and pitching and pitching and pitching) large pots of tech money earmarked for pandemic response, filing required reports with funders and the government, and diligently accounting for every penny spent.

It was a bit of a culture shock coming from the technology industry. Tech isn’t exactly profligate, but it certainly empowers twentysomething engineers to spend thousands of dollars by typing a command into their terminals. An engineer who fumble-fingers a command and spends ten times what they expected to is told to type more carefully next time.

On the advantages private individuals and organizations have over official initiatives:

The government of the United States is an intrinsically political entity. We were formally nonpartisan (and even better, as a 501(c)(3) nonprofit, had to be). Informally, to quote a memo I wrote early on, we would do a deal with the devil himself if it got one more patient one more dose. We didn’t need to worry about compromising anyone’s reelection chances by being too maniacally focused on shots in arms to consider the big picture. We had no responsibilities to allies in our party, like not overshadowing their efforts, because we had no party and, for that matter, no shadow.

I knew that many political actors wanted to hoard the facts of their operations so that they could claim credit for them. I just didn’t particularly care. If an actor had a dose available to the public, it was going to be publicized anywhere we could cause it to be.

(It's hard to convey how much I like and appreciate that last paragraph.)

On funder-nonprofit misalignment:

Some potential funders were in after an emailed discussion that could fit in a tweet. Some were in after a single call.

Some potential funders had expectations that were misaligned with us. VaccinateCA was always designed as a rapid-response project that would spin up, cover for an urgent gap in US infrastructure, and then spin down once the work was done. We explained this at length while emphasizing that we wanted to work with funders who could reach a decision quickly. Every day mattered. Every dose matters.

We had some interactions where we were put through weeks or months of grant writing, which sounds like ‘turn in a paper and wait for it to be graded’ and is more ‘schedule sufficient meetings with sufficient backing documentation to buy a company for $20 million’. The funder eventually passed on us, saying they worried we would create no institution with enduring value after the pandemic.

I don’t begrudge anyone’s choices of how to spend their money, particularly charitably earmarked money. I will point out that the gap in expectations between a grant-reviewing team keen on institution building and a nonprofit with an urgent unmet need is a very, very common story in nonprofit fundraising.

Many pots of money have preferences with regard to how they allocate, and those preferences change with the seasons. Have I mentioned that health equity was all the rage in California in 2021? I put on my best face to funders, explained that the system of siloing vaccine information benefited only people who were professionally competent at navigating the American healthcare bureaucracy. I suggested that publishing vaccine locations to a website and Google and every other place we could think of was an improvement over that status quo. I didn’t engage with debates about how, and this was made absolutely explicit in some conversations – perhaps saving lives but failing to save lives in preferred demographic ratios would be considered worse than not engaging in the project at all.

(I'll be upfront that despite having spent a couple of my formative years in California, my bias leans so far in Patrick's direction that it'd probably be useful for me to hear out the strongest counterargument, especially in the context of triage.)

Strong upvote for multiple reasons: thoroughness and transparency of reasoning and execution, stating upfront that the cost-effectiveness was well below WHO's threshold, prioritising reproducibility, and the "what this analysis doesn't show" and "lessons learned" sections. 

I wonder if "de-averaging the portfolio" by ballparking cost per impact by channel (school awareness packages vs workshops vs crisis hotline) might help guide resource allocation across channels (send more packets vs get more hotline volunteers etc). My naive guess is that suicide risk isn't the same across channels, which the model as it stands implicitly assumes (which makes school awareness get ~10x as much impact credit as the crisis hotline); I'd assume that this risk for the school students is similar to that of the general population but that hotline callers are self-selected for being at much higher risk of suicide, so I'd explore the hypothesis that most of the bottomline suicide prevention impact comes from the crisis hotline even though most of the topline reach comes from the school awareness packages. This is also a channel attribution question, which as you've said the current model doesn't show and is a hard one to answer. 

I am in the process of building such a thing

Is it available online / open-source / etc by any chance? Even just as a butterfly idea.

I don't know, sorry. I admittedly tend to steer clear of community debates as they make me sad, probably shouldn't have commented in the first place...

