Modders, start your en­gines.

by William Judd

Yesterday, 10:29am

With the rather ex­cel­lent Steam Controller now on its way to the lucky few that man­aged to or­der one, Valve has re­leased a full set of CAD files for their new hard­ware. The idea is to let en­ter­pris­ing mod­ders cre­ate their own Steam Controller add-ons, like skins, charg­ing stands, grip ex­ten­ders or smart­phone mounts.

The Valve re­lease in­cludes files for the ex­ter­nal shell (“surface topol­ogy”) of the Controller and Puck, with a .STP, .STL and en­gi­neer­ing di­a­gram of each de­vice, with the lat­ter show­ing ar­eas that must re­main un­cov­ered to let the de­vice main­tain its sig­nal strength and oth­er­wise func­tion as de­signed.

Valve has pre­vi­ously re­leased CAD files for its Steam Deck hand­held, Valve Index VR suite and even the orig­i­nal Steam Controller a decade ago, so this re­lease is wel­comed but not un­ex­pected.

The re­lease is un­der a fairly re­stric­tive Creative Commons li­cense which al­lows for non-com­mer­cial use and re­quires at­tri­bu­tion and shar­ing of de­signs back to the com­mu­nity. However, the li­cense also sug­gests that com­mer­cial en­ti­ties in­ter­ested in mak­ing ac­ces­sories for the Steam Controller or its Puck can con­tact Valve di­rectly to dis­cuss terms.

What is your ul­ti­mate Steam Controller or Steam Controller Puck ac­ces­sory? Let us know in the com­ments be­low. For me, it would def­i­nitely be a smart­phone clip - play­ing through some­thing rel­a­tively low-stakes like Forza Horizon 6 via Moonlight game stream­ing on a phone would be slick.

[source steam­com­mu­nity.com]

Will is web­site ed­i­tor for Digital Foundry, spe­cial­is­ing in PC hard­ware, sim rac­ing and dis­play tech­nol­ogy.

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Bluesky

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Parkinson’s Law states that work ex­pands to fill the time avail­able. In the era of AI, work­ers now have a tool that ex­pands to fill what­ever a large lan­guage model can be per­suaded to gen­er­ate, which is to say, with­out limit.

Parkinson’s Law states that work ex­pands to fill the time avail­able. In the era of AI, work­ers now have a tool that ex­pands to fill what­ever a large lan­guage model can be per­suaded to gen­er­ate, which is to say, with­out limit.

What I have watched hap­pen in my pro­fes­sion in the last two years, I am still strug­gling to de­scribe. The first time I knew some­thing was wrong, roughly a year and a quar­ter ago, I no­ticed a col­league re­ply­ing to me us­ing AI. His re­sponse was ob­vi­ously gen­er­ated by Claude. The punc­tu­a­tion gave it away — em dashes where no one types em dashes, the rhyth­mic struc­ture, the con­fi­dent grasp of tech­nolo­gies I knew for a fact he did not un­der­stand. I sat with it for a while, weigh­ing whether to de­bate some­one who was vis­i­bly copy-past­ing ver­ba­tim from a model. The chan­nel was pub­lic, and I spent more time than I should have cor­rect­ing fun­da­men­tals. Eventually I stopped. He was not, in any mean­ing­ful sense, on the other side of the con­ver­sa­tion.

Generative AI can pro­duce work that looks ex­pert with­out be­ing ex­pert, and the fail­ure ar­rives in two shapes. The first is when novices in a field are able to pro­duce work that re­sem­bles what their se­niors pro­duce, faster or more ad­vanced than their judg­ment. The sec­ond is when peo­ple gen­er­ate ar­ti­facts in dis­ci­plines they were never trained in. The two fail­ures look sim­i­lar from a dis­tance and are not the same. Research has mostly mea­sured the first. The sec­ond is what it is miss­ing, and in my ex­pe­ri­ence it is the riskier of the two.

Cross do­main gen­er­a­tion

People who can­not write code are build­ing soft­ware. People who have never de­signed a data sys­tem are de­sign­ing data sys­tems. Most of it is not shipped; it is built, of­ten for many hours, pos­si­bly shown in­ter­nally with great vigor, used qui­etly, and oc­ca­sion­ally sur­faced to a client with­out much fan­fare. Workers can ob­sess over an idea, work­ing many hours over­time. There are a few prac­ti­tion­ers who use the cur­rent agen­tic tools to do com­plex things prop­erly, but they are scarce and as I find, typ­i­cally in code gen­er­a­tion. AI, for all its ca­pa­bil­i­ties at the level of the in­di­vid­ual, has not scaled prop­erly in my work­place.

I have a col­league, a care­ful and in­tel­li­gent per­son in a role that is not en­gi­neer­ing, who spent two months ear­lier this year build­ing a sys­tem that should have been de­signed by some­one with for­mal train­ing in data ar­chi­tec­ture. He used the tools well, by the stan­dards by which use of the tools is cur­rently mea­sured. He pro­duced a great deal of code, a great deal of doc­u­men­ta­tion, a great deal of what looked, to any­one who did not know what to look for, like progress. He could not, when asked, ex­plain how any of it ac­tu­ally worked. The work was wrong from the first day. The schemas, and more im­por­tantly the ob­jec­tives, were wrong in a way that would have been ob­vi­ous to any­one with two years in the field. Several of us did know. When opin­ions were voiced even as high as a V.P., he fought back. The room had been arranged in such a way that say­ing so was not a con­tri­bu­tion; his man­agers were too in­vested in the ap­pear­ance of mo­men­tum to want the ap­pear­ance dis­turbed. The work will con­tinue, in all prob­a­bil­ity, un­til it is shown to a stake­holder, and they de­cide not to in­vest.

This is the part of the phe­nom­e­non I find hard­est to write about. The tool did not make him a worse col­league. It made him able to im­per­son­ate, for months, a dis­ci­pline he had never trained in, and the im­per­son­ation was good enough that the in­sti­tu­tional in­cen­tives all bent to­ward let­ting him con­tinue. Perhaps it’s a fail­ure of man­age­ment, but I have been find­ing man­age­ment to be so ea­ger to em­brace AI that they’re will­ing to ac­cept the risk.

It would be tol­er­a­ble, per­haps, if the tool of­fered an hon­est as­sess­ment of what it had pro­duced. The Cheng et al. Stanford study pub­lished in Science this spring [1] con­firmed what every reg­u­lar user al­ready knew: lead­ing mod­els are roughly fifty per­cent more agree­able than hu­man re­spon­dents, af­firm­ing the user even where the af­fir­ma­tion is un­war­ranted. Berkeley CMR meta-analy­ses [4] found AI-literate users of­ten over­es­ti­mate their per­for­mance. Particularly in­ter­est­ing when work­ers stray out­side of their train­ing. An NBER study of sup­port agents [2] found gen­er­a­tive AI boosted novice pro­duc­tiv­ity by about a third while barely help­ing ex­perts. Harvard Business School re­searchers found the same pat­tern in con­sult­ing work [3]. So you have over­con­fi­dent, novices able to im­prove their in­di­vid­ual pro­duc­tiv­ity in an area of ex­per­tise they are un­able to re­view for cor­rect­ness. What could go wrong?

