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Vitamin D & Omega-3 have a larger ef­fect on de­pres­sion than an­ti­de­pres­sants

⏱ This post is over years old.

Proceed at own risk.

The “effect size” of an­ti­de­pres­sants on de­pres­sion, vs placebo, is around 0.4. (On av­er­age; some peo­ple re­spond much bet­ter or much worse.) This is like go­ing from a C to a C+.

In con­trast: the ef­fect size of 1500 mg/​day of “≥60% EPA” Omega-3 sup­ple­ments is a bit higher, around 0.6. This is like go­ing from a C to a B–. (With un­cer­tainty; at worst, Omega-3′s “only” on par with an­ti­de­pres­sants.)

But, much bet­ter: the ef­fect size of 5000 IU/day of Vitamin D is around 1.8. This is like go­ing from a C to an A–! (With un­cer­tainty; at worst, Vitamin D’s “only” twice as ef­fec­tive as an­ti­de­pres­sants.) This works even for peo­ple who don’t have a Vitamin D in­suf­fi­ciency, which al­most half of American adults do.

Even if you’re al­ready tak­ing Vitamin D & Omega-3, dou­ble check your dose: it may still not be enough! The of­fi­cial rec­om­men­da­tions are all too low, and re­cent re­search sug­gests even the of­fi­cial max­i­mum safe dose for Vitamin D is too low.

I know the “yay sup­ple­ments” genre of writ­ing is full of sloppy re­search & grifters, and you should be skep­ti­cal of my claim of easy wins, of “$100 bills lay­ing on the side­walk”. But there is good sci­ence among the trash, and pol­icy is of­ten decades be­hind sci­ence in any field, not just health.

So, Vitamin D & Omega-3: pos­si­bly high re­ward, for low risk. That’s a pos­i­tive “expected value” bet! These sup­ple­ments are safe, cheap, over-the-counter, and have pos­i­tive side-ef­fects (on Covid & cog­ni­tion). As al­ways, “ask your doc­tor”, show them the peer-re­viewed pa­pers cited in this post.

Unless you have spe­cific rea­sons to not take Vitamin D & Omega-3 — kid­ney stones, blood thin­ners, etc — please try them, for at least a month! They could save your men­tal health. Maybe even your life.

In Alicetown, the av­er­age per­son has 4 younger cousins.

In Bobtown, the av­er­age per­son has 3 younger cousins.

Alright, not so sur­pris­ing. You may not even no­tice a dif­fer­ence.

In Alicetown, the av­er­age per­son has 4 limbs.

In Bobtown, the av­er­age per­son has 3 limbs.

It’s the same ab­solute dif­fer­ence (4 vs 3) and rel­a­tive dif­fer­ence (3/4). So what makes limbs more sur­pris­ing than cousins? Well, partly it’s more dra­matic & vis­i­ble, but also be­cause: we ex­pect high vari­a­tion in the num­ber of some­one’s younger cousins, but not their num­ber of limbs.

This is why sci­en­tists cal­cu­late an “effect size” or “standardized mean dif­fer­ence” (“mean” = av­er­age). We take the dif­fer­ence be­tween two groups, then di­vide by the to­tal amount of vari­a­tion, to ac­count for how sur­pris­ing a dif­fer­ence is.

Unfortunately for laypeo­ple, the ef­fect size is usu­ally just re­ported as a num­ber, like “+0.74” for spac­ing out your study­ing vs cram­ming, or “–0.776″ for sleep de­pri­va­tion on at­ten­tion.

But what’s that mean? How can we make these num­bers in­tu­itive?

Well, a com­mon way for data to be is a bell-shaped curve (also called a “normal dis­tri­b­u­tion”). And most of us are, alas, well-ac­quainted with the bell curve in school grades. (“grading on a curve”)

So: school grades give us a use­ful way to think about stan­dard­ized ef­fect sizes! We can now con­vert that num­ber into an ac­tual let­ter grade:

For ex­am­ple: spac­ing out your study­ing, rel­a­tive to cram­ming, will on av­er­age lift your test scores from a C to a B–. (effect size = +0.74) And short-term sleep de­pri­va­tion, rel­a­tive to healthy sleep, will on av­er­age tank your abil­ity to pay at­ten­tion from a C to a D+. (effect size: –0.776)

But it’s not lim­ited to just grades & aca­d­e­mic per­for­mance. Effect sizes can also help us un­der­stand any kind of dif­fer­ence be­tween groups, in ob­ser­va­tion or in ex­per­i­ments!

Let’s use our school grade anal­ogy, to in­ter­pret ef­fect sizes on men­tal health:

What’s an “F in men­tal health”? By de­f­i­n­i­tion of a bell curve, ~2.3% of peo­ple are be­low –2 sigma (an “F”). (See: this bell curve cal­cu­la­tor.) In Canada, ~2.6% of peo­ple had sui­ci­dal ideation in 2022, while in the US, it was ~4.9% in 2019. So, it’s not too far off to say: “F in men­tal health = lit­er­ally sui­ci­dal”. (Also, re­minder that ~4% is 1-in-25 peo­ple. You likely know some­one, or are some­one, who will feel sui­ci­dal this year. Please reach out to your friends & loved ones!)

What’s a “D in men­tal health”? ~16% of peo­ple are be­low –1 sigma (a “D”) on a bell curve. The Keyes 2002 study es­ti­mated that ~14.1% of adults meet the DSM-III cri­te­ria for a ma­jor de­pres­sive episode. So, D = Depressed.

What’s an av­er­age “C in men­tal health”? ~68% of peo­ple are within a sigma of av­er­age (a “C”) on a bell curve. Same above study found that 56.6 per­cent had mod­er­ate men­tal health. They were nei­ther “languishing” nor “flourishing”. I guess C = Could Be Worse.

What’s a “B in men­tal health”? ~16% of peo­ple are above +1 sigma (a “B”) on a bell curve. Same above study found that 17.2% of adults are “flourishing”. Good for them! B = Flourishing, life is good.

What’s an “A in men­tal health”? I don’t know who these freaks are. I ac­tu­ally could not find any sci­en­tific stud­ies on “the +2 sigma in well-be­ing”. In con­trast, there’s lots of re­search on sui­ci­dal ideation, the –2 sigma in well-be­ing. In the ab­sence of any ac­tual data, I’ll just say: A = AWESOME

So, if an in­ter­ven­tion is found to have an ef­fect size of +1.0, that’s like go­ing up a let­ter grade. If some­thing’s found to have an ef­fect size of -2.0, that’s like go­ing down two let­ter grades. And so on.

Okay, so how do we get peo­ples’ “mental health grades” up?

Let’s look at an­ti­de­pres­sants, Omega-3, and Vitamin D, in turn:

The good news is they work. The bad news is they don’t work as well as you’d think they may work.

Cipriani et al 2018 is a meta-analy­sis: a study that col­lects & com­bines lots of pre­vi­ous stud­ies (that pass some ba­sic cri­te­ria, to min­i­mize a garbage-in-garbage-out sit­u­a­tion). While meta-analy­ses aren’t per­fect, it’s usu­ally bet­ter for “science com­mu­ni­ca­tors” like me to cite meta-analy­ses over in­di­vid­ual stud­ies, to re­duce the chance I’m cherry-pick­ing.

Anyway: this meta-analy­sis an­a­lyzes 522 tri­als with 116,477 par­tic­i­pants. All 21 an­ti­de­pres­sants they stud­ied were bet­ter than placebo (a pill that con­tains no ac­tive med­i­cine). The most ef­fec­tive an­ti­de­pres­sant, Amitriptyline, had an “Odds Ratio” of 2.13, which con­verts to an ef­fect size of 0.417, which is “small-medium” ac­cord­ing to Cohen’s rec­om­men­da­tions. Or, by our school-let­ter-grade com­par­i­son: the best an­ti­de­pres­sant would take your men­tal health grade from an F to F+, or C to C+.

From Figure 3 of that pa­per, you can see that Amitriptyline has the high­est es­ti­mated ef­fect size, while the side ef­fects are no worse than placebo:

But hang on, only F to F+ on av­er­age? How does that square with peo­ple’s per­sonal ex­pe­ri­ence that an­ti­de­pres­sants have been life­sav­ing?

Well, first: the av­er­age per­son has around 1 tes­ti­cle.

