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Can you beat ensloppification? I made a quiz for Wikipedia's Signs of AI Writing

https://tryward.app/aiquiz
1•bennydog224•1m ago•1 comments

Spec-Driven Design with Kiro: Lessons from Seddle

https://medium.com/@dustin_44710/spec-driven-design-with-kiro-lessons-from-seddle-9320ef18a61f
1•nslog•1m ago•0 comments

Agents need good developer experience too

https://modal.com/blog/agents-devex
1•birdculture•2m ago•0 comments

The Dark Factory

https://twitter.com/i/status/2020161285376082326
1•Ozzie_osman•2m ago•0 comments

Free data transfer out to internet when moving out of AWS (2024)

https://aws.amazon.com/blogs/aws/free-data-transfer-out-to-internet-when-moving-out-of-aws/
1•tosh•3m ago•0 comments

Interop 2025: A Year of Convergence

https://webkit.org/blog/17808/interop-2025-review/
1•alwillis•5m ago•0 comments

Prejudice Against Leprosy

https://text.npr.org/g-s1-108321
1•hi41•5m ago•0 comments

Slint: Cross Platform UI Library

https://slint.dev/
1•Palmik•9m ago•0 comments

AI and Education: Generative AI and the Future of Critical Thinking

https://www.youtube.com/watch?v=k7PvscqGD24
1•nyc111•10m ago•0 comments

Maple Mono: Smooth your coding flow

https://font.subf.dev/en/
1•signa11•10m ago•0 comments

Moltbook isn't real but it can still hurt you

https://12gramsofcarbon.com/p/tech-things-moltbook-isnt-real-but
1•theahura•14m ago•0 comments

Take Back the Em Dash–and Your Voice

https://spin.atomicobject.com/take-back-em-dash/
1•ingve•15m ago•0 comments

Show HN: 289x speedup over MLP using Spectral Graphs

https://zenodo.org/login/?next=%2Fme%2Fuploads%3Fq%3D%26f%3Dshared_with_me%25253Afalse%26l%3Dlist...
1•andrespi•16m ago•0 comments

Teaching Mathematics

https://www.karlin.mff.cuni.cz/~spurny/doc/articles/arnold.htm
1•samuel246•18m ago•0 comments

3D Printed Microfluidic Multiplexing [video]

https://www.youtube.com/watch?v=VZ2ZcOzLnGg
2•downboots•18m ago•0 comments

Abstractions Are in the Eye of the Beholder

https://software.rajivprab.com/2019/08/29/abstractions-are-in-the-eye-of-the-beholder/
2•whack•19m ago•0 comments

Show HN: Routed Attention – 75-99% savings by routing between O(N) and O(N²)

https://zenodo.org/records/18518956
1•MikeBee•19m ago•0 comments

We didn't ask for this internet – Ezra Klein show [video]

https://www.youtube.com/shorts/ve02F0gyfjY
1•softwaredoug•20m ago•0 comments

The Real AI Talent War Is for Plumbers and Electricians

https://www.wired.com/story/why-there-arent-enough-electricians-and-plumbers-to-build-ai-data-cen...
2•geox•23m ago•0 comments

Show HN: MimiClaw, OpenClaw(Clawdbot)on $5 Chips

https://github.com/memovai/mimiclaw
1•ssslvky1•23m ago•0 comments

I Maintain My Blog in the Age of Agents

https://www.jerpint.io/blog/2026-02-07-how-i-maintain-my-blog-in-the-age-of-agents/
3•jerpint•23m ago•0 comments

The Fall of the Nerds

https://www.noahpinion.blog/p/the-fall-of-the-nerds
1•otoolep•25m ago•0 comments

Show HN: I'm 15 and built a free tool for reading ancient texts.

https://the-lexicon-project.netlify.app/
2•breadwithjam•28m ago•1 comments

How close is AI to taking my job?

https://epoch.ai/gradient-updates/how-close-is-ai-to-taking-my-job
1•cjbarber•28m ago•0 comments

You are the reason I am not reviewing this PR

https://github.com/NixOS/nixpkgs/pull/479442
2•midzer•30m ago•1 comments

Show HN: FamilyMemories.video – Turn static old photos into 5s AI videos

https://familymemories.video
1•tareq_•31m ago•0 comments

How Meta Made Linux a Planet-Scale Load Balancer

https://softwarefrontier.substack.com/p/how-meta-turned-the-linux-kernel
1•CortexFlow•31m ago•0 comments

A Turing Test for AI Coding

https://t-cadet.github.io/programming-wisdom/#2026-02-06-a-turing-test-for-ai-coding
2•phi-system•32m ago•0 comments

How to Identify and Eliminate Unused AWS Resources

https://medium.com/@vkelk/how-to-identify-and-eliminate-unused-aws-resources-b0e2040b4de8
3•vkelk•32m ago•0 comments

A2CDVI – HDMI output from from the Apple IIc's digital video output connector

https://github.com/MrTechGadget/A2C_DVI_SMD
2•mmoogle•33m ago•0 comments
Open in hackernews

Startup equity is worth more than you think

https://www.amafinance.org/startup_comp/
2•usaar333•6mo ago

Comments

random_savv•6mo ago
It’s interesting that the author thinks that the value of the shares is higher than the preferred price, even though employees typically hold common shares, meaning they get wiped out in most scenarios except best case. The expected (best case) growth is not an argument in favor of a 4x multiple on price. The chance of achieving that is baked into the price
usaar333•6mo ago
The value of the equity package is 4x higher than the FAANG equivalent equity package (at preferred/market pricing) - that's not the same as saying the shares themselves are worth that.