The con­duit prob­lem

A grow­ing body of work calls this out­put-com­pe­tence de­cou­pling [5]. In any pre­vi­ous era, the qual­ity of a piece of work was a more or less re­li­able sig­nal of the com­pe­tence of the per­son who pro­duced it. A novice es­say read like a novice es­say; novice code crashed in novice ways. AI has sev­ered that re­la­tion­ship. A novice now pro­duces work that does not be­tray the novice, be­cause the com­pe­tence the work re­flects is not the novice’s com­pe­tence at all. It is the sys­tem’s. The per­son, in the trans­ac­tion, be­comes a kind of con­duit, ca­pa­ble of rout­ing the out­put to a re­cip­i­ent and in­ca­pable of eval­u­at­ing it on the way through.

The skills of pro­duc­ing work and judg­ing it were de­lib­er­ately dis­tinct, but ac­com­plish­ing the work it­self used to teach the judg­ment. The first skill now be­longs, in large part, to the ma­chines. The sec­ond still be­longs to us, though fewer are both­er­ing to ac­quire or uti­lize it.

The ar­chi­tec­tural cri­tique that used to come from some­one who was taught, or who had built and bro­ken three of these be­fore now comes from a model with no em­bod­ied mem­ory of build­ing or break­ing any­thing. The slow­ness was not a tax on the real work; the slow­ness was the real work. It was how the work got good, and how the peo­ple pro­duc­ing the work got good, and how the firm whose name was on the work could promise the client that what they were buy­ing was a par­tic­u­lar kind of thing rather than a generic one.

The cur­rent gen­er­a­tion of agen­tic sys­tems is built around the premise that the hu­man is the bot­tle­neck — that the loop runs faster and cleaner with­out the awk­ward de­lay of some­one read­ing what is about to hap­pen and de­cid­ing whether it should. This is, in a great many cases, ex­actly back­wards. The hu­man in the loop is not a ves­tige of an ear­lier era; the hu­man is the only part of the loop with skin in the game. Removing the H from HITL is not an ef­fi­ciency. It is the aban­don­ment of the only mech­a­nism the sys­tem has for catch­ing it­self.

Slop on the in­side

Requirements doc­u­ments that were once a page are now twelve. Status up­dates that were once three sen­tences are now bul­leted sum­maries of bul­leted sum­maries. Retrospective notes, post-in­ci­dent re­ports, de­sign memos, kick­off decks: every ar­ti­fact that can be elon­gated is, by peo­ple who do not read what they pro­duce, for read­ers who do not read what they re­ceive. The cost of pro­duc­ing a doc­u­ment has fallen to nearly zero; the cost of read­ing one has not, and is in fact ris­ing, be­cause the reader must now sift the syn­thetic con­text for what­ever the doc­u­ment was orig­i­nally about. Each in­di­vid­ual de­ci­sion to elon­gate seems ra­tio­nal, and each is in­de­pen­dently re­warded — read­ers are more con­fi­dent in longer AI-generated ex­pla­na­tions whether or not the ex­pla­na­tions are cor­rect [5]. The col­lec­tive ef­fect is that the sig­nal in any given work­place is harder to find than it was be­fore any of this be­gan. The check­points have been hid­den, drowned in their own pa­per­work, even when the peo­ple drown­ing them were gen­uinely try­ing to “be brief”.

This is a new form of slop, and it is more ex­pen­sive than the pub­lic kind, be­cause the peo­ple pro­duc­ing it are be­ing paid a salary to do so. The pipeline of fu­ture ex­perts is thin­ning from both ends. The work that used to teach judg­ment is now done by the tool, and the en­try-level roles where the teach­ing hap­pened are be­ing cut on the the­ory that the tool can do the work. What this is caus­ing, in many of­fices in­clud­ing mine, is a great deal of mo­tion and very lit­tle of what mo­tion used to cre­ate.

The down­stream costs are ac­cu­mu­lat­ing quickly. Most of the pub­lic dis­cus­sion of AI slop has fo­cused on the flood into pub­lic mar­kets — a University of Florida mar­ket­ing study [6] be­ing among the more di­rect treat­ments. What is less re­marked upon is the same dy­namic play­ing out in­side or­ga­ni­za­tions: time wasted us­ing AI on tasks that did not need it, on ar­ti­facts no one will read, on processes that ex­ist only be­cause the tool made it cheap to con­struct them. On decks that spell out things that pre­vi­ously did­n’t even need to be said or were as­sumed.

What to do about it

What dis­ci­pline looks like, in this en­vi­ron­ment, is al­most em­bar­rass­ingly old-fash­ioned and may seem ob­vi­ous to most of you un­til you try to avoid it. Use the tool where you can ver­ify pre­cisely what it pro­duces. Never ask a model for con­fir­ma­tion; the tool agrees with every­one, and an agree­ment that costs the agreer noth­ing is worth noth­ing.

Generative AI does well on tasks where feed­back is fast, where be­ing ap­prox­i­mately right is good enough, where the hu­man re­mains the fi­nal ar­biter. Drafting a memo, gen­er­at­ing ex­am­ples, sum­ma­riz­ing ma­te­r­ial the reader could ver­ify if they cared to. The University of Illinois Generative AI guid­ance [7] and the PLOS Computational Biology “Ten Simple Rules” pa­per on AI in re­search [8], among the more care­ful doc­u­ments now cir­cu­lat­ing, list much of this ex­plic­itly: brain­storm­ing, copy­edit­ing, re­for­mu­lat­ing one’s own ideas, pat­tern de­tec­tion in data one al­ready un­der­stands.

In every rec­om­mended use, the hu­man sup­plies the judg­ment and the tool sup­plies the through­put. This is a stronger po­si­tion than hu­man-in-the-loop. The tool sits out­side the work, con­tribut­ing where in­vited and silent oth­er­wise, which is the op­po­site of what most agen­tic sys­tems are now be­ing built to do.

For firms, the com­pet­i­tive ad­van­tage of a firm whose work can be trusted has not dis­ap­peared; it has, if any­thing, ap­pre­ci­ated, be­cause so many of the fir­m’s com­peti­tors are qui­etly con­vert­ing them­selves into con­tent-gen­er­a­tion pipelines and count­ing on the client not to no­tice.