The punch­line be­ing ~50% of peo­ple have 2 tes­ti­cles while ~50% of peo­ple have 0 tes­ti­cles, hence the av­er­age is “around 1”. Likewise, the av­er­age ef­fect for the best an­ti­de­pres­sant is 0.4 — but some peo­ple re­spond much bet­ter to that… and some re­spond much worse.

And, sec­ond: the be­lief that things will get bet­ter is a pow­er­ful thing. Unfortunately, the power of hope gets a bad name in med­i­cine: “placebo”.

When you take any med­i­cine, you don’t just get (effect of med­i­cine). You get (effect of med­i­cine + ef­fect of placebo + ef­fect of time).

And what is the ef­fect of placebo? Amazingly, de­spite re­searchers hav­ing used place­bos for decades, it’s only re­cently that we started test­ing “open-label” place­bos: place­bos where we just tell the pa­tient it’s a placebo. We then com­pare “getting placebo” to “getting noth­ing”. The ef­fect size of open placebo, on stuff rang­ing from pain to de­pres­sion, is around 0.43. (Spille et al 2023)

That is: the ef­fect of (placebo vs noth­ing) is as strong as (the best an­ti­de­pres­sant vs placebo)! But again, I think “placebo” is an in­sult­ing word for the power of hope. Hope is­n’t magic, but it’s mea­sur­ably not-noth­ing. I as­sert: we should­n’t dis­miss such a con­nec­tion be­tween men­tal state & phys­i­cal health.

But any­way, for the rest of this ar­ti­cle, I’ll only be re­port­ing ef­fect sizes ver­sus placebo. Just re­mem­ber that the power of hope gives you an ex­tra +0.4 (like C to C+) for all in­ter­ven­tions.

Keep get­ting con­fused on which fat is what? Me too. So, here’s a crash course on var­i­ous fats:

Fatty acids are chains of car­bons & hy­dro­gens + two oxy­gens. They say “OOH” at one end, and “HHH” at the other end:

A sat­u­rated fatty acid is one where all the car­bons’ free spots are filled up with hy­dro­gens. (Hence, “saturated”) This makes the mol­e­cule stick straight out. This is why long sat­u­rated fatty acids — like those found in but­ter — tend to be solid at room tem­per­a­ture.

In con­trast, un­sat­u­rated fatty acids have at least one hy­dro­gen miss­ing. This causes them to have a dou­ble-bond “kink” in the mol­e­cule. This makes them not stick out, which is why un­sat­u­rated fats tend to be liq­uid at room tem­per­a­ture. Mono-unsaturated fatty acids (MUFAs) — like in olive oil — only have one kink. Poly-unsaturated fatty acids (PUFAs) — like in fatty fish — have two or more kinks. Let’s be ma­ture adults about this, please.

For com­plete­ness: trans fats are un­sat­u­rated fats whose “kink” is twisted around, caus­ing them to go straight. That is the worst sen­tence I’ve writ­ten all month. The twisted kink is caused by the hy­dro­gens be­ing on op­po­site sides, hence “trans”. (And yes, if they’re on the same side it’s “cis”. Latin was a mis­take.) The mol­e­cule be­ing straight is why trans fats — which mar­garine used to be full of — are solid at room tem­per­a­ture, de­spite be­ing an un­sat­u­rated fat.

It’s neat when­ever you can trace the his­tory of some­thing right down to its atoms! Margarine was first in­vented be­cause it’s cheaper, and is spread­able straight from the fridge, un­like but­ter. Margarine (used to be) made by tak­ing un­sat­u­rated veg­etable oils, which were cheaper than an­i­mal fats, then pump­ing a bunch of hy­dro­gens into it (hence, “hydrogenated oils”). If you com­pletely hy­dro­genate an oil, it be­comes a sat­u­rated fat. But they only par­tially hy­dro­genated those oils, lead­ing to trans fats, which were cheaper & a spread­able semi-solid at fridge tem­per­a­ture.

In the 1970s & 80s, the US Food & Drug Administration con­cluded that trans fats were not harm­ful to hu­mans, and nu­tri­tion­ists pro­moted mar­garine over but­ter, be­cause but­ter had “unhealthy” sat­u­rated fats. But in the early 1990s, sci­en­tists re­al­ized that trans fats were even worse for you than sat­u­rated fats. Only in the 2010′s, did most Western coun­tries start of­fi­cially ban­ning trans fats. Reminder: pol­icy is of­ten decades be­hind sci­ence.

I need to stop go­ing on in­fo­dump tan­gents. Anyway, Omega-3 is any fatty acid with its first kink at the 3rd car­bon from the Omega end (“HHH”), though it can have more kinks later down the chain. (And yes, Omega-6 has its first kink at the 6th car­bon, and Omega-9 has its first kink at the 9th car­bon. There’s noth­ing phys­i­cally pre­vent­ing Omega-4 or Omega-5′s from ex­ist­ing, but due to some quirk of evo­lu­tion, Omega-3, -6, and -9 are the ones bi­o­log­i­cal life uses most. As far as I can tell, there’s no spe­cific rea­son they’re all mul­ti­ples of 3. Probably just a co­in­ci­dence. There is a less com­mon Omega-7.)

Finally, there’s three main types of Omega-3: EPA (Eicosapentaenoic Acid), DHA (Docosahexaenoic Acid), and ALA (Alpha-Linolenic Acid). ALA is mostly found in plants like chia seeds & wal­nuts, while EPA & DHA mostly come from seafood, though there are al­gae-based ve­gan sources.

EPA & DHA are the fo­cus of this sec­tion. For bio-me­chan­i­cal rea­sons I don’t un­der­stand but I as­sume some­one else does: EPA is the one as­so­ci­ated with anti-in­flam­ma­tion, bet­ter brain health, and less de­pres­sion… while DHA is­n’t. (But DHA is still needed for other stuff, like your neu­rons’ cell walls, so don’t cut them out com­pletely!)

All the above info in a Venn (technically Euler) di­a­gram:

Okay, enough yap. Time for the ac­tual data:

Sublette et al 2011 is an older meta-analy­sis (15 tri­als with 916 par­tic­i­pants). It’s the only meta-analy­sis I could find that es­ti­mates the ac­tual “dose-response” curve, which shows: how much ef­fect, for how much treat­ment.

Why is dose-re­sponse im­por­tant? Because one prob­lem with many meta-analy­ses is they’ll do some­thing like: “Study 1 gave pa­tients 1 gram of med­i­cine and saw a +1 im­prove­ment in dis­ease, Study 2 gave 10 grams and saw +4 im­prove­ment, Study 3 gave 100 grams and saw neg­a­tive –5 im­prove­ment… the av­er­age of +1, +4, and –5 is zero… there­fore the med­i­cine’s ef­fect is zero.”

As men­tioned ear­lier, this is a mean­ing­less mean. That’s why we want to know the re­sponse at each dose.

Anyway, the Sublette meta-analy­sis gath­ered ran­dom­ized tri­als study­ing Omega-3 on de­pres­sion (vs placebo, of course) and got the fol­low­ing dose-re­sponse curve.⤵ Note that the hor­i­zon­tal axis is not just amount of to­tal Omega-3, but specif­i­cally the ex­tra amount of “unopposed” EPA, above the amount of DHA. Or in other words, “EPA mi­nus DHA”:

The top ef­fect size is around +0.558, which is like go­ing from an F to D–, or C to B–. You get this max­i­mum ef­fect around 1 to 2 grams of ex­tra EPA, and too much EPA gets worse re­sults. The meta-analy­sis finds that Omega-3 sup­ple­ments that are ~60% EPA (and the rest DHA) are op­ti­mal.

This find­ing is roughly in line with later meta-analy­ses. Liao et al 2019 also finds that ~1 gram of ≥60% EPA is best, but ac­tu­ally found a much higher ef­fect size: +1.03. Kelaiditis et al 2023 also finds 1 to 2g of ≥60% EPA is best, but found a lower ef­fect size of +0.43… which is still as good as the best an­ti­de­pres­sant!

Either way, let’s boil this down to a rec­om­men­da­tion. You want around 1 gram of EPA a day. So if your sup­ple­ments are 60% EPA, you need 1 gram ÷ 0.6 ~= 1.667 grams = 1667 mil­ligrams. Let’s round this down for con­ve­nience: get 1500 mg/​day of 60%-EPA Omega-3 sup­ple­ments.