Great rule of thumb :) I'm sometimes knee-deep in chartmaking before I realise I don't actually know exactly what I want to communicate.

Tangentially reminded me of Eugene Wei's suggestion to "remove the legend", in an essay that also attempted to illustrate how to implement Ed Tufte's advice from his cult bestseller The Visual Display of Quantitative Information. 

I'd also like to signal-boost the excellent chart guides from storytelling with data.

I don't know what he meant, but my guess FWIW is this 2014 essay.

Aside: wow, the slide presentation you linked to above is both really aesthetically pleasing and has great content, thanks for sharing :) 

I think you're conflating intervention durability with outcome durability? A child who survives cerebral malaria due to seasonal malaria chemoprevention gets to live the rest of their life; SMC programs are rerun because (mostly) new beneficiary cohorts are at highest risk, not because last year's cohort's survival expires somehow. Similarly with nets and child vaccinations and vitamin A deficiency prevention (i.e. the GW top charities), as well as salt iodisation and TaRL in education and many other top interventions recommended by the likes of TLYCS and FP and so on.

I'd also push back a bit on the "permanent solutions" phrasing. Infrastructure isn't that permanent and requires ongoing expenditures and has a shelf half-life (I used to work in ops in fluid resource-constrained environments so I feel this keenly), diseases can develop resistance to vaccines so you need boosters, etc. Ex-AIM CEO Joey Savoie has a great blog talking more about how Someone Always Pays: Why Nothing Is Really "Sustainable".

Phrasing nitpicking aside, some big funders are in fact funding more "permanent / sustainable" solutions. Open Phil Coefficient Giving's new $120M Abundance and Growth Fund aims to "accelerate economic growth and boost scientific and technological progress while lowering the cost of living", and Founders Pledge (which is almost OP-scale in giving) just launched a new Catalytic Impact Fund that targets "ecosystem leverage points" where small investments can build "sustainable, long-term solutions to global poverty and suffering". 

Jason's comment above on timetable speedup is essentially how e.g. GiveWell models their grants for malaria vaccines. The model says their grant would need to speed up co-administration for all highest need children in all of subsaharan Africa by at least 9 months to clear their 10x bar, so you can interpret their grant as a bet that funding that clinical trial would in fact achieve at least 9 months speedup. Notice how it's an uncertain bet; I think most donors (weighted by dollars moved) care quite a fair bit about certainty of direct benefits, so they'd probably donate to e.g. the Top Charities Fund instead of the more experimental EV-maxxing All Grants Fund.

I admire influential orgs that publicly change their mind due to external feedback, and GiveWell is as usual exemplary of this (see also their grant "lookbacks"). From their recently published Progress on Issues We Identified During Top Charities Red Teaming, here's how external feedback changed their bottomline grantmaking:

In 2023, we conducted “red teaming” to critically examine our four top charities. We found several issues: 4 mistakes and 10 areas requiring more work. We thought these could significantly affect our 2024 grants: $5m-$40m in grants we wouldn’t have made otherwise and $5m-$40m less in grants we would have made otherwise (out of ~$325m total).

This report looks back at how addressing these issues changed our actual grantmaking decisions in 2024. Our rough estimate is that red teaming led to ~$37m in grants we wouldn't have made otherwise and prevented ~$20m in grants we would have made otherwise, out of ~$340m total grants. The biggest driver was incorporating multiple sources for disease burden data rather than relying on single sources.1 There were also several cases where updates did not change grant decisions but led to meaningful changes in our research. 

Some self-assessed progress that caught my eye — incomplete list, full one here; these "led to important errors or... worsened the credibility of our research" (0 = no progress made, 10 = completely resolved):