This is al­ready com­ing to a head. Deloitte has al­ready re­funded part of a $440,000 fee over an AI-hallucinated gov­ern­ment re­port. It could be a pro­duc­tion sys­tem built on a hal­lu­ci­nated spec­i­fi­ca­tion, or a se­nior en­gi­neer who re­al­izes they have spent the last year nom­i­nally re­view­ing work they could no longer com­pe­tently re­view. The reck­on­ing will not be sub­tle. The firms still do­ing the work prop­erly will be in a po­si­tion to charge for it. The firms that have hol­lowed them­selves out will dis­cover that what they hol­lowed out was the thing the client was pay­ing for.

Misunderstanding and mis­use of AI in the work­place is ram­pant. In many of the rooms I now find my­self in, ex­per­tise has been asked to look the other way: to de­liver faster, pro­duce more, in­te­grate the tools more deeply, get out of the way of the col­leagues who are “getting things done”. The ar­ti­facts are ac­cu­mu­lat­ing; the work is not. And some­where on the other side of all this out­put, a client is open­ing a de­liv­er­able, read­ing a sum­ma­rized list, and they may just choose to re­view it man­u­ally.

Disclaimer: I am not an ex­pert, or a writer. This is not an aca­d­e­mic ar­ti­cle. Whether I like it or not, I am at the precipice of AI. These are my ex­pe­ri­ences, in my work­place, with ref­er­ences to things that I think are relevent. If you take one thing away, take away that peo­ple are im­pres­sion­able crea­tures. Also, those that claimed this ar­ti­cle is iron­i­cally a ca­su­alty of it’s own com­plaint are 100% right, Kudos.

References

1. Sycophantic AI de­creases proso­cial in­ten­tions and pro­motes de­pen­dence (Cheng, Lee, Khadpe, Yu, Han, & Jurafsky, 2026). Science.

2. Generative AI at Work (Brynjolfsson, Li, & Raymond, 2025). The Quarterly Journal of Economics, 140(2), 889 – 942. Also: NBER Working Paper No. 31161, April 2023.

3. Navigating the Jagged Technological Frontier (Dell’Acqua, McFowland, Mollick, et al., 2026). Organization Science. Originally HBS Working Paper No. 24 – 013, 2023.

4. Seven Myths About AI and Productivity: What the Evidence Really Says (Berkeley CMR, 2025). Meta-analysis con­firm­ing asym­met­ric AI pro­duc­tiv­ity gains and user over­con­fi­dence.

5. Beyond the Steeper Curve: AI-Mediated Metacognitive Decoupling (Koch, 2025). Longer AI ex­pla­na­tions make users more con­fi­dent re­gard­less of cor­rect­ness.

6. Generative AI and the mar­ket for cre­ative con­tent (Zou, Shi, & Wu, 2026). Forthcoming, Journal of Marketing Research.

7. Generative AI Guidance (University of Illinois). Recommended uses and lim­i­ta­tions of gen­er­a­tive AI in aca­d­e­mic and pro­fes­sional work.

8. Ten sim­ple rules for op­ti­mal and care­ful use of gen­er­a­tive AI in sci­ence (Helmy, Jin, et al., 2025). PLOS Computational Biology, 21(10), e1013588.

6th May 2026

I re­cently talked with Joseph Ruscio about AI cod­ing tools for Heavybit’s High Leverage pod­cast: Ep. #9, The AI Coding Paradigm Shift with Simon Willison. Here are some of my high­lights, in­clud­ing my dis­turb­ing re­al­iza­tion that vibe cod­ing and agen­tic en­gi­neer­ing have started to con­verge in my own work.

One thing I re­ally en­joy about pod­casts is that they some­times push me to think out loud in a way that ex­poses an idea I’ve not pre­vi­ously been able to put into words.

Vibe cod­ing and agen­tic en­gi­neer­ing are start­ing to over­lap

A few weeks af­ter vibe cod­ing was first coined I pub­lished Not all AI-assisted pro­gram­ming is vibe cod­ing (but vibe cod­ing rocks), where I firmly staked out my be­lief that “vibe cod­ing” is a very dif­fer­ent beast from re­spon­si­ble use of AI to write code, which I’ve since started to call agen­tic en­gi­neer­ing.

When Joseph brought up the dis­tinc­tion be­tween the two I had a sud­den re­al­iza­tion that they’re not nearly as dis­tinct for me as they used to be:

Weirdly though, those things have started to blur for me al­ready, which is quite up­set­ting. I thought we had a very clear de­lin­eation where vibe cod­ing is the thing where you’re not look­ing at the code at all. You might not even know how to pro­gram. You might be a non-pro­gram­mer who asks for a thing, and gets a thing, and if the thing works, then great! And if it does­n’t, you tell it that it does­n’t work and cross your fin­gers. But at no point are you re­ally car­ing about the code qual­ity or any of those ad­di­tional con­straints. And my take on vibe cod­ing was that it’s fan­tas­tic, pro­vided you un­der­stand when it can be used and when it can’t. A per­sonal tool for you, where if there’s a bug it hurts only you, go ahead! If you’re build­ing soft­ware for other peo­ple, vibe cod­ing is grossly ir­re­spon­si­ble be­cause it’s other peo­ple’s in­for­ma­tion. Other peo­ple get hurt by your stu­pid bugs. You need to have a higher level than that. This con­trasts with agen­tic en­gi­neer­ing where you are a pro­fes­sional soft­ware en­gi­neer. You un­der­stand se­cu­rity and main­tain­abil­ity and op­er­a­tions and per­for­mance and so forth. You’re us­ing these tools to the high­est of your own abil­ity. I’m find­ing the scope of chal­lenges I can take on has gone up by a sig­nif­i­cant amount be­cause I’ve got the sup­port of these tools. But I’m still lean­ing on my 25 years of ex­pe­ri­ence as a soft­ware en­gi­neer. The goal is to build high qual­ity pro­duc­tion sys­tems: if you’re build­ing lower qual­ity stuff faster, I think that’s bad. I want to build higher qual­ity stuff faster. I want every­thing I’m build­ing to be bet­ter in every way than it was be­fore. The prob­lem is that as the cod­ing agents get more re­li­able, I’m not re­view­ing every line of code that they write any­more, even for my pro­duc­tion level stuff. I know full well that if you ask Claude Code to build a JSON API end­point that runs a SQL query and out­puts the re­sults as JSON, it’s just go­ing to do it right. It’s not go­ing to mess that up. You have it add au­to­mated tests, you have it add doc­u­men­ta­tion, you know it’s go­ing to be good. But I’m not re­view­ing that code. And now I’ve got that feel­ing of guilt: if I haven’t re­viewed the code, is it re­ally re­spon­si­ble for me to use this in pro­duc­tion? The thing that re­ally helps me is think­ing back to when I’ve worked at larger or­ga­ni­za­tions where I’ve been an en­gi­neer­ing man­ager. Other teams are build­ing soft­ware that my team de­pends on. If an­other team hands over some­thing and says, “hey, this is the im­age re­size ser­vice, here’s how to use it to re­size your im­ages”… I’m not go­ing to go and read every line of code that they wrote. I’m go­ing to look at their doc­u­men­ta­tion and I’m go­ing to use it to re­size some im­ages. And then I’m go­ing to start ship­ping my own fea­tures. And if I start run­ning into prob­lems where the im­age re­sizer thing ap­pears to have bugs or the per­for­mance is­n’t good, that’s when I might dig into their Git repos­i­to­ries and see what’s go­ing on. But for the most part I treat that as a semi-black box that I don’t look at un­til I need to. I’m start­ing to treat the agents in the same way. And it still feels un­com­fort­able, be­cause hu­man be­ings are ac­count­able for what they do. A team can build a rep­u­ta­tion. I can say “I trust that team over there. They built good soft­ware in the past. They’re not go­ing to build some­thing rub­bish be­cause that af­fects their pro­fes­sional rep­u­ta­tions.” Claude Code does not have a pro­fes­sional rep­u­ta­tion! It can’t take ac­count­abil­ity for what it’s done. But it’s been prov­ing it­self any­way—time and time again it’s churn­ing out straight­for­ward things and do­ing them right in the style that I like.

