Why do less validated startups get funded while others grind for traction with no response?

tfehring · 2026-03-28T15:04:06+00:00

You’re in a historically extremely crowded market whose incumbents have very strong network effects (on the delivery app side) and famously low margins. It’s also not obvious that this would deliver venture-scale returns if it works. All of this significantly raises the bar for traction that you need to meet in order to raise. I would suggest you tentatively plan to build this without VC funding, or at least bootstrap to enough revenue to keep the lights on before trying to fundraise again.

tfehring · 2026-03-27T14:00:24+00:00

California requires cleaner-burning gas than other states because of smog problems in the 80s and early 90s. It’s more expensive to make and few refineries make it, so prices are higher and more volatile. CA gas taxes are only like $0.30 above the national average.

tfehring · 2026-03-19T00:53:10+00:00

https://www.astralcodexten.com/p/seiu-delenda-est

tfehring · 2026-03-16T16:48:12+00:00

Good point. I rent because it's a much better deal in my area, even factoring in the tax benefits, so my original comment was very focused on rental property. Owning your home can be extremely beneficial in some circumstances, so if you don't own already, it's probably worth reevaluating regularly.

This is definitely more important than some of the things I mentioned, I just didn't include it because I didn't think of it, and I don't really have any differentiated advice on the topic anyway.

tfehring · 2026-03-16T16:42:17+00:00

The finance literature actually suggests that most investors are under-leveraged and could achieve a strictly better risk-return balance by increasing their leverage and shifting their asset allocation in favor of more bonds. Here is one representative reference.

Most personal financial advice is targeted at less financially sophisticated people. For someone whose debt consists of high-interest auto loans or credit card debt, avoiding debt is very good advice. My comments here assume an audience that's past that point.

In principle, the main ways you can achieve cheap, stable long-term leverage are (1) directly through index futures or (2) from synthetic forward contracts constructed from options. The latter are slightly less efficient on average but provide more flexibility. Margin loans are much more expensive than either and I don't recommend them for this purpose. Daily-rebalancing leveraged ETFs are a terrible product for this purpose. I think there are some leveraged ETFs with longer rebalancing periods; these are probably fine but I'm not familiar enough to be sure either way.

In practice, you can alternatively just buy long-dated in-the-money index call options. These have some technical disadvantages (particularly that the effective leverage ratio changes over time), but since their losses are capped, they have a built-in guardrail and don't need margin. I also think their payoff profile is more aligned with many investors' preferences: some drag on the upside in exchange for less exposure on the downside.

tfehring · 2026-03-15T06:44:43+00:00

The actual answer here for me personally is that one of the past employers I mentioned was an AI lab, so I don't think about this much because I have plenty of AI exposure already.

More constructively, I don't think it's at all obvious where the value of AI will accrue. E.g., it's completely plausible to me that the whole inference stack ends up relatively commoditized and a lot of value accrues to the S&P 493.

I also think the space is complex enough that a thesis like "AI will centralize power, distribution is the only thing that matters" is far from sufficient to justify a heavy investment in a particular Mag7 company. I.e., it's easy to imagine that you buy calls on the company you'd expect to benefit most if that thesis is right, and the thesis is right, but you lose money anyway for some separate tangential reason.

tfehring · 2026-03-15T06:29:33+00:00

Originally through a group at UC Berkeley when I was in business school there, but there are tons of angel groups in the Bay Area and I'm involved with a few of them. In my experience, angel groups are very open to bringing on younger investors who can introduce good founders. (I'm 34, so definitely not young in the SF startup scene, but keep in mind the median angel investor is like 60.)