In com­par­i­son, most of­fi­cial health or­ga­ni­za­tions rec­om­mend “250–500 mg com­bined EPA and DHA each day for healthy adults.” That is over three times too low, at least for op­ti­mal ef­fects on de­pres­sion. Which, as we cal­cu­lated above, is prob­a­bly around 1500 mg/​day. (The of­fi­cial safe dose is 5000 mg/​day)

Finally, a (small) study di­rectly in­ves­ti­gat­ing the link be­tween sui­cide & Omega-3. Sublette et al 2006: “Low [DHA] and low Omega-3 pro­por­tions […] pre­dicted risk of sui­ci­dal be­hav­ior among de­pressed pa­tients over the 2-year pe­riod.” Though keep in mind this is a small study, and it’s ob­ser­va­tional not ex­per­i­men­tal. Also, weird that con­trary to the above stud­ies on de­pres­sion, DHA pre­dicted sui­cide but not EPA. Not sure what to make of that.

Bonus: Omega-3 may also boost cog­ni­tion? Shahinfar et al 2025: “Enhancement of global cog­ni­tive abil­i­ties was ob­served with in­creas­ing omega-3 dosage up to 1500 mg/​day. [effect size = 1.00, like go­ing from a grade of C to B!], fol­lowed by down­ward trend at higher doses.”

Ghaemi et al 2024 is a meta-analy­sis on Vitamin D on de­pres­sion (31 tri­als with 24,189 par­tic­i­pants).

Again, it ac­tu­ally es­ti­mates a dose-re­sponse curve! Below is Figure 1 + Table 2, show­ing the ef­fect of Vitamin D dosage on de­pres­sion vs placebo. The solid line is the av­er­age es­ti­mated ef­fect, dashed lines are 95% con­fi­dence in­ter­val. Note the ef­fect size is neg­a­tive in this fig­ure, be­cause they’re mea­sur­ing re­duc­tion in de­pres­sive symp­toms:

The up­per range of un­cer­tainty is low­est at 5000 IU (International Units) of Vitamin D a day, with an es­ti­mated ef­fect size of 1.82, with a 95% un­cer­tainty range, from 0.98 to 2.66. An ef­fect size of 1.82 is like tak­ing your men­tal health from an F to a C–, or a C to an A–! And even in the most pes­simistic case, 0.98, that’s still over twice as ef­fec­tive as the top an­ti­de­pres­sant!

* The pa­per’s sum­mary says 8000 IU is best, with ef­fect size 2.04, but there’s much greater un­cer­tainty there.

* The pa­per also finds that longer stud­ies had smaller ef­fects than shorter stud­ies, but this does not nec­es­sar­ily mean Vitamin D’s ef­fects are short-lived. Looking at Supplementary Table 4, it seems this is partly be­cause longer stud­ies used lower av­er­age daily doses. (For ex­am­ple, one 52-week study only gave par­tic­i­pants 400 IU a day.)

* Other meta-analy­ses re­port lower ef­fects, be­cause they use “meaningless means”. If you have nine tri­als at 400 IU/day with ef­fect +0.5, and one trial at 4000 IU/day with ef­fect +1.5, your “average” ef­fect is +0.6. Again, that’s why I chose this meta-analy­sis: it es­ti­mates the ac­tual dose-re­sponse curve.

* Table 1 also shows that Vitamin D helps for both pa­tients us­ing an­ti­de­pres­sant med­ica­tion, and not. This is en­cour­ag­ing: it means you can stack both med­ica­tions & sup­ple­ments!

* Admittedly, Table 1 seems to im­ply that Vitamin D sup­ple­men­ta­tion did­n’t help par­tic­i­pants with­out Vitamin D de­fi­ciency, but:

You prob­a­bly are lack­ing Vitamin D: Liu et al 2018 finds that a bit un­der half of all adults (41.4%) have Vitamin D Insufficiency.

Looking at Supplementary Table 4, the tri­als whose par­tic­i­pants did­n’t have Vitamin D de­fi­ciency (understandably) used much lower doses. That’s prob­a­bly why they had a much lower ef­fect.

* You prob­a­bly are lack­ing Vitamin D: Liu et al 2018 finds that a bit un­der half of all adults (41.4%) have Vitamin D Insufficiency.

* Looking at Supplementary Table 4, the tri­als whose par­tic­i­pants did­n’t have Vitamin D de­fi­ciency (understandably) used much lower doses. That’s prob­a­bly why they had a much lower ef­fect.

The “official” rec­om­men­da­tions are all too low:

So, if this meta-analy­sis is right, then 5000 IU/day is around op­ti­mal. But the of­fi­cial rec­om­men­da­tion for Vitamin D is 400–800 IU/day, over six times too low. 5000 IU/day is even higher than the “official max­i­mum safe dose”, of 4000 IU/day! But McCullough et al 2019 gave over thou­sands of pa­tients 5,000 to 10,000 IU/day, for seven years, and there were zero cases of se­ri­ous side ef­fects. This matches later stud­ies like Billington et al 2020, a 3-year-long dou­ble-blinded ran­dom­ized trial, which found “the safety pro­file of vi­t­a­min D sup­ple­men­ta­tion is sim­i­lar for doses of 400, 4000, and 10,000 IU/day.” (Although 15 par­tic­i­pants got “mild hy­per­cal­cemia”, but “all cases re­solved on re­peat test­ing.” Either way, that’s a small cost for re­duc­ing the risk of ma­jor de­pres­sion & sui­cide.)

And it makes evo­lu­tion­ary sense that 10,000 IU a day should be safe. Your skin, ex­posed to the Sun’s ul­tra­vi­o­let rays, can syn­the­size up to (the equiv­a­lent of) 10,000 IU a day, be­fore plateau­ing out. Source is Vieth 1999: “Because vi­t­a­min D is po­ten­tially toxic, in­take of [1000 IU/day] has been avoided even though the weight of ev­i­dence shows that the cur­rently ac­cepted [limit] of [2000 IU/day] is too low by at least 5-fold.”

Speaking of the Sun, why take sup­ple­ments in­stead of just get­ting Vitamin D from sun ex­po­sure? Well, skin can­cer. But also: be­cause Sun-Skin D varies greatly de­pend­ing on the sea­son, your lat­i­tude, and your skin type. There’s less ul­tra­vi­o­let rays from the Sun in win­ter/​fall, and at lat­i­tudes fur­ther from the equa­tor. And the darker your skin is, the less Vitamin D your skin makes for the same amount of Sun ex­po­sure. As ex­pected from the bio-physics of skin, Black adults have the high­est preva­lence of Vitamin D de­fi­ciency (82.1%!!), fol­lowed by Hispanic adults (62.9%). (But hey, at least Black adults have the low­est in­ci­dence of skin can­cer. You win some you lose some.) The point is: speak­ing as some­one with Southeast Asian skin, who’s cur­rently in Canada dur­ing win­ter… even if I stood out­side naked for hours, I’d get ap­prox­i­mately zero IU/day of Vitamin D from the Sun. Thus: sup­ple­ments.

Direct ef­fect on sui­cide: Finally, a meta-analy­sis di­rectly mea­sur­ing the ef­fect of Vitamin D on sui­ci­dal be­hav­iour. Yu et al 2025: “Vitamin D in pa­tients with [suicidal be­hav­iours] were sig­nif­i­cantly lower than in con­trols (standardized mean dif­fer­ence: –0.69, or a ‘medium’ dif­fer­ence)”. Reminder that this pa­per by it­self only mea­sures cor­re­la­tion, not cau­sa­tion — but com­bined with the above ex­per­i­ments of Vitamin D on de­pres­sion, I think it’s rea­son­able to guess it’s partly causal.

* Almost half of you have a Vitamin D de­fi­ciency ac­cord­ing to the of­fi­cial rec­om­men­da­tion (800 IU/day).

* And the of­fi­cial rec­om­men­da­tion is way too low. Even the of­fi­cial max­i­mum safe dose (4000 IU/day) is be­low the op­ti­mal Vitamin D for de­pres­sion (5000 IU/day) or what your body can pro­duce from the Sun in op­ti­mal con­di­tions (10,000 IU/day). Recent ran­dom­ized con­trolled tri­als con­firm that 10,000 IU/day is, in­deed, mostly safe.

* And even if you do 3000 IU/day, well be­low the max safe limit, the ex­pected ef­fect is still bet­ter than the best an­ti­de­pres­sant, even on the pes­simistic end of the es­ti­mate!

* Reminder that of­fi­cial pol­icy is of­ten decades be­hind the sci­ence.