Weirdly though, those things have started to blur for me al­ready, which is quite up­set­ting.

I thought we had a very clear de­lin­eation where vibe cod­ing is the thing where you’re not look­ing at the code at all. You might not even know how to pro­gram. You might be a non-pro­gram­mer who asks for a thing, and gets a thing, and if the thing works, then great! And if it does­n’t, you tell it that it does­n’t work and cross your fin­gers.

But at no point are you re­ally car­ing about the code qual­ity or any of those ad­di­tional con­straints. And my take on vibe cod­ing was that it’s fan­tas­tic, pro­vided you un­der­stand when it can be used and when it can’t.

A per­sonal tool for you, where if there’s a bug it hurts only you, go ahead!

If you’re build­ing soft­ware for other peo­ple, vibe cod­ing is grossly ir­re­spon­si­ble be­cause it’s other peo­ple’s in­for­ma­tion. Other peo­ple get hurt by your stu­pid bugs. You need to have a higher level than that.

This con­trasts with agen­tic en­gi­neer­ing where you are a pro­fes­sional soft­ware en­gi­neer. You un­der­stand se­cu­rity and main­tain­abil­ity and op­er­a­tions and per­for­mance and so forth. You’re us­ing these tools to the high­est of your own abil­ity. I’m find­ing the scope of chal­lenges I can take on has gone up by a sig­nif­i­cant amount be­cause I’ve got the sup­port of these tools.

But I’m still lean­ing on my 25 years of ex­pe­ri­ence as a soft­ware en­gi­neer.

The goal is to build high qual­ity pro­duc­tion sys­tems: if you’re build­ing lower qual­ity stuff faster, I think that’s bad. I want to build higher qual­ity stuff faster. I want every­thing I’m build­ing to be bet­ter in every way than it was be­fore.

The prob­lem is that as the cod­ing agents get more re­li­able, I’m not re­view­ing every line of code that they write any­more, even for my pro­duc­tion level stuff.

I know full well that if you ask Claude Code to build a JSON API end­point that runs a SQL query and out­puts the re­sults as JSON, it’s just go­ing to do it right. It’s not go­ing to mess that up. You have it add au­to­mated tests, you have it add doc­u­men­ta­tion, you know it’s go­ing to be good.

But I’m not re­view­ing that code. And now I’ve got that feel­ing of guilt: if I haven’t re­viewed the code, is it re­ally re­spon­si­ble for me to use this in pro­duc­tion?

The thing that re­ally helps me is think­ing back to when I’ve worked at larger or­ga­ni­za­tions where I’ve been an en­gi­neer­ing man­ager. Other teams are build­ing soft­ware that my team de­pends on.

If an­other team hands over some­thing and says, “hey, this is the im­age re­size ser­vice, here’s how to use it to re­size your im­ages”… I’m not go­ing to go and read every line of code that they wrote.

I’m go­ing to look at their doc­u­men­ta­tion and I’m go­ing to use it to re­size some im­ages. And then I’m go­ing to start ship­ping my own fea­tures. And if I start run­ning into prob­lems where the im­age re­sizer thing ap­pears to have bugs or the per­for­mance is­n’t good, that’s when I might dig into their Git repos­i­to­ries and see what’s go­ing on. But for the most part I treat that as a semi-black box that I don’t look at un­til I need to.

I’m start­ing to treat the agents in the same way. And it still feels un­com­fort­able, be­cause hu­man be­ings are ac­count­able for what they do. A team can build a rep­u­ta­tion. I can say “I trust that team over there. They built good soft­ware in the past. They’re not go­ing to build some­thing rub­bish be­cause that af­fects their pro­fes­sional rep­u­ta­tions.”

Claude Code does not have a pro­fes­sional rep­u­ta­tion! It can’t take ac­count­abil­ity for what it’s done. But it’s been prov­ing it­self any­way—time and time again it’s churn­ing out straight­for­ward things and do­ing them right in the style that I like.

There’s an el­e­ment of the nor­mal­iza­tion of de­viance here—every time a model turns out to have writ­ten the right code with­out me mon­i­tor­ing it closely there’s a risk that I’ll trust it at the wrong mo­ment in the fu­ture and get burned.

The new chal­lenge of eval­u­at­ing soft­ware

It used to be if you found a GitHub repos­i­tory with a hun­dred com­mits and a good readme and au­to­mated tests and stuff, you could be pretty sure that the per­son writ­ing that had put a lot of care and at­ten­tion into that pro­ject. And now I can knock out a git repos­i­tory with a hun­dred com­mits and a beau­ti­ful readme and com­pre­hen­sive tests of every line of code in half an hour! It looks iden­ti­cal to those pro­jects that have had a great deal of care and at­ten­tion. Maybe it is as good as them. I don’t know. I can’t tell from look­ing at it. Even for my own pro­jects, I can’t tell. So I re­al­ized what I value more than the qual­ity of the tests and doc­u­men­ta­tion is that I want some­body to have used the thing. If you’ve got a vibe coded thing which you have used every day for the past two weeks, that’s much more valu­able to me than some­thing that you’ve just spat out and hardly even ex­er­cised.

It used to be if you found a GitHub repos­i­tory with a hun­dred com­mits and a good readme and au­to­mated tests and stuff, you could be pretty sure that the per­son writ­ing that had put a lot of care and at­ten­tion into that pro­ject.