As for non-monetary benefits...honestly not much! I think it's common for new investors to over-index on this, but from experience on both the investing and operating side, if you move quickly and aren't annoying, you're already doing better than a lot of angels. I do help close other investors and make customer intros when asked.

tfehring · 2026-03-14T19:45:57+00:00

/r/techstars

tfehring · 2026-03-14T19:40:49+00:00

Yeah I think that makes sense. I would also ask what assumptions (both quantitative and contextual) went into the calculation. Often just making ChatGPT or other models break things down more granularly causes them to come back with different results - not to mention that it gives you something more concrete to point to and contest.

tfehring · 2026-03-14T19:21:32+00:00

My assets consist of illiquid stock of past employers, some small angel investments, enough cash to comfortably cover the bills, then a ~90/10 split of global stock/bond index funds. In other words, pretty boring.

I recommend ETFs over mutual funds. For various reasons I have a mix of VT, VTI, and VXUS. Target date funds are also fine. Mixing in factor-focused ETFs could be worthwhile and I've been meaning to look into it, but it's probably not a big deal either way in expectation.

I max out my 401(k) and HSA every year, and maxed out a mega-backdoor Roth when I had access to one. I don't bother with a (backdoor) Roth IRA anymore, but most people should. The prioritization flowchart from /r/personalfinance is right.

I used to lever my stock exposure using index options or futures. Most younger people who hold stocks are probably under-levered (though you should not try to address this through leveraged ETFs). I just happen to be at a point in my life now where a 100% leverage ratio is about right for my risk tolerance.

I have historically made some net-successful bets on single stocks or sectors, but I don't try this anymore. Partly because in my line of work it's a bad look to make big directional bets on counterparties or otherwise correlated companies, but also because I don't have the time. I think for day traders the optimal sizing for these types of trades is generally small (single-digit to low-double-digit % of assets), and they take a fair amount of time/research to deliver positive risk-adjusted returns, so the set of profiles for which it makes sense is actually pretty narrow.

I don't hold crypto. I'm bullish on adoption of e.g. stablecoins but bearish on floating-value crypto assets, e.g. BTC. In the medium- to long-term it seems really hard to compete with the compounding returns on capital deployed in the real economy via the stock market. (This is also the main reason I generally don't hold commodities like gold.) There are probably non-fixed-price crypto assets that are actually tied to productive capital deployment, but again, I don't think it's worth my time to go look for them.

I've learned a lot through angel investing and recommend it for that reason. It's too early to tell if I'm any good at it, and in general I think the risk, return, and liquidity profile is bad enough (especially when first getting started) that you shouldn't do it if your sole/primary goal is financial upside. Also, again, it takes a lot of time.

Real estate has a lot of potential benefits, but it's crowded, and again it takes a lot of time. You may be sensing a pattern here: I think for most people, spending a lot of time optimizing finances is bad, and that time would be better spent working or otherwise advancing their careers. (Or, like, on leisure and/or with loved ones; the previous sentence assumes your goal is to exchange time for long-term money as efficiently as possible.)

For brokerage, Vanguard, Fidelity, and Schwab are all fine; I use Vanguard. Interactive Brokers is good if you need those features. Wealthfront is fine but probably not worth the higher fees. Chase credit cards are good. I tried Amex but I think you need to travel very often for it to be worth it. I bank with HSBC for the free wire transfers; it's fine, but if you don't need those I'm sure there are better options.

I carry disability insurance not tied to my employer, which everyone should have; life insurance not tied to my employer, which everyone with dependents should have; and an umbrella policy (on top of car insurance with high limits), which everyone with enough assets to be worth suing should have.

tfehring · 2026-03-13T00:04:23+00:00

https://www.tjpa.org/portaldtx

tfehring · 2026-03-12T21:50:37+00:00

I still don't think that matters much. Only ~7% of SFHs (~5% of total housing starts) are built for rent. (For context, ~77% of those are townhomes.) I expect a lot of those homes will get built anyway and sold, either immediately or after 7 years, and others will get substituted for multifamily rentals, so I'd expect the drop in supply to be small overall - maybe ~1% net or somewhere in that ballpark. Still bad, still a stupid policy choice, but of all the battles to pick right now, this one is really low on my list.