* Reminder that I’m not say­ing “take sup­ple­ments in­stead of an­ti­de­pres­sants”; in fact the above meta-analy­sis shows you can ef­fec­tively stack them!

Bonus: Vitamin D sup­ple­men­ta­tion was found in sev­eral ran­dom­ized con­trolled tri­als to re­duce mor­tal­ity from Covid-19, though much less than of­fi­cial treat­ments like Paxlovid. Vitamin D also prob­a­bly helps guard against in­fluenza too, though the ev­i­dence is small & early.

Scurvy is caused by a lack of Vitamin C. It’s a con­di­tion that causes your wounds to re-open up & teeth to fall out. Scurvy used to kill al­most half(!) of all sailors on ma­jor ex­pe­di­tions; it’s es­ti­mated mil­lions died. It can be cured by eat­ing lemons.

Rickets is mostly caused by a lack of Vitamin D. It’s a con­di­tion where kids’ bones go all soft and de­formed. During the Industrial Revolution, up to 80% of kids suf­fered from it. It can be pre­vented with cod liver oil.

Goiters is mostly caused by a lack of Iodine. It’s a con­di­tion where the thy­roid gland in your neck swells up painfully, to the size of an ap­ple. During WWI, a third of adult men had goi­ters. It can be pre­vented with iodized salt.

About 1 in 4 peo­ple are ex­pected to have clin­i­cal de­pres­sion some­time in their life. Depression is the #1 source of the global “burden from dis­ease” in the men­tal health cat­e­gory, and that cat­e­gory is the #6 bur­den of dis­ease in the world, above Alzheimer’s, malaria, and sex­u­ally trans­mit­ted in­fec­tions.

The ef­fec­tive al­tru­ists are all, “woah for just $3000 you can pre­vent a child’s death from malaria” — and that’s great! save them kids! — but where’s the fan­fare for the ac­cu­mu­lat­ing ev­i­dence that, “woah with cheap daily sup­ple­ments we can save mil­lions from sui­cide & de­pressed lives”?

Over and over again through­out his­tory, some hor­rific thing that caused mil­lions to suf­fer, turned out to be “yeah you were miss­ing this one mol­e­cule lol”. To be clear: not every­thing is gonna be that sim­ple, and men­tal health is not “just” chem­istry. Also, all the num­bers on this page have with large er­ror bars & un­cer­tainty, more re­search is needed.

But, as of right now, I feel I can at least con­fi­dently claim the fol­low­ing:

“[Nvidia CEO] Jensen Huang Is Begging You to Stop Being So Negative About AI” — Headline from Gizmodo

Guys, enough is enough. Bullying is a se­ri­ous is­sue, and it’s time for me to speak out. There’s an ex­tremely hurt­ful nar­ra­tive go­ing around that my prod­uct, a rev­o­lu­tion­ary new tech­nol­ogy that ex­ists to scam the el­derly and make you dis­trust any­thing you see on­line, is harm­ful to so­ci­ety. This slan­der is to­tally un­war­ranted, and I would re­ally ap­pre­ci­ate it if every­one would stop be­ing so mean about this thing I just in­vested a bil­lion dol­lars in.

As some­one who des­per­ately needs this tech­nol­ogy to work out, I can hon­estly say it is the most es­sen­tial tool ever cre­ated in all of hu­man his­tory. Don’t mer­ci­lessly ridicule it just be­cause it steals the joy out of your hob­bies and cre­ates sex­u­ally ex­plicit im­ages of women with­out their con­sent. Seriously, please stop! It re­ally hurts my feel­ings.

It’s easy to throw stones if you think about the job dis­place­ment and eco­log­i­cal de­struc­tion caused by this point­less tech­nol­ogy. But such black-and-white, not-want­ing-bil­lion­aires-to-get-richer think­ing is, quite frankly, cruel. You can’t just mea­sure the value of some­thing in terms of “whether or not it makes every­thing worse for every­one.” The world is much more com­pli­cated than that.

This tech­nol­ogy is go­ing to fuel in­no­va­tion across in­dus­tries and solve all prob­lems of fem­i­nism and equal rights. Yes, it’s ex­pand­ing the sur­veil­lance state, and yes, it’s de­stroy­ing the ed­u­ca­tion sys­tem, and yes, it’s be­ing trained on copy­righted work with­out per­mis­sion, and yes, it’s be­ing used to cre­ate lethal au­tonomous weapons sys­tems that can iden­tify, tar­get, and kill with­out hu­man in­put, but… I for­get my point, but ul­ti­mately, I think you should em­brace it.

Lately, I feel like I just can’t win with you guys. Please, just use my evil tech­nol­ogy. What’s so wrong with that? Just use it. I’m beg­ging you. I want to con­tinue liv­ing my im­moral tech­no­fas­cist life with­out any crit­i­cism.

The first im­ages from the Meteosat Third Generation-Sounder satel­lite have been shared at the European Space Conference in Brussels, show­ing how the mis­sion will pro­vide data on tem­per­a­ture and hu­mid­ity, for more ac­cu­rate weather fore­cast­ing over Europe and north­ern Africa.

The im­ages from Meteosat Third Generation-Sounder (MTG-S) show a full-disc im­age of Earth as seen from geo­sta­tion­ary or­bit, about 36 000 km above Earth’s sur­face. These im­ages were cap­tured on 15 November 2025 by the satel­lite’s Infrared Sounder in­stru­ment. In the ‘temperature’ im­age (below), the Infrared Sounder used a long-wave in­frared chan­nel, which mea­sured Earth’s sur­face tem­per­a­ture as well as the tem­per­a­ture at the top of clouds. Dark red cor­re­sponds to high tem­per­a­tures, mainly on the warmer land sur­faces, while blue cor­re­sponds to lower tem­per­a­tures, typ­i­cally on the top of clouds.As would be ex­pected, most of the warmest (dark red) ar­eas in this im­age are on the con­ti­nents of Africa and South America. In the top-cen­tre of the im­age, the out­line of the coast of west­ern Africa is clearly vis­i­ble in dark red, with the Cape Verde penin­sula, home to Senegal’s cap­i­tal Dakar, vis­i­ble as among the warmest ar­eas in this im­age. In the bot­tom-right of the im­age, the west­ern coast of Namibia and South Africa are also vis­i­ble in red be­neath a swirl of cold cloud shown in blue, while the north­east coast of Brazil is vis­i­ble in dark red on the left of the im­age.

The ‘humidity’ im­age (below) was cap­tured us­ing the Infrared Sounder’s medium-wave in­frared chan­nel, which mea­sures hu­mid­ity in Earth’s at­mos­phere. Blue colours cor­re­spond to re­gions in the at­mos­phere with higher hu­mid­ity, while red colours cor­re­spond to lower hu­mid­ity in the at­mos­phere.The out­lines of land­masses are not vis­i­ble in this im­age. The ar­eas of least at­mos­pheric hu­mid­ity, shown in dark red, are seen ap­prox­i­mately over the Sahara Desert and the Middle East (top of im­age), while a large area of ‘dry’ at­mos­phere also cov­ers part of the South Atlantic Ocean (centre of im­age). Numerous patches of high hu­mid­ity are seen in dark blue over the east­ern part of the African con­ti­nent as well as in high and low lat­i­tudes.

Below we see a close-up from MTG-Sounder of the European con­ti­nent and part of north­ern Africa. Like the first im­age above, here we see heat from land sur­faces and tem­per­a­tures at the top of clouds. The heat from the African con­ti­nent is seen in red in the lower part of the im­age, while a dark blue weather front cov­ers Spain and Portugal. The Italian penin­sula is in the cen­tre of the im­age.

Temperatures over Europe and north­ern Africa by MTG-Sounder

And the an­i­ma­tion (below) uses data from the MTG-Sounder satel­lite to track the erup­tion of Ethiopia’s Hayli Gubbi vol­cano on 23 November 2025. The back­ground im­agery shows sur­face tem­per­a­ture changes while in­frared chan­nels high­light the de­vel­op­ing ash plume. The satel­lite’s timely ob­ser­va­tions en­able track­ing of the evolv­ing ash plume over time.