• Failure to engage with outside experts (8/10): We spent 240 days at conferences/site visits in 2024 (vs. 60 in 2023). We think this type of external engagement helped us avoid ~$4m in grants and identify new grant opportunities like Uduma water utility ($480,000). We've established ongoing relationships with field experts. (more)
• Failure to check burden data against multiple sources (8/10): By using multiple data sources for disease burden, we made ~$34m in grants we likely wouldn't have otherwise and declined ~$14m in grants we probably would have made. We've implemented comprehensive guidelines for triangulating data sources. (more)
• Failure to account for individuals receiving interventions from other sources (7/10): We were underestimating how many people would get nets without our campaigns, reducing cost-effectiveness by 20-25%. We've updated our models but have made limited progress on exploring routine distribution systems (continuous distribution through existing health channels) as an alternative or complement to our mass campaigns. (more)
• Failure to estimate interactions between programs (7/10): We adjusted our vitamin A model to account for overlap with azithromycin distribution (reducing effectiveness by ~15%) and accounted for malaria vaccine coverage when estimating nets impact. We've developed a framework to systematically address this. (more)

(As an aside, I've noticed plenty of claims of GW top charity-beating cost-effectiveness figures both on the forum and elsewhere, and I basically never give them the credence I'd give to GW's own estimates, due to the kind of (usually downward) adjustments mentioned above like receiving interventions from other sources or between-program interventions, and GW's sheer reasoning thoroughness behind those adjustments, seriously, click on any of those "(more)"s)

Some other issues they'd "been aware of at the time of red teaming and had deprioritized but that we thought were worth looking into following red teaming" — again incomplete list, full one here:

• Insufficient attention to inconsistency across cost-effectiveness analyses (CEAs) (8/10): We made our estimates of long-term income effects of preventive health programs more consistent (now 20-30% of benefits across top charities vs. previously 10-40%) and fixed implausible assumptions on indirect deaths (deaths prevented, e.g., by malaria prevention that aren’t attributed to malaria on cause-of-death data). We've implemented regular consistency checks. (more)
• Insufficient attention to some fundamental drivers of intervention efficacy (7/10): We updated our assumptions about net durability and chemical decay on nets (each changing cost-effectiveness by -5% and 11% across geographies) and consulted experts about vaccine efficacy concerns, but we haven't systematically addressed monitoring intervention efficacy drivers across programs. (more)
• Insufficient sideways checks on coverage, costs, and program impact (7/10): We funded $900,000 for external surveys of Evidence Action's water programs, incorporated additional DHS data in our models, and added other verification methods. We've made this a standard part of our process but think there are other areas where we’d benefit from additional verification of program metrics. (more)
• Insufficient follow-up on potentially concerning monitoring and costing data (7/10): We’ve encouraged Helen Keller to improve its monitoring (now requiring independent checks of 10% of households), verified AMF's data systems have improved, and published our first program lookbacks. However, we still think there are important gaps. (more)

I always had the impression GW engaged outside experts a fair bit, so I was pleasantly surprised to learn they thought they weren't doing enough of it and then actually followed through so seriously, this is an A+ example of organisational commitment to and follow-through on self-improvement so I'd like to quote this section in full:

In 2024, we spent ~240 days at conferences or site visits, compared to ~60 in 2023. We spoke to experts more regularly as part of grant investigations, and tried a few new approaches to getting external feedback. While it’s tough to establish impact, we think this led to four smaller grants we might not have made otherwise (totalling ~$1 million) and led us to deprioritize a ~$10 million grant we might’ve made otherwise.

More detail on what we said we’d do to address this issue and what we found (text in italics is drawn from our original report):