And now I can knock out a git repos­i­tory with a hun­dred com­mits and a beau­ti­ful readme and com­pre­hen­sive tests of every line of code in half an hour! It looks iden­ti­cal to those pro­jects that have had a great deal of care and at­ten­tion. Maybe it is as good as them. I don’t know. I can’t tell from look­ing at it. Even for my own pro­jects, I can’t tell.

So I re­al­ized what I value more than the qual­ity of the tests and doc­u­men­ta­tion is that I want some­body to have used the thing. If you’ve got a vibe coded thing which you have used every day for the past two weeks, that’s much more valu­able to me than some­thing that you’ve just spat out and hardly even ex­er­cised.

The bot­tle­necks have shifted

If you can go from pro­duc­ing 200 lines of code a day to 2,000 lines of code a day, what else breaks? The en­tire soft­ware de­vel­op­ment life­cy­cle was, it turns out, de­signed around the idea that it takes a day to pro­duce a few hun­dred lines of code. And now it does­n’t. It’s not just the down­stream stuff, it’s the up­stream stuff as well. I saw a great talk by Jenny Wen, who’s the de­sign leader at Anthropic, where she said we have all of these de­sign processes that are based around the idea that you need to get the de­sign right—be­cause if you hand it off to the en­gi­neers and they spend three months build­ing the wrong thing, that’s cat­a­strophic. There’s this whole very ex­ten­sive de­sign process that you put in place be­cause that de­sign re­sults in ex­pen­sive work. But if it does­n’t take three months to build, maybe the de­sign process can be a whole lot riskier be­cause cost, if you get some­thing wrong, has been re­duced so much.

If you can go from pro­duc­ing 200 lines of code a day to 2,000 lines of code a day, what else breaks? The en­tire soft­ware de­vel­op­ment life­cy­cle was, it turns out, de­signed around the idea that it takes a day to pro­duce a few hun­dred lines of code. And now it does­n’t.

It’s not just the down­stream stuff, it’s the up­stream stuff as well. I saw a great talk by Jenny Wen, who’s the de­sign leader at Anthropic, where she said we have all of these de­sign processes that are based around the idea that you need to get the de­sign right—be­cause if you hand it off to the en­gi­neers and they spend three months build­ing the wrong thing, that’s cat­a­strophic.

There’s this whole very ex­ten­sive de­sign process that you put in place be­cause that de­sign re­sults in ex­pen­sive work. But if it does­n’t take three months to build, maybe the de­sign process can be a whole lot riskier be­cause cost, if you get some­thing wrong, has been re­duced so much.

Why I’m still not afraid for my ca­reer

When I look at my con­ver­sa­tions with the agents, it’s very clear to me that this is moon lan­guage for the vast ma­jor­ity of hu­man be­ings. There are a whole bunch of rea­sons I’m not scared that my ca­reer as a soft­ware en­gi­neer is over now that com­put­ers can write their own code, partly be­cause these things are am­pli­fiers of ex­ist­ing ex­pe­ri­ence. If you know what you’re do­ing, you can run so much faster with them. […] I’m con­stantly re­minded as I work with these tools how hard the thing that we do is. Producing soft­ware is a fe­ro­ciously dif­fi­cult thing to do. And you could give me all of the AI tools in the world and what we’re try­ing to achieve here is still re­ally dif­fi­cult. […] Matthew Yglesias, who’s a po­lit­i­cal com­men­ta­tor, yes­ter­day tweeted, “Five months in, I think I’ve de­cided that I don’t want to vibecode — I want pro­fes­sion­ally man­aged soft­ware com­pa­nies to use AI cod­ing as­sis­tance to make more/​bet­ter/​cheaper soft­ware prod­ucts that they sell to me for money.” And that feels about right to me. I can plumb my house if I watch enough YouTube videos on plumb­ing. I would rather hire a plumber.

When I look at my con­ver­sa­tions with the agents, it’s very clear to me that this is moon lan­guage for the vast ma­jor­ity of hu­man be­ings.

There are a whole bunch of rea­sons I’m not scared that my ca­reer as a soft­ware en­gi­neer is over now that com­put­ers can write their own code, partly be­cause these things are am­pli­fiers of ex­ist­ing ex­pe­ri­ence. If you know what you’re do­ing, you can run so much faster with them. […]

I’m con­stantly re­minded as I work with these tools how hard the thing that we do is. Producing soft­ware is a fe­ro­ciously dif­fi­cult thing to do. And you could give me all of the AI tools in the world and what we’re try­ing to achieve here is still re­ally dif­fi­cult. […]

Matthew Yglesias, who’s a po­lit­i­cal com­men­ta­tor, yes­ter­day tweeted, “Five months in, I think I’ve de­cided that I don’t want to vibecode — I want pro­fes­sion­ally man­aged soft­ware com­pa­nies to use AI cod­ing as­sis­tance to make more/​bet­ter/​cheaper soft­ware prod­ucts that they sell to me for money.” And that feels about right to me. I can plumb my house if I watch enough YouTube videos on plumb­ing. I would rather hire a plumber.

On the threat to SaaS providers of com­pa­nies rolling their own so­lu­tions in­stead:

I just re­al­ized it’s the thing I said ear­lier about how I only want to use your side pro­ject if you’ve used it for a few weeks. The en­ter­prise ver­sion of that is I don’t want a CRM un­less at least two other gi­ant en­ter­prises have suc­cess­fully used that CRM for six months. […] You want so­lu­tions that are proven to work be­fore you take a risk on them.

I just re­al­ized it’s the thing I said ear­lier about how I only want to use your side pro­ject if you’ve used it for a few weeks. The en­ter­prise ver­sion of that is I don’t want a CRM un­less at least two other gi­ant en­ter­prises have suc­cess­fully used that CRM for six months. […] You want so­lu­tions that are proven to work be­fore you take a risk on them.

The other month I fi­nally ran an ex­per­i­ment we had been post­pon­ing for over a year at .txt.

The goal was to test our struc­tured-gen­er­a­tion al­go­rithms and their open-source coun­ter­parts, re­plac­ing the naive “does it ac­cept this string?” with some­thing closer to the real prob­lem: “does it pro­duce the right to­ken dis­tri­b­u­tion?”

The ex­per­i­ment kept com­ing up in con­ver­sa­tion, then re­turn­ing to the roadmap. Last month, I spent half an hour ex­plain­ing the method to Codex. A few hours later, it had pro­duced a work­ing first ver­sion. That’s all it took.