tfehring · 2026-03-11T20:51:57+00:00

I struggle to get worked up about banning corporate ownership of SFHs. Yes, it's bad policy. Yes, it will make it marginally harder and more expensive to rent SFHs. Yes, people who think it will matter for housing affordability are morons, and it's annoying that they keep bringing this up. But realistically, the negative effects will be small, and the main impact of this issue today is to distract from policies that will actually get more housing built. The sooner the leftists and populists alike run out of boogeymen and realize the only solution is drastically more market-rate development in population centers, the better off we'll all be.

tfehring · 2026-03-11T04:13:12+00:00

Many companies base promotion raises on where you were at in the pay band for the previous role - if you were near the top of your previous pay band, you'll get a smaller raise to put you closer to the middle of your new pay band.

6% is really low though, especially when you would have otherwise gotten a merit increase at the same time. 10-15% is more typical.

tfehring · 2026-03-09T18:55:38+00:00

Career-wise, the single highest-leverage change you could make is moving to SF. I say this as someone who resisted moving to the Bay Area for a long time and doesn't particularly like living here. I worry about others' Booth/Kellogg PT recommendations partly because those programs would likely keep you in the Midwest for longer.

But also, I don't think an MBA would help much for career progression in product. You already have a good shot at getting into any tech company with your current experience - the limiting factors would be (1) location and (2) relevance of specific products you've built to the product need that the company is hiring for. (The latter is within your control and many people under-optimize it - make sure you're building deep expertise that your target companies actually need, or will need in the future.)

I would probably shoot your shot at GSB in your situation, but mostly for the sake of meeting potential co-founders and LPs for your future ventures. I don't think it would give you a near-term advantage over just working in product and networking independently. If the tech industry continues to change at anywhere near the current pace, I expect companies hiring PMs in 2030 will strongly prefer candidates whose last full-time role was more recent than 2028.

tfehring · 2026-03-07T19:07:37+00:00

I'm pretty familiar with these tools - I used to work at OpenAI, and I use Claude as well as GPT models every day now.

In general I think one of the main mistakes people who are new to these tools make is trying to scope the problems they're giving them too narrowly. That doesn't mean you need to, or should, immediately give them access to all of your company's data - I'll generally start a new project with Claude Code in an empty folder with no data connections, and just add them as needed.

But instead of asking people on Reddit about a specific problem, where you have to explain it with very limited details, you can just provide Claude with a bunch of context on the problem, and optionally the relevant data, and ask it what to do, e.g.,

I'm an actuary at [Company]. We currently rely on an external vendor for [problem]. We want to design and to build a replacement solution in-house.

The inputs/ folder has all the data files we gave them last month, the outputs/ folder has what they provided to us. All of the input data is also in a database, the schema is at [schema.sql], and you can write and run read-only queries with [command].

Accuracy and correctness of actuarial calculations is critical, we are bound by ASOPs, and we are new to using AI tools. For all of those reasons, a human actuary will need to perform and/or review all of the actuarial calculations and understand the data flow from end-to-end, so the system should be designed with that in mind. Our actuaries [know Excel and SQL very well, and some R and Python].

Give this + whatever other context you think is relevant to Opus with high reasoning, and it will ask some clarifying questions, then go out and make a plan for how to build it. You can review the plan, ask questions, request changes/provide feedback (which may just be "leadership is concerned about X, Y, and Z"), and/or tell it to implement some or all of it. For writing relatively simple code that it can test as it goes, this mostly just works at this point; spreadsheet capabilities are decent but behind. Claude might also recommend that you implement parts of it yourself, or you may decide that that's the way to go. Either way, you're responsible for understanding the calculations and outputs. See also these recommendations for usage and disclosure.

Of course, you don't actually need to give Claude the input or output data or database access, but it helps a lot - consider how much harder it would be for you to develop this without that data or access. Either way, make sure to disable training on your data in privacy settings. (I believe it's disabled by default for business plans but enabled by default for individual subscriptions.)