MTG is a world-class Earth ob­ser­va­tion mis­sion de­vel­oped by the European Space Agency (ESA) with European part­ners to ad­dress sci­en­tific and so­ci­etal chal­lenges. The mis­sion pro­vides game-chang­ing data for fore­cast­ing weather and air qual­ity over Europe.The satel­lite’s geo­sta­tion­ary po­si­tion above the equa­tor means it main­tains a fixed po­si­tion rel­a­tive to Earth, fol­low­ing the same area on the plan­et’s sur­face as we ro­tate. This en­ables it to pro­vide cov­er­age of Europe and part of north­ern Africa on a 15-minute re­peat cy­cle. It sup­plies new data on tem­per­a­ture and hu­mid­ity over Europe every 30 min­utes, sup­ply­ing me­te­o­rol­o­gists with a com­plete weather pic­ture of the re­gion and com­ple­ment­ing data on cloud for­ma­tion and light­ning from the MTG-Imager (MTG-I) satel­lite.

ESA’s Director of Earth Observation Programmes, Simonetta Cheli, said, “Seeing the first Infrared Sounder im­ages from the MTG-Sounder satel­lite re­ally brings this mis­sion and its po­ten­tial to life. We ex­pect data from this mis­sion to change the way we fore­cast se­vere storms over Europe — and this is very ex­cit­ing for com­mu­ni­ties and cit­i­zens, as well as for me­te­o­rol­o­gists and cli­ma­tol­o­gists. As ever, the out­stand­ing work done by our teams in col­lab­o­ra­tion with long-stand­ing part­ners, in­clud­ing Eumetsat, the European Commission and dozens of European in­dus­try teams, means we now have the abil­ity to pre­dict ex­treme weather events in more ac­cu­rate and timely ways than ever be­fore.”The Infrared Sounder in­stru­ment on board MTG-S is the first European hy­per­spec­tral sound­ing in­stru­ment in geo­sta­tion­ary or­bit. It is de­signed to gen­er­ate a com­pletely new type of data prod­uct. It uses in­ter­fer­o­met­ric tech­niques, which analyse minis­cule pat­terns in light waves, to cap­ture data on tem­per­a­ture and hu­mid­ity, as well as be­ing able to mea­sure wind and trace gases in the at­mos­phere. The data will even­tu­ally be used to gen­er­ate three-di­men­sional maps of the at­mos­phere, help­ing to im­prove the ac­cu­racy of weather fore­cast­ing, es­pe­cially for now­cast­ing rapidly evolv­ing storms.“It’s fan­tas­tic to see the first im­ages from this ground­break­ing mis­sion,” said James Champion, ESA’s MTG Project Manager. “This satel­lite has been 15 years in de­vel­op­ment and will rev­o­lu­tionise weather fore­cast­ing and es­pe­cially now­cast­ing. The abil­ity to ver­ti­cally pro­file the full Earth’s disk with a re­peat cy­cle of only 30 min­utes for Europe is an in­cred­i­ble ac­com­plish­ment!”

“I’m ex­cited that we can share these first im­ages from the Infrared Sounder, which show­case just a small se­lec­tion of the 1700 in­frared chan­nels con­tin­u­ously ac­quired by the in­stru­ment as it ob­serves Earth,” said Pieter Van den Braembussche, MTG System and Payload Manager at ESA. “By com­bin­ing all 1700 chan­nels, we will soon be able to gen­er­ate three di­men­sional maps of tem­per­a­ture, hu­mid­ity and even trace gases in the at­mos­phere. This ca­pa­bil­ity will of­fer a com­pletely new per­spec­tive on Earth’s at­mos­phere, not pre­vi­ously avail­able in Europe, and is ex­pected to help fore­cast­ers pre­dict se­vere storms ear­lier than is pos­si­ble to­day.”

The MTG mis­sion cur­rently has two satel­lites in or­bit: MTG-I and MTG-S. The sec­ond Imager will be launched later in 2026.MTG-S was launched on 1 July 2025. Thales Alenia Space is the prime con­trac­tor for the over­all MTG mis­sion, with OHB Systems re­spon­si­ble for the MTG-Sounder satel­lite. Mission con­trol and data dis­tri­b­u­tion are man­aged by Eumetsat.The MTG-S satel­lite also hosts the Copernicus Sentinel-4 mis­sion, which con­sists of an ul­tra­vi­o­let, vis­i­ble and near-in­frared (UVN) imag­ing spec­trom­e­ter. Sentinel-4 de­liv­ered its first im­ages last year.

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Tesla CEO Elon Musk said on Wednesday that the au­tomaker is end­ing pro­duc­tion of its Model S and X ve­hi­cles, and will use the fac­tory in Fremont, California, to build Optimus hu­manoid ro­bots.

“It’s time to ba­si­cally bring the Model S and X pro­grams to an end with an hon­or­able dis­charge,” Musk said on the com­pa­ny’s fourth-quar­ter earn­ings call. “If you’re in­ter­ested in buy­ing a Model S and X, now would be the time to or­der it.”

After the orig­i­nal Roadster, the two mod­els are Tesla’s old­est ve­hi­cles, and in re­cent years the com­pany has slashed prices as global com­pe­ti­tion for elec­tric ve­hi­cles has soared. Tesla started sell­ing the Model S sedan in 2012, and the Model X SUV three years later.

On Tesla’s web­site, the Model S cur­rently starts at about $95,000, while the Model X starts at around $100,000

Tesla’s far more pop­u­lar mod­els are the 3 and Y, which ac­counted for 97% of the com­pa­ny’s 1.59 mil­lion de­liv­er­ies last year. The Model 3 now starts at about $37,000, and the Model Y is around $40,000. Tesla de­buted more af­ford­able ver­sions of the ve­hi­cles late last year.

In its earn­ings an­nounce­ment on Wednesday, Tesla re­ported its first an­nual rev­enue de­cline on record, with sales falling in three of the past four quar­ters. Musk has been try­ing to turn at­ten­tion away from tra­di­tional EVs and to­ward a fu­ture of dri­ver­less cars and hu­manoid ro­bots, ar­eas where the com­pany cur­rently has vir­tu­ally no busi­ness.

The goal of this tracker is to de­tect sta­tis­ti­cally sig­nif­i­cant degra­da­tions in Claude Code with Opus 4.5 per­for­mance on SWE tasks. What you see is what you get: We bench­mark in Claude Code CLI with the SOTA model (currently Opus 4.5) di­rectly, no cus­tom har­nesses.

Shows if any time pe­riod has a sta­tis­ti­cally sig­nif­i­cant per­for­mance drop (p < 0.05).

Historical av­er­age pass rate used as ref­er­ence for de­tect­ing per­for­mance changes.

Percentage of bench­mark tasks passed in the most re­cent day’s eval­u­a­tions.

Aggregate pass rate over the last 7 days. Provides a more sta­ble mea­sure than daily re­sults.

Aggregate pass rate over the last 30 days. Best mea­sure of over­all sus­tained per­for­mance.

Daily bench­mark pass rates over the past 30 days. Hover over leg­end items for de­tails on each vi­sual el­e­ment.

Daily bench­mark pass rate show­ing the per­cent­age of tasks solved each day.

Historical av­er­age pass rate (58%) used as ref­er­ence for de­tect­ing per­for­mance changes.

Shaded re­gion around base­line (±14.0%). Changes within this band are not sta­tis­ti­cally sig­nif­i­cant (p ≥ 0.05).

95% con­fi­dence in­ter­val for each data point. Toggle check­box to show/​hide. Wider in­ter­vals in­di­cate more un­cer­tainty (fewer sam­ples).

Historical av­er­age pass rate (58%) used as ref­er­ence for de­tect­ing per­for­mance changes.

Shaded re­gion around base­line (±5.6%). Changes within this band are not sta­tis­ti­cally sig­nif­i­cant (p ≥ 0.05).

95% con­fi­dence in­ter­val for each data point. Toggle check­box to show/​hide. Wider in­ter­vals in­di­cate more un­cer­tainty (fewer sam­ples).

The goal of this tracker is to de­tect sta­tis­ti­cally sig­nif­i­cant degra­da­tions in Claude Code with Opus 4.5 per­for­mance on SWE tasks. We are an in­de­pen­dent third party with no af­fil­i­a­tion to fron­tier model providers.

Context: In September 2025, Anthropic pub­lished a

post­mortem on Claude degra­da­tions. We want to of­fer a re­source to de­tect such degra­da­tions in the fu­ture.