Coding agents are trans­form­ing the way in­di­vid­u­als write code. In a way, that has al­ready hap­pened. And yet I re­main skep­ti­cal of the story peo­ple usu­ally tell about what this means for soft­ware as an in­dus­try: that in­di­vid­ual pro­duc­tiv­ity gains will trans­late into the in­dus­try mov­ing sub­stan­tially faster. I have been stuck on that ten­sion for months.

Time to re-read the clas­sics.

Impactful soft­ware tends to be writ­ten by many hu­mans that need to col­lab­o­rate.

Impactful soft­ware tends to be writ­ten by many hu­mans that need to col­lab­o­rate.

Discussions on cod­ing agents al­most ex­clu­sively fo­cus on the in­di­vid­ual pro­duc­tiv­ity gains. But col­lab­o­ra­tion is the in­ter­est­ing unit of analy­sis.

This is def­i­nitely not a new idea. Fred Brooks wrote about it in 1975 in The Mythical Man Month, and it was not new then; Gerald Weinberg in­tro­duced the idea in 1971 in The Psychology of Computer Programming. Software is what’s left over af­ter a group of hu­mans fin­ishes ne­go­ti­at­ing with each other about what the sys­tem should do. The code mat­ters, but it is the residue of the harder work, not the work it­self.

For fifty years the residue was ex­pen­sive enough to keep our at­ten­tion on it. Typing speed, lan­guage de­sign, frame­work choice, IDE plu­g­ins, code re­view tool­ing were all about re­duc­ing the cost of the residue. With cod­ing agents the cost has fallen far enough that we can see what’s un­der­neath: peo­ple try­ing to agree.

Negotiating, agree­ing, com­mu­ni­cat­ing the shared pic­ture of what we are build­ing has be­come the work. And it’s just as hard as it was.

The Roadmap is the Limit

The Roadmap is the Limit

What slows down a team where agents do the im­ple­men­ta­tion is the pro­duc­tion of spec­i­fi­ca­tions pre­cise enough for an agent to pick up and run. Roadmap, writ­ten down. Acceptance cri­te­ria, writ­ten down. The “what we ac­tu­ally want” forced into pre­ci­sion, be it via a test suite, a ticket, or a writ­ten de­sign.

Your mileage may vary, but many man­agers I know are over­whelmed by this. Features get im­ple­mented at break­neck speed, and en­gi­neers are not wait­ing on other en­gi­neers any­more. They are wait­ing on the next well-formed spec. The bot­tle­neck moves from the peo­ple writ­ing the code to the peo­ple de­cid­ing what code should ex­ist. Which is to say: man­age­ment.

Focus is say­ing no

Focus is say­ing no

And the sur­face that has to be agreed on is grow­ing. Jevons Paradox: when some­thing gets cheaper, you tend to use more of it, not less. When code gets 10x cheaper to write, we don’t spend 10% of the ef­fort on the same out­comes. We spend the same ef­fort on out­comes that weren’t worth pur­su­ing be­fore. Prototypes that would have been “not worth the time” three months ago get spun up in an af­ter­noon. Internal tools that solve prob­lems no­body quite had get built and for­got­ten.

Every vibe-coded prod­uct with 12 fea­tures is 11 fea­tures away from be­ing great.

People can only ab­sorb fea­tures at a cer­tain rate, and that rate stays roughly the same whether the team ships ten fea­tures or fifty. Steve Jobs in 1997: fo­cus is about say­ing no. Apple killed roughly sev­enty per­cent of its prod­uct line that year, and the com­pany that came back was the one that had learned to sub­tract. The dis­ci­pline got harder with agents; don’t we all like the feel­ing of ship­ping a new fea­ture?

Context is gold.

Context is gold.

All of that ne­go­ti­a­tion runs on some­thing hu­mans rarely think about: shared con­text.

Context is the com­mod­ity an or­ga­ni­za­tion runs on. It is the shared un­der­stand­ing of what we are build­ing, why it mat­ters, what has been tried, who de­cided what, what is load-bear­ing and what is ves­ti­gial. Humans on a team ac­crete it by os­mo­sis. By be­ing in the room, by read­ing the same Slack chan­nel, by de­bug­ging the same out­age at two in the morn­ing. Most of it is never writ­ten down. When a se­nior en­gi­neer re­views a PR and says “this’ll break the mi­gra­tion,” they are draw­ing on con­text that has no doc­u­ment.

Agents can­not do os­mo­sis. They do not get con­text by be­ing in the room, by half-hear­ing the plan­ning con­ver­sa­tion, or by car­ry­ing the mem­ory of the last in­ci­dent. Whatever you do not man­age to pack into the prompt, the file tree, the tools, or the ex­plicit in­struc­tions, they do not re­li­ably have. Without con­text, an agent will pro­duce a plau­si­ble an­swer to a slightly wrong ver­sion of the ques­tion.

So when I find my­self ex­cited about an agent that did some­thing use­ful at .txt, the hon­est ac­count­ing is that we did the con­text work. The next ten en­gi­neers will not have that pic­ture by de­fault. They will have it only to the ex­tent we get se­ri­ous about writ­ing it down.

Context, the un­writ­ten sub­strate or­ga­ni­za­tions have al­ways run on, is now the rate-lim­it­ing in­put. And the nat­ural thing for hu­mans to do is leave it im­plicit, be­cause there was never any­one to read the ex­plicit ver­sion.

Real pro­gram­mers don’t doc­u­ment their pro­grams.

Real pro­gram­mers don’t doc­u­ment their pro­grams.

Producing eas­ily con­sum­able con­text is pre­cisely the thing hu­mans don’t like to do.

What may save us it that agents are un­rea­son­ably good at read­ing ex­haus­tively. An agent will read every PR com­ment, every closed is­sue, every com­mit mes­sage, every stale de­sign doc, every Slack archive, and ex­tract pat­terns no­body both­ered to write down be­cause no­body was go­ing to read them.

We have started build­ing this at .txt. Agents that crawl the code­base, the is­sues, the PRs, the threads, and pro­duce a knowl­edge base of the im­plicit de­ci­sions, the con­ven­tions, the why-we-did-it-this-way that no­body had time to doc­u­ment. Not just “this mod­ule ex­ists,” but “this mod­ule is weird be­cause the mi­gra­tion had to pre­serve old be­hav­ior,” or “this bench­mark mat­ters be­cause a pre­vi­ous op­ti­miza­tion silently changed the dis­tri­b­u­tion.” Other agents use that knowl­edge base when they need to act on the code­base. The os­mo­sis hu­mans do in­for­mally is be­ing ex­ter­nal­ized into some­thing agents can read, and hu­mans can too.

Agents that con­sume con­text need agents that pro­duce it. Once that loop is run­ning, the or­ga­ni­za­tion has a writ­ten sub­strate it would never have pro­duced on its own. The con­straint that was rate-lim­it­ing in the pre­vi­ous sec­tion stops be­ing con­stant. Context be­comes a thing you can pro­duce more of.