To sum up the arguments:

* Employment packages allow things a shareholder cannot do (functionally recall their investment), so the high volatility leads to higher package returns.

* FAANG equity grants (RSUs) are taxed at much higher rates

* Expected return is in fact higher on startup equity than FAANG equity (and you generally have no way to invest in the good startups directly aside from working for them).

inhumantsar•6mo ago
doesn't all of this assume that the startup reaches a liquidity event which favors the employee though? or at least that the startup is hot enough that there's a secondary market for those shares?

unless I'm misunderstanding the argument, I dont see how those hypothetical returns could be considered "expected returns". startups which reach a place where employees can profitably cash out seem far too rare to reasonably expect a return at all, never mind a large one.

Since a person works for one company at a time (usually), and it can take 3-5 years or more for a startup to reach a place where the equity is worth something, this argument reads to me like "the returns on a Powerball win are so much higher than your projected lifetime earnings that playing the lottery is a smart financial move".

usaar333•6mo ago
It's a probabilistic model. It assumes (correctly) that the low probability of a home run times the home run's valuation is quite large ("expected returns" in the probabilistic sense).

> this argument reads to me like "the returns on a Powerball win are so much higher than your projected lifetime earnings that playing the lottery is a smart financial move".

That's stronger claim than it is making, but yes in a sense it is saying the lottery can be a good move because the expectation is large - that's what VCs do after all.

Note that all the model aims to do is value the equity package. If a public company is offering more than what this model values the startup equity package as (and this often is the case!), it isn't worth it financially to work at that startup.

robocat•6mo ago
> Expected return is in fact higher on startup equity than FAANG equity

Expected return is extremely misleading because it depends strongly on extraordinarily few outlier winners. Like when Jeff Bezos walks into a bar and now the average wealth of every person in the bar is over a billion dollars.

The modal return of common shares is $0.

usaar333•6mo ago
Why is modal return so important? You'll work more than 2 jobs
robocat•6mo ago
Firstly, if your prior is that every previous startup failed, what does that say about your future chances of success?

Secondly, all the returns for YC are concentrated in a few companies. If you were in a winner then great, otherwise you most likely got $0 for your shares.

4% of YC companies become unicorns. How many startups do you need to work for before you become part of the 4%? That number is not a feasible number of jobs for one lifetime.

The modal return matters far more than the average return because you don't get to choose to be in an outlier.

The first article I checked said that 17 companies had IPOed for YC. Common shares often only get returns from an IPO. How many companies have gone through YC? What's the average number of companies you need to be part of before you get to be in one of the 17?

I'm using YC because the numbers are better for YC than most other VC or startups.

usaar333•6mo ago
> Firstly, if your prior is that every previous startup failed, what does that say about your future chances of success?

The prior is the market. It isn't sane to use your own prior experience. (Works both ways -- if your last startup did great, shouldn't assume next will).

> 4% of YC companies become unicorns. How many startups do you need to work for before you become part of the 4%? That number is not a feasible number of jobs for one lifetime.

The bar (and what the model is calculating) is Series A from top VC, not YC Seed funding. That significantly increases odds. Specifically, ~45% YC companies get Series A, so it's more like 10% chance of a YC Series A funded company becoming a unicorn (https://www.lennysnewsletter.com/p/pulling-back-the-curtain-...).

Model is change jobs every 18 months if not booming. A 1 in 10 chance is quite reasonable over a career.

I agree there is an issue with the event being too rare, but you can't just look only at modal returns. 2/3 chance of $0 (the modal return) and 1/3 chance of $10 million profit is still pretty good odds to work with.

robocat•6mo ago
> The prior is the market.

What a wierd statement. It matters not how well others do. In a winner takes most market, then only the median outcome matters ($0 usually).

I admit my statement about priors was unclear: I meant that your prior is a previous attempt with a startup. If you have influence and the startup fails then that is a signal about your ability to be successful working with your next startup.

> The bar (and what the model is calculating) is Series A

Common shares still have a median worth of $0 on series A.

> Model is change jobs every 18 months if not booming. A 1 in 10 chance is quite reasonable over a career.

I really doubt that. Someone has some historical stats that would show the truth either way. YC in particular haven't published any stats on median returns. I've only seen them mention average returns (heavily skewed by outlier winners). They have the data but they don't publish the modal return because they are VCs.

Common shares only return value for the rarer big successes. I also strongly suspect that there's a lot of historical bias. VCs play repeated games and are getting better at reducing the value of common shares to $0. It is an adversarial relationship: every dollar that common shares gain is a dollar that preferencial could have had if they played their game better.