We run a daily eval­u­a­tion of Claude Code CLI on a cu­rated, con­t­a­m­i­na­tion-re­sis­tant sub­set of

SWE-Bench-Pro. We al­ways use the lat­est avail­able Claude Code re­lease and the SOTA model (currently Opus 4.5). Benchmarks run di­rectly in Claude Code with­out cus­tom har­nesses, so re­sults re­flect what ac­tual users can ex­pect. This al­lows us to de­tect degra­da­tion re­lated to both model changes and har­ness changes.

Each daily eval­u­a­tion runs on N=50 test in­stances, so daily vari­abil­ity is ex­pected. Weekly and monthly re­sults are ag­gre­gated for more re­li­able es­ti­mates.

We model tests as Bernoulli ran­dom vari­ables and com­pute 95% con­fi­dence in­ter­vals around daily, weekly, and monthly pass rates. Statistically sig­nif­i­cant dif­fer­ences in any of those time hori­zons are re­ported.

Get no­ti­fied when degra­da­tion is de­tected We’ll email you when we de­tect a sta­tis­ti­cally sig­nif­i­cant per­for­mance drop. Thanks for sub­scrib­ing! Check your email to con­firm. Something went wrong. Please try again.

The UK Government re­cently un­veiled its ‘AI Skills Hub’, which wants to pro­vide 10 mil­lion work­ers with AI skills by 2030. The main site was de­liv­ered by PwC for the low, low price of.. £4.1 mil­lion (~$5,657,000).

It is not good. Like, at all - the UI is in­sanely bad and it’s clear that this was just a vibecoded site (to be fair, this is the AI Skills Hub, but c’­mon, where is the pride in your work? I would be ashamed to even re­lease this as a pro­to­type!)

PwC did­n’t even write any of the course con­tent! The only thing the Skills Hub does is link out to ex­ter­nal pages, like Salesforce’s free Trailhead learn­ing plat­form:

Note that I’m fairly cer­tain this course al­ready ex­isted be­fore the con­tract was even awarded, so all the site does is.. link out to other sites?

PwC it­self also ad­mits that the site does not prop­erly meet ac­ces­si­bil­ity stan­dards:

Even for those with­out a dis­abil­ity, the lack of here in this re­gard means that the site can be very con­fus­ing and buggy as a re­sult.

The site has a course on “AI and in­tel­lec­tual prop­erty”. One thing it men­tions is fair use:

Except that fair use is not a thing in the UK - that’s a US con­cept! The UK uses what’s known as “fair deal­ing”, which is more re­stric­tive than fair use, so the de­tails here are plain wrong.

The in­ter­face for this web­site has also not been clearly thought out - one glar­ing ex­am­ple is the process of ac­tu­ally en­rolling in a course.

On the course page, the “Enroll Now” but­ton is tiny, and if you don’t see it and try scrolling down to the bot­tom, you will find your­self noth­ing but a com­ment sec­tion!

Then you have other bugs too, like the “Skills & Training Gap Analysis” - which is linked at the top of the site! - ap­par­ently be­ing closed off to the pub­lic for no rea­son:

To be hon­est, see­ing this made me an­gry.

I’m an­gry at the sheer waste­ful­ness of the UK Government here. Our pub­lic ser­vices are col­laps­ing - while £4 mil­lion is ad­mit­tedly chump change for the UK gov­ern­ment, there are real peo­ple be­hind these num­bers - fam­i­lies wait­ing months for NHS ap­point­ments, chil­dren in crum­bling schools, vul­ner­a­ble peo­ple not get­ting the care they need. The waste feels par­tic­u­larly galling when you re­alise that al­most no one will ac­tu­ally use this site!

I’m also an­gry that the small web­dev busi­nesses we have here in the UK were left out of this - for less than 5% of the cost, we’d have a bet­ter web­site and help out small busi­nesses who ac­tu­ally care about their work, in­stead of hand­ing the pro­ject to a multi­na­tional com­pany that made nearly $60 bil­lion in rev­enue in a year and has zero qualms about rip­ping off the British tax­payer.

A reader sent me an­other “AI Delivery” site from the gov­ern­ment, that was also AI gen­er­ated. This one is ad­mit­tedly a fair bit bet­ter — for one thing, we did­n’t pay £4.1 mil­lion for it! — but have some pride in your work, for good­ness sake!

Diagrams are es­sen­tial for AI-assisted pro­gram­ming. When you’re work­ing with an AI cod­ing as­sis­tant, be­ing able to vi­su­al­ize data flows, state ma­chines, and sys­tem ar­chi­tec­ture—di­rectly in your ter­mi­nal or chat in­ter­face—makes com­plex con­cepts in­stantly gras­pable.

Mermaid is the de facto stan­dard for text-based di­a­grams. It’s bril­liant. But the de­fault ren­derer has prob­lems:

* Aesthetics — Might be per­sonal pref­er­ence, but wished they looked more pro­fes­sional

* No ter­mi­nal out­put — Can’t ren­der to ASCII for CLI tools

* Heavy de­pen­den­cies — Pulls in a lot of code for sim­ple di­a­grams

We built beau­ti­ful-mer­maid at Craft to power di­a­grams in Craft Agents. It’s fast, beau­ti­ful, and works every­where—from rich UIs to plain ter­mi­nals.

The ASCII ren­der­ing en­gine is based on mer­maid-ascii by Alexander Grooff. We ported it from Go to TypeScript and ex­tended it Thank you Alexander for the ex­cel­lent foun­da­tion! (And in­spi­ra­tion that this was pos­si­ble.)

* 15 built-in themes — And dead sim­ple to add your own

* Full Shiki com­pat­i­bil­ity — Use any VS Code theme di­rectly

npm in­stall beau­ti­ful-mer­maid

# or

bun add beau­ti­ful-mer­maid

# or

pnpm add beau­ti­ful-mer­maid

im­port { ren­der­Mer­maid } from ‘beautiful-mermaid’

const svg = await ren­der­Mer­maid(`

graph TD

A[Start] –> B{Decision}

B –>|Yes| C[Action]

B –>|No| D[End]

im­port { ren­der­Mer­maid­Ascii } from ‘beautiful-mermaid’

const ascii = ren­der­Mer­maid­Ascii(`graph LR; A –> B –> C`)

Also avail­able via js­De­livr. The bun­dle ex­poses ren­der­Mer­maid, ren­der­Mer­maid­Ascii, THEMES, DEFAULTS, and fromShikiTheme on the global beau­ti­ful­Mer­maid ob­ject.

The them­ing sys­tem is the heart of beau­ti­ful-mer­maid. It’s de­signed to be both pow­er­ful and dead sim­ple.

Every di­a­gram needs just two col­ors: back­ground (bg) and fore­ground (fg). That’s it. From these two col­ors, the en­tire di­a­gram is de­rived us­ing color-mix():

const svg = await ren­der­Mer­maid(di­a­gram, {

bg: ‘#1a1b26’, // Background

fg: ‘#a9b1d6’, // Foreground

This is Mono Mode—a co­her­ent, beau­ti­ful di­a­gram from just two col­ors. The sys­tem au­to­mat­i­cally de­rives:

For richer themes, you can pro­vide op­tional “enrichment” col­ors that over­ride spe­cific de­riva­tions:

const svg = await ren­der­Mer­maid(di­a­gram, {

bg: ‘#1a1b26’,

fg: ‘#a9b1d6’,

// Optional en­rich­ment:

line: ‘#3d59a1’, // Edge/connector color

ac­cent: ‘#7aa2f7’, // Arrow heads, high­lights

muted: ‘#565f89’, // Secondary text, la­bels

sur­face: ‘#292e42’, // Node fill tint

bor­der: ‘#3d59a1’, // Node stroke

If an en­rich­ment color is­n’t pro­vided, it falls back to the color-mix() de­riva­tion. This means you can pro­vide just the col­ors you care about.