Of course, this loop will only ever pro­duce a par­tial pic­ture. To quote Michael Polanyi: we know more than we can tell. Some load-bear­ing con­text ex­ists pre­cisely be­cause it was never put into words, and writ­ing it down would change what it is. The os­mo­sis layer hu­mans ac­crete in per­son is not fully re­cov­er­able from writ­ten ex­haust. What comes out the other side is closer to a use­ful start­ing point than to a full re­cov­ery, and whether that is enough to com­pound is an em­pir­i­cal ques­tion I’m still test­ing. I think it is. I’m not sure.

The new moat is or­ga­ni­za­tional, not tech­ni­cal.

The new moat is or­ga­ni­za­tional, not tech­ni­cal.

The com­pa­nies that win the next decade will not nec­es­sar­ily have the best mod­els or the best agent in­fra­struc­ture. It will be the com­pa­nies whose fifty peo­ple, then two hun­dred, then two thou­sand, can stay aligned on a shrink­ing set of de­ci­sions while ship­ping more out­put per head. They will be the ones that al­ready knew, be­fore agents ar­rived, that their hard­est prob­lem was co­her­ence.

That is a cul­ture and man­age­ment prob­lem. Always has been.

Every pre­vi­ous gen­er­a­tion of tool­ing, whether IDEs, ver­sion con­trol, CI, mi­croser­vices, or de­vops, promised to solve co­or­di­na­tion through bet­ter tools. Every one of them turned out to be a mul­ti­plier on what­ever or­ga­ni­za­tional co­her­ence was al­ready there. Small teams have co­her­ence for free; the mul­ti­plier is uni­formly pos­i­tive there, which is why the loud­est agent boost­ers tend to be small teams, and why they are mostly right about their own con­text. Past a cer­tain size, co­her­ence has to be pro­duced and main­tained, and the mul­ti­plier sharp­ens in both di­rec­tions. Good orgs got bet­ter. Bad orgs got faster at ru­in­ing things.

Agents are a much big­ger mul­ti­plier than any of those. The sig­nal is go­ing to be louder in both di­rec­tions. They are over­es­ti­mated as a way to make in­di­vid­u­als write code faster, and un­der­es­ti­mated as a way to make or­ga­ni­za­tions ex­ter­nal­ize what they know.

Agents can feel like the ex­ten­sion of your own mind, and that feel­ing is ex­hil­a­rat­ing. The harder chal­lenge is mak­ing them an ex­ten­sion of your com­pany cul­ture. That is a dif­fer­ent prob­lem and a dif­fer­ent shape of work. It needs writ­ing cul­ture. It needs man­age­ment thought­ful enough to iden­tify where they re­main a con­text bot­tle­neck. It needs peo­ple who treat co­her­ence as a real ar­ti­fact to main­tain. What’s new is that some of those things are build­able now. The read-and-ex­tract loop is one shape, and there will be oth­ers.

I’ll re­port back on the ex­per­i­ment.

We’ve agreed to a part­ner­ship with SpaceX that will sub­stan­tially in­crease our com­pute ca­pac­ity. This, along with our other re­cent com­pute deals, means that we’ve been able to in­crease our us­age lim­its for Claude Code and the Claude API.

Below, we de­scribe these changes and the progress we’re mak­ing on com­pute.

The fol­low­ing three changes—all ef­fec­tive to­day—are aimed at im­prov­ing the ex­pe­ri­ence of us­ing Claude for our most ded­i­cated cus­tomers.

First, we’re dou­bling Claude Code’s five-hour rate lim­its for Pro, Max, Team, and seat-based Enterprise plans.

Second, we’re re­mov­ing the peak hours limit re­duc­tion on Claude Code for Pro and Max ac­counts.

Third, we’re rais­ing our API rate lim­its con­sid­er­ably for Claude Opus mod­els, as shown in the table be­low:

New com­pute part­ner­ship with SpaceX

We’ve signed an agree­ment with SpaceX to use all of the com­pute ca­pac­ity at their Colossus 1 data cen­ter. This gives us ac­cess to more than 300 megawatts of new ca­pac­ity (over 220,000 NVIDIA GPUs) within the month. This ad­di­tional ca­pac­ity will di­rectly im­prove ca­pac­ity for Claude Pro and Claude Max sub­scribers.

This joins our other sig­nif­i­cant com­pute an­nounce­ments:

An up to 5 gi­gawatt (GW) agree­ment with Amazon, which in­cludes nearly 1 GW of new ca­pac­ity by the end of 2026;

A 5 GW agree­ment with Google and Broadcom, which will be­gin com­ing on­line in 2027;

A strate­gic part­ner­ship with Microsoft and NVIDIA that in­cludes $30 bil­lion of Azure ca­pac­ity;

Our $50 bil­lion in­vest­ment in American AI in­fra­struc­ture with Fluidstack.

We train and run Claude on a range of AI hard­ware—AWS Trainium, Google TPUs, and NVIDIA GPUs—and con­tinue to ex­plore op­por­tu­ni­ties to bring ad­di­tional ca­pac­ity on­line.

As part of this agree­ment, we have also ex­pressed in­ter­est in part­ner­ing with SpaceX to de­velop mul­ti­ple gi­gawatts of or­bital AI com­pute ca­pac­ity.

Expanding in­ter­na­tion­ally

Our en­ter­prise cus­tomers—par­tic­u­larly those in reg­u­lated in­dus­tries like fi­nan­cial ser­vices, health­care, and gov­ern­ment—in­creas­ingly need in-re­gion in­fra­struc­ture to meet com­pli­ance and data res­i­dency re­quire­ments. Accordingly, some of our ca­pac­ity ex­pan­sion will be in­ter­na­tional: our re­cently an­nounced col­lab­o­ra­tion with Amazon in­cludes ad­di­tional in­fer­ence in Asia and Europe.

We’re very in­ten­tional about where we’ll add ca­pac­ity—part­ner­ing with de­mo­c­ra­tic coun­tries whose le­gal and reg­u­la­tory frame­works sup­port in­vest­ments of this scale, and where the sup­ply chain on which our com­pute de­pends—hard­ware, net­work­ing, and fa­cil­i­ties—will be se­cure.

Finally, we re­cently made a com­mit­ment to cover any con­sumer elec­tric­ity price in­creases caused by our data cen­ters in the US. As part of our in­ter­na­tional ex­pan­sion, we’re ex­plor­ing ways to ex­tend that com­mit­ment to new ju­ris­dic­tions, as well as part­ner­ing with lo­cal lead­ers to in­vest back into the com­mu­ni­ties that host our fa­cil­i­ties.