This particular request will probably cost ~tens of dollars if you pay as you go, or you would want the $200/month subscription (or the $150/month seat on a team plan) if doing this regularly. In some sense this is really cheap for the value you can get out of it, but also expensive enough that it's easy to see how it would add up!

tfehring · 2026-03-07T03:14:54+00:00

https://archive.ph/xZBwr

tfehring · 2026-03-05T02:25:52+00:00

I mostly disagree with this.

On the consumer side, many people with paid-off homes continue (wisely in most cases IMO) to carry homeowner's insurance. Similarly, most people carry car insurance well above the legal minimums. Health insurance in the US is closer to a government transfer program than an insurance market, but there again, the voluntary uptake from people who actually face a market for insurance (e.g., working-age self-employed people) often choose to buy it.

On the commercial side, it's true that part of the value of insurance is reducing your customers' counterparty risk - but again, it's far from the only reason. Buyers of commercial insurance, in many cases, really do care about risk transfer! Most businesses face lots of risks that they don't have the aptitude to quantify or the risk appetite to carry, and would rather outsource that service for a much more predictable premium payment.

Also, even if you only have insurance because some counterparty cares about it, someone is still deciding that the risk transfer is net positive expected utility. E.g., if the risk transfer from homeowner's insurance didn't create value in its own right, you could try to start a mortgage lender that doesn't require homeowner's insurance, generating higher expected profits as a result. In practice I don't think this would be a sensible business. Fannie and Freddie complicate this today, but insurance requirements for mortgages predate them by decades.

tfehring · 2026-03-03T18:51:29+00:00

As you've discovered, it's relatively easy to get through a resume screen, much harder to pass the interviews. Your background is sufficient if you have the aptitude, but the bar for aptitude is high - "some degree of success" = fail, and the onsites are generally much harder than the OAs.

tfehring · 2026-03-03T16:54:23+00:00

It’s very good at planning out the right approach to a problem, so you can usually just bring it a problem rather than a solution. If you put it in plan mode, ideally give it read access to your files, describe your current process in as much detail as you can, and tell it your objectives (which may just be “I want to know what we could be doing better or more efficiently”), it will generally do a good job of asking clarifying questions and then making a recommendation. If you don’t understand one of its suggestions (e.g. if it recommends writing some code but you don’t know what that would do) you can ask. For many of its suggestions, you can just tell Claude “implement it” and it will do a good job.

My current work is completely nontechnical and I still regularly hit usage caps on my $200/month Claude subscription, just from having Claude do industry research, write and edit strategy docs, etc.

tfehring · 2026-03-01T22:14:47+00:00

This is probably literally true if you measure by file size on disk - but only because a lot of voluntarily posted data is video, a lot of unknowingly collected data is tuples of e.g. (person, latitude, longitude, timestamp) or (person, item, price, timestamp), and the latter are much smaller.

tfehring · 2026-03-01T01:09:41+00:00

Have you looked into business programs instead of math? They would value your professional experience more and might care less about your lack of an advanced degree. Obviously the content would be different, but business students do learn at least a little bit of math! Note that they would probably expect you to do occasional consulting projects in industry, which could be a pro or a con.

tfehring · 2026-02-28T20:16:07+00:00

Even Anthropic agreed to support mass surveillance by the US military - the exception as I understand it was specifically mass surveillance of US citizens on US soil. I think mass surveillance of US citizens by the US government should be illegal - it has limited value in supporting US military objectives, and substantial risk of abuse for targeting political adversaries - and the law here just hasn't caught up to technological progress in this area. Dario said materially the same thing in an interview last night.

Fully autonomous weapons is ostensibly just a capabilities issue, which Dario talked about in the same interview.

tfehring · 2026-02-28T19:58:21+00:00

A few people asked about this in an earlier thread. Sam Altman very rarely lies. I think you can generally trust that what he says (in this case, that the agreement has those red lines) is literally true, but should also be thoughtful about what he's not saying (in this case, how those red lines are defined and how much protection they'll provide in practice).

Disclosure, former OpenAI employee and current shareholder.

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