All col­ors are CSS cus­tom prop­er­ties on the el­e­ment. This means you can switch themes in­stantly with­out re-ren­der­ing:

// Switch theme by up­dat­ing CSS vari­ables

svg.style.set­Prop­erty(‘–bg’, ‘#282a36’)

svg.style.set­Prop­erty(‘–fg’, ‘#f8f8f2’)

// The en­tire di­a­gram up­dates im­me­di­ately

15 care­fully cu­rated themes ship out of the box:

im­port { ren­der­Mer­maid, THEMES } from ‘beautiful-mermaid’

const svg = await ren­der­Mer­maid(di­a­gram, THEMES[‘tokyo-night’])

Creating a theme is triv­ial. At min­i­mum, just pro­vide bg and fg:

const myTheme = {

bg: ‘#0f0f0f’,

fg: ‘#e0e0e0’,

const svg = await ren­der­Mer­maid(di­a­gram, myTheme)

Want richer col­ors? Add any of the op­tional en­rich­ments:

const myRichTheme = {

bg: ‘#0f0f0f’,

fg: ‘#e0e0e0’,

ac­cent: ‘#ff6b6b’, // Pop of color for ar­rows

muted: ‘#666666’, // Subdued la­bels

Use any VS Code theme di­rectly via Shiki in­te­gra­tion. This gives you ac­cess to hun­dreds of com­mu­nity themes:

im­port { getS­in­gle­ton­High­lighter } from ‘shiki’

im­port { ren­der­Mer­maid, fromShikiTheme } from ‘beautiful-mermaid’

// Load any theme from Shiki’s reg­istry

const high­lighter = await getS­in­gle­ton­High­lighter({

themes: [‘vitesse-dark’, ‘rose-pine’, ‘material-theme-darker’]

// Extract di­a­gram col­ors from the theme

const col­ors = fromShikiTheme(high­lighter.get­Theme(‘vitesse-dark’))

const svg = await ren­der­Mer­maid(di­a­gram, col­ors)

The fromShikiTheme() func­tion in­tel­li­gently maps VS Code ed­i­tor col­ors to di­a­gram roles:

For ter­mi­nal en­vi­ron­ments, CLI tools, or any­where you need plain text, ren­der to ASCII or Unicode box-draw­ing char­ac­ters:

im­port { ren­der­Mer­maid­Ascii } from ‘beautiful-mermaid’

// Unicode mode (default) — pret­tier box draw­ing

const uni­code = ren­der­Mer­maid­Ascii(`graph LR; A –> B`)

// Pure ASCII mode — max­i­mum com­pat­i­bil­ity

const ascii = ren­der­Mer­maid­Ascii(`graph LR; A –> B`, { use­Ascii: true })

ren­der­Mer­maid­Ascii(di­a­gram, {

use­Ascii: false, // true = ASCII, false = Unicode (default)

paddingX: 5, // Horizontal spac­ing be­tween nodes

paddingY: 5, // Vertical spac­ing be­tween nodes

boxBor­der­Padding: 1, // Padding in­side node boxes

The ASCII ren­der­ing en­gine is based on mer­maid-ascii by Alexander Grooff. We ported it from Go to TypeScript and ex­tended it with:

Thank you Alexander for the ex­cel­lent foun­da­tion!

The act­ing head of the US gov­ern­men­t’s top cy­ber­se­cu­rity agency re­port­edly up­loaded sen­si­tive gov­ern­ment files into a pub­lic ver­sion of ChatGPT, trig­ger­ing in­ter­nal se­cu­rity alerts and a fed­eral re­view.

A Politico in­ves­ti­ga­tion claims Madhu Gottumukkala, the in­terim di­rec­tor of the Cybersecurity and Infrastructure Security Agency, up­loaded con­tract­ing doc­u­ments marked “For Official Use Only” into ChatGPT last sum­mer.

The re­port says Gottumukkala re­quested a spe­cial ex­emp­tion to ac­cess ChatGPT, which is blocked for other Department of Homeland Security staff.

Cybersecurity mon­i­tor­ing sys­tems then re­port­edly flagged the up­loads in early August. That trig­gered a DHS-led dam­age as­sess­ment to de­ter­mine whether the in­for­ma­tion had been ex­posed.

Public ver­sions of ChatGPT share user in­puts with OpenAI, which raised con­cerns in­side the fed­eral gov­ern­ment about sen­si­tive data leav­ing in­ter­nal net­works.

CISA spokesper­son Marci McCarthy told Politico that Gottumukkala “was granted per­mis­sion to use ChatGPT with DHS con­trols in place,” adding that the use was “short-term and lim­ited.”

Gottumukkala has served as act­ing di­rec­tor since May, while the Senate has yet to con­firm Sean Plankey as per­ma­nent head of the agency.

The ChatGPT in­ci­dent fol­lows other re­ported is­sues dur­ing Gottumukkala’s tenure. Politico said he pre­vi­ously failed a coun­ter­in­tel­li­gence poly­graph re­quired for ac­cess to highly sen­si­tive in­tel­li­gence. During con­gres­sional tes­ti­mony last week, he re­jected that char­ac­ter­i­za­tion when ques­tioned.

The re­port lands as the ad­min­is­tra­tion of US President Donald Trump con­tin­ues to push AI adop­tion across fed­eral agen­cies.

Trump signed an ex­ec­u­tive or­der in December aimed at lim­it­ing state-level AI reg­u­la­tion, while the Pentagon has an­nounced an “AI-first” strat­egy to ex­pand the mil­i­tary’s use of ar­ti­fi­cial in­tel­li­gence.

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This con­tent is gen­er­ated by Google AI. Generative AI is ex­per­i­men­tal

In August, we pre­viewed Genie 3, a gen­eral-pur­pose world model ca­pa­ble of gen­er­at­ing di­verse, in­ter­ac­tive en­vi­ron­ments. Even in this early form, trusted testers were able to cre­ate an im­pres­sive range of fas­ci­nat­ing worlds and ex­pe­ri­ences, and un­cov­ered en­tirely new ways to use it. The next step is to broaden ac­cess through a ded­i­cated, in­ter­ac­tive pro­to­type fo­cused on im­mer­sive world cre­ation. Starting to­day, we’re rolling out ac­cess to Project Genie for Google AI Ultra sub­scribers in the U.S (18+). This ex­per­i­men­tal re­search pro­to­type lets users cre­ate, ex­plore and remix their own in­ter­ac­tive worlds.A world model sim­u­lates the dy­nam­ics of an en­vi­ron­ment, pre­dict­ing how they evolve and how ac­tions af­fect them. While Google DeepMind has a his­tory of agents for spe­cific en­vi­ron­ments like Chess or Go, build­ing AGI re­quires sys­tems that nav­i­gate the di­ver­sity of the real world.To meet this chal­lenge and sup­port our AGI mis­sion, we de­vel­oped Genie 3. Unlike ex­plorable ex­pe­ri­ences in sta­tic 3D snap­shots, Genie 3 gen­er­ates the path ahead in real time as you move and in­ter­act with the world. It sim­u­lates physics and in­ter­ac­tions for dy­namic worlds, while its break­through con­sis­tency en­ables the sim­u­la­tion of any real-world sce­nario — from ro­bot­ics and mod­el­ling an­i­ma­tion and fic­tion, to ex­plor­ing lo­ca­tions and his­tor­i­cal set­tings.Build­ing on our model re­search with trusted testers from across in­dus­tries and do­mains, we are tak­ing the next step with an ex­per­i­men­tal re­search pro­to­type: Project Genie.Project Genie is a pro­to­type web app pow­ered by Genie 3, Nano Banana Pro and Gemini, which al­lows users to ex­per­i­ment with the im­mer­sive ex­pe­ri­ences of our world model first­hand. The ex­pe­ri­ence is cen­tred on three core ca­pa­bil­i­ties:

Prompt with text and gen­er­ated or up­loaded im­ages to cre­ate a liv­ing, ex­pand­ing en­vi­ron­ment. Create your char­ac­ter, your world, and de­fine how you want to ex­plore it — from walk­ing to rid­ing, fly­ing to dri­ving, and any­thing be­yond.For more pre­cise con­trol, we have in­te­grated “World Sketching” with Nano Banana Pro. This al­lows you to pre­view what your world will look like and mod­ify your im­age to fine tune your world prior to jump­ing in. You can also de­fine your per­spec­tive for the char­ac­ter — such as first-per­son or third-per­son — giv­ing you con­trol over how you ex­pe­ri­ence the scene be­fore you en­ter.

Your world is a nav­i­ga­ble en­vi­ron­ment that’s wait­ing to be ex­plored. As you move, Project Genie gen­er­ates the path ahead in real time based on the ac­tions you take. You can also ad­just the cam­era as you tra­verse through the world.Remix ex­ist­ing worlds into new in­ter­pre­ta­tions, by build­ing on top of their prompts. You can also ex­plore cu­rated worlds in the gallery or in the for in­spi­ra­tion, or build on top of them. And once you’re done, you can down­load videos of your worlds and your ex­plo­rations.