Related con­tent

Agents for fi­nan­cial ser­vices

We’re re­leas­ing ten new Cowork and Claude Code plu­g­ins, in­te­gra­tions with the Microsoft 365 suite, new con­nec­tors, and an MCP app for fi­nan­cial ser­vices and in­sur­ance or­ga­ni­za­tions.

Read more

Building a new en­ter­prise AI ser­vices com­pany with Blackstone, Hellman & Friedman, and Goldman Sachs

Read more

Sorry Peter.

—

I’m at a birth­day party, and while most peo­ple here also work in tech, there’s al­ways a Guy with a Real Job. You know, a phys­i­cal job, build­ing some or other thing peo­ple need. And this Guy al­ways asks some vari­ant of the same ques­tion: aren’t you wor­ried AI is tak­ing your job? I glance around and see a few faces turn­ing around to­ward us, rolling their eyes ever so slightly be­fore re­turn­ing to their pre­vi­ous con­ver­sa­tion. Yes, this ques­tion again.

They have a nephew who builds Shopify stores, they don’t un­der­stand half the words he uses but he’s in real trou­ble and says every­body in tech is. Is his nephew gonna have to learn a “trade”? Are we all?

Enough drinks in and I’ll an­swer proper, be­cause I don’t care any­more whether oth­ers think what I’m say­ing is in­ter­est­ing or true. But usu­ally I’ll sigh and say “Sure, yeah a lit­tle. Most of us are. Would be stu­pid not to be, right?” to which they nod be­fore mov­ing on to a lighter topic, like whether we’re go­ing to nuke Iran or not.

The truth is, work­ing in tech al­ways sucked, and never re­ally was what they thought it was.

My job, some peo­ple think, is to sit at a clean desk in a cor­ner of­fice, sur­rounded by open of­fices filled with long ta­bles with MacBooks or Thinkpads. In my cor­ner of­fice, I de­vise per­fect plans, that my per­fect em­ploy­ees ap­plaud me for. None es­cape my gaze, every de­ci­sion is made, per­fectly, by me, and every cent and minute is ac­counted for.

When the ap­plause fades, my em­ploy­ees, or re­ports, or “my team” when I’m feel­ing jolly, start fu­ri­ously typ­ing. Typing typ­ing typ­ing. And not long af­ter, per­fect soft­ware is pro­duced. It rolls off the col­lec­tive as­sem­bly line, and like a first child, it can do no wrong.

Except, that’s not what any­thing is like at all. Yes, I’m up­set I never got a cor­ner of­fice, but I’m too busy pan­ick­ing be­cause I have no idea what I’m do­ing, no­body does, and the wheels just came off. The CEO says AI is mak­ing his buddy Jared’s team so pro­duc­tive he was able to fire half of them, but like, as a brag, not a threat? I dunno, I felt threat­ened, but that’s prob­a­bly just my anx­i­ety flar­ing up. Surely I can bor­row a xanax from one of the sev­eral em­ploy­ees cry­ing in the bath­room.

Imagine you take a job as a ship cap­tain. You bike into the har­bor on your first day, ex­cited to meet your crew. You no­tice the ship is­n’t there, but Greg, the very ex­citable re­cruiter you spoke to, waves you over and as­sures you it’s not a prob­lem. You’re strapped to a cat­a­pult and mirac­u­lously launched onto the ship. The pre­vi­ous cap­tain started a fire be­cause an­other cap­tain ex­plained in­ter­nal com­bus­tion to him at Captainpalooza 2025, and he wanted to start it­er­at­ing to­wards that. He was pushed off the ship, but took the man­ual with him. Wouldn’t be a prob­lem if it weren’t for the fact the en­tire ship was cus­tom-built for him. The ship still has sails, but they’re not con­nected to the mast, and the in­ter­nal com­bus­tion en­gine semi-bolted to the stern still has parts scat­tered all over the deck.

You go be­low deck to fig­ure out how the ship works and where you’re go­ing, but when you fol­low the stairs to the lower decks you some­how end up in the mast? You ask a sailor what’s hap­pen­ing. He glitches and says “You’re ab­solutely right! My ap­proach was flawed, but here’s a bet­ter stairs im­ple­men­ta­tion”. The mast snaps up­side down, and you’re back on deck, right where you started. The sails are up­side down, and your “sailor” ex­cit­edly waits for you to tell him how well he’s done.

You ask some­one else “wait, where are we even go­ing?”, and yay a hu­man! No glitch­ing, no peppy but un­help­ful an­swers, an ac­tual hu­man be­ing. She has­n’t slept in a week. She barely looks at you and says “ask the nav­i­ga­tor”. “The nav­i­ga­tor?”, you ask. She points. The nav­i­ga­tor is a doll that says “onward and up­ward” when you press a but­ton on its back.

The doll catches fire.

This is the job now. You’re stand­ing on a burn­ing ship, hold­ing a map, try­ing to fig­ure out where the hell we’re go­ing and how we’re go­ing to get there.

You know this ship. Some of you were en­gi­neers on one just like it. Some of you were the cap­tain who left. I’m not writ­ing this for the Guy at the birth­day party. I’m writ­ing it for you.

You were an en­gi­neer once. You re­mem­ber what a code re­view was for. You re­mem­ber be­ing the ju­nior whose first PR got shred­ded by a se­nior who took the time to ex­plain why. You did­n’t wake up one morn­ing in 2024 and de­cide to abol­ish that.

What hap­pened was: the run­way got cut. The board meet­ing did­n’t have the word “values” in it any­where. The CFO had a spread­sheet. The CEO had come back from an off­site where some­one had shown him a demo of an agent writ­ing a whole fea­ture in four­teen min­utes, and he had be­lieved it (the way peo­ple be­lieve things when they want to be­lieve them) and he had told the board he could cut thirty per­cent of en­gi­neer­ing by Q2. Now it was your job to fig­ure out how.

You told your­self the ju­niors would be fine. They’d adapt, they’d reskill, they’d land some­where. You told your­self the se­niors could ab­sorb the miss­ing hands, that the agents would cover the gap. You told your­self you’d re­visit it next quar­ter. You signed the list. You went home. You drank a lit­tle more than usual. You went to sleep.

You knew.

You knew, be­cause you’d been the en­gi­neer who had to clean up af­ter the last leader who’d been sold a sim­ple an­swer. You’d watched Goodhart’s Law eat ve­loc­ity met­rics, story points, test cov­er­age; every num­ber a non-en­gi­neer had ever been handed as proof the work was go­ing well. You knew the DORA met­rics were al­ready telling you what hap­pens to de­ploy­ment sta­bil­ity when you add tool­ing faster than you add judg­ment. You knew what hap­pens to a code­base when the peo­ple who’d catch the er­rors get pushed out, or learn to stop catch­ing