• More regularly attend conferences with experts in areas in which we fund programs (malaria, vaccination, etc.).
  • In 2024, our research team attended 16 conferences, or ~140 days, compared to ~40 days at conferences in 2023.35
  • We think these conferences helped us build relationships with experts and identify new grant opportunities. Two examples:
    • A conversation with another funder at a conference led us to re-evaluate our assumptions on HPV coverage and ultimately deprioritize a roughly $10 million grant we may have made otherwise.36
    • We learned about Uduma, a for-profit rural water utility, at a conference and made a $480,000 grant to them in November 2024.37
  • We also made more site visits. In 2023, we spent approximately 20 days on site visits. In 2024, the number was approximately 100 days.38
• Reach out to experts more regularly as part of grant investigations and intervention research. We’ve always consulted with program implementers, researchers, and others through the course of our work, but we think we should allocate more relative time to conversations over desk research in most cases.
  • Our research team has allocated more time to expert conversations. A few examples:
    • Our 2024 grants for VAS to Helen Keller International relied significantly on conversations with program experts. Excluding conversations with the grantee, we had 15 external conversations.
    • We’ve set up longer-term contracts with individuals who provide us regular feedback. For example, our water and livelihoods team has engaged Daniele Lantagne and Paul Gunstensen for input on grant opportunities and external review of our research.
    • We spoke with other implementers about programs we’re considering. For example, we discussed our 2024 grant to support PATH’s technical assistance to support the rollout of malaria vaccines with external stakeholders in the space.39
  • This led to learning about some new grant opportunities. For example:
    • The $150,000 grant to International Rescue Committee (IRC) for desk-based scoping of programs to increase vaccination coverage stemmed from a conversation with an expert.
    • We connected with Zipline at a conference, and made a $55,000 grant to them for desk-based scoping of drones to increase vaccination coverage in December 2024.
    • We are currently considering a $4 million grant that we learned about through an expert conversation.40
• Experiment with new approaches for getting feedback on our work.
  • In addition to the above, we tried a few other approaches we hadn’t (or hadn’t extensively) used before. Three examples:
    • Following our red teaming of GiveWell’s top charities, we decided to review our iron grantmaking to understand what were the top research questions we should address as we consider making additional grants in the near future. We had three experts review our work in parallel to internal red teaming, so we could get input and ask questions along the way.41 We did not do this during our top charities red teaming, in the report of which we wrote “we had limited back-and-forth with external experts during the red teaming process, and we think more engagement with individuals outside of GiveWell could improve the process.”
    • We made a grant to Busara to collect qualitative information on our grants to Helen Keller International's vitamin A supplementation program in Nigeria.42
    • We funded the Center for Global Development to understand why highly cost-effective GiveWell programs aren’t funded by other groups focused on saving lives. This evaluation was designed to get external scrutiny from an organization with expertise in global health and development, and by other funders and decision-makers in low- and middle-income countries.

Some quick reactions:

• I like that GW thinks they should allocate more time to expert conversations vs desk research in most cases
• I like that GW are improving their own red-teaming process by having experts review their work in parallel
• I too am keen to see what CGD find out re: why GW top-recommended programs aren't funded by other groups you'd expect to do so
• the Zipline exploratory grant is very cool, I raved about it previously
• I wouldn't have expected that the biggest driver in terms of grants made/not made would be failure to sense check raw data in burden calculations; while they've done a lot to redress this there's still a lot more on the horizon, poised to affect grantmaking for areas like maternal mortality (prev. underrated, deserves a second look)
• funnily enough, they self-scored 5/10 on "insufficient focus on simplicity in cost-effectiveness models"; as someone who spent all my corporate career pained by working with big messy spreadsheets and who's also checked out GW's CEAs over the years I think they're being a bit harsh on themselves here...

Ben Kuhn has a great essay about how 

all my favorite people are great at a skill I’ve labeled in my head as “staring into the abyss.”¹

Staring into the abyss means thinking reasonably about things that are uncomfortable to contemplate, like arguments against your religious beliefs, or in favor of breaking up with your partner. It’s common to procrastinate on thinking hard about these things because it might require you to acknowledge that you were very wrong about something in the past, and perhaps wasted a bunch of time based on that (e.g. dating the wrong person or praying to the wrong god). However, in most cases you have to either admit this eventually or, if you never admit it, lock yourself into a sub-optimal future life trajectory, so it’s best to be impatient and stare directly into the uncomfortable topic until you’ve figured out what to do. ...

I noticed that it wasn’t just Drew (cofounder and CEO of Wave) who is great at this, but many the people whose work I respect the most, or who have had the most impact on how I think. Conversely, I also noticed that for many of the people I know who have struggled to make good high-level life decisions, they were at least partly blocked by having an abyss that they needed to stare into, but flinched away from.

So I’ve come to believe that becoming more willing to stare into the abyss is one of the most important things you can do to become a better thinker and make better decisions about how to spend your life.

I agree, and I think there's an organisational analogue as well, which GiveWell exemplifies above.

CE/AIM-incubated orgs run lean. (Some past discussion here if you're interested.) I also don't live in a high CoL country, which helps.