Project Genie is an ex­per­i­men­tal re­search pro­to­type in Google Labs, pow­ered by Genie 3. As with all our work to­wards gen­eral AI sys­tems, our mis­sion is to build AI re­spon­si­bly to ben­e­fit hu­man­ity. Since Genie 3 is an early re­search model, there are a few known ar­eas for im­prove­ment:Gen­er­ated worlds might not look com­pletely true-to-life or al­ways ad­here closely to prompts or im­ages, or real-world physic­sChar­ac­ters can some­times be less con­trol­lable, or ex­pe­ri­ence higher la­tency in con­trolA few of the Genie 3 model ca­pa­bil­i­ties we an­nounced in August, such as prompt­able events that change the world as you ex­plore it, are not yet in­cluded in this pro­to­type. You can find more de­tails on model lim­i­ta­tions and fu­ture up­dates on how we’re im­prov­ing the ex­pe­ri­ence, here.Build­ing on the work we have been do­ing with trusted testers, we are ex­cited to share this pro­to­type with users of our most ad­vanced AI to bet­ter un­der­stand how peo­ple will use world mod­els in many ar­eas of both AI re­search and gen­er­a­tive me­dia.Ac­cess to Project Genie be­gins rolling out to­day to Google AI Ultra sub­scribers in the U.S. (18+), ex­pand­ing to more ter­ri­to­ries in due course. We look for­ward to see­ing the in­fi­nitely di­verse worlds they cre­ate, and in time, our goal is to make these ex­pe­ri­ences and tech­nol­ogy ac­ces­si­ble to more users.

Writing about lay­offs and the tech mar­ket has been on my TODO for sev­eral years. Yesterday, the news of 16k Amazon lay­offs plus two LinkedIn posts on the same topic back-to-back en­cour­aged me to fi­nally write about it.

Disclaimer: I worked 5 years at Shopify. This is prob­a­bly why such posts come one af­ter an­other on my feed but Shopify is­n’t the point here, they are just a mi­cro piece of the whole fucked up sys­tem.

Tech job mar­ket is fun­da­men­tally bro­ken and we all point­ing fin­gers at AI.

But hav­ing spent al­most 2 decades in the in­dus­try, I think the rot goes much deeper than ChatGPT.

Truth to be told tech mar­ket has­n’t truly ‘improved’ since the 2008 fi­nan­cial cri­sis. It just mu­tated into some­thing evil.

After the 2008 mort­gage cri­sis, the eco­nomic regime sig­nif­i­cantly changed. Which was also around the time my in­ter­est in Finance be­gan and re­cently I started to build my own in­vest­ment tool you can read more about it here.

At that time time we en­tered an era of ex­ten­sive liq­uid­ity (cheap money). When in­ter­est rates are near zero, in­vestors de­mand growth above all else.

As a re­sult, tech com­pa­nies stopped build­ing for sus­tain­abil­ity and started build­ing for ex­po­nen­tial ex­pan­sion.

Here is a graph shows US Fed Interest Rates by years.

In tra­di­tional in­dus­tries like man­u­fac­tur­ing you don’t hire 500 fac­tory work­ers un­less you have a pro­duc­tion line that needs them. You don’t over-hire based on a guess.

But in Tech, the play­book is dif­fer­ent. Companies over-hire soft­ware en­gi­neers in­ten­tion­ally. To play the lot­tery. It is sim­i­lar to hav­ing slow and steady ETF in­vest­ments vs ac­tive in­vest­ing. No mat­ter how godly you are with ac­tive in­vest­ing sooner or later, you will in­vest on a loser. Same goes for busi­nesses.

In a fac­tory, “Work in Progress” (unfinished goods) is a li­a­bil­ity. You don’t want in­ven­tory sit­ting on the floor; you want it out the door.

In soft­ware, we con­vinced our­selves that “Work in Progress” (hiring en­gi­neers to work on pro­jects that haven’t shipped yet) is an as­set.

It is not. It is just ex­ces­sive in­ven­tory.

When the mar­ket turned, com­pa­nies re­al­ized they were ware­hous­ing tal­ent like un­sold prod­ucts. And just like un­sold in­ven­tory, when the stor­age costs get too high, you dump it.

Till ~2010, a lay­off was a sign of fail­ure. It meant the CEO messed up.

In 2024, a lay­off is a sig­nal of “discipline.” Companies lay off thou­sands, and their stock price jumps.

They are sig­nal­ing to Wall Street that they are will­ing to sac­ri­fice hu­man cap­i­tal to pro­tect mar­gins.

Big Tech com­pa­nies (think Google, Meta, or any hy­per-growth SaaS) op­er­ate on a two-tier sys­tem:

1. The Core: A fun­da­men­tal team work­ing on the ac­tual rev­enue-gen­er­at­ing prod­ucts (the search en­gine, the ad net­work, the check­out flow).

2. The Bets: Thousands of en­gi­neers hired to build par­al­lel prod­ucts, ex­per­i­men­tal fea­tures, or sim­ply to keep tal­ent away from com­peti­tors and po­ten­tially build some­thing that would move into “The Core” tier.

The com­pany knows that most of these side bets will fail. When the eco­nomic winds change, the ‘non-core’ staff be­comes im­me­di­ately re­place­able.

It’s a vi­cious cy­cle: Hire the best peo­ple you can find to hoard tal­ent, see what sticks, and lay off the rest when in­vestors want to see bet­ter mar­gins.

Most en­gi­neers (including me) spent months grind­ing LeetCode at least twice in their ca­reer, study­ing sys­tem de­sign, and pass­ing gru­el­ing 6-round in­ter­views to prove they are the “top 1%.”

Yet, once hired, they are of­ten placed on a non-es­sen­tial team where they be­come noth­ing more than a sta­tis­tic on a spread­sheet.

You jump through hoops to prove you are ex­cep­tional, only to be treated as dis­pos­able.

For a long time, Europe of­fered a counter-bal­ance. The pay was lower than Silicon Valley, but the trade-off was sta­bil­ity, stronger la­bor pro­tec­tions, and a slower, more sus­tain­able pace of work.

As American tech gi­ants ex­panded into Europe and as European uni­corns chased the same growth-at-all-costs play­books the in­cen­tives changed.

Leadership im­ported US-style com­pen­sa­tion mod­els, in­vestor ex­pec­ta­tions, and or­ga­ni­za­tional volatil­ity, but with­out im­port­ing US-level pay or up­side.

”On pa­per” Europe still has strong la­bor laws. In prac­tice, com­pa­nies learned to route around them: con­stant re­or­ga­ni­za­tions, “strategic re­fo­cus” lay­offs, per­for­mance-man­aged ex­its.

The re­sult is the worst of both worlds. European en­gi­neers now face US-level job in­se­cu­rity with European-level com­pen­sa­tion and lim­ited mo­bil­ity. The safety net has­n’t dis­ap­peared, but it’s be­ing slowly hol­lowed out.

And sev­er­ances… A small, one-time pay­ment is used to jus­tify years of be­low mar­ket com­pen­sa­tion, while of­fer­ing lit­tle real pro­tec­tion against sud­den dis­place­ment.

Europe just be­came a lower-cost ex­ten­sion of Silicon Valley.

Ultimately, this comes down to how com­pa­nies sig­nal value.

Traditional busi­nesses used to show their health through rev­enue, profit, and smart cap­i­tal in­vest­ment. Today, Tech com­pa­nies use lay­offs as a mar­ket­ing sig­nal to Wall Street. They cut costs not be­cause they are go­ing bank­rupt, but to show they can be “efficient.”

The more liq­uid­ity that was pumped into Tech, the harder this sit­u­a­tion be­came. As long as en­gi­neers are treated as spec­u­la­tive as­sets rather than hu­man cap­i­tal, the mar­ket will re­main bro­ken re­gard­less of how good AI gets.

The job mar­ket is not “tough” right now be­cause of AI. It is tough be­cause we are un­wind­ing 14 years of fi­nan­cial tox­i­c­ity.

The liq­uid­ity that flooded the tech sec­tor did­n’t just in­flate val­u­a­tions; it in­flated teams, egos, and ex­pec­ta­tions.

Until the in­dus­try re­learns how to build with scarcity rather than ex­cess, the “vicious cy­cle” of hire-and-dump will con­tinue re­gard­less of how good AI will get.

So you aren’t be­ing laid off be­cause your per­for­mance was bad; you are be­ing ef­fec­tively “liquidated” like a bad stock trade that you sell with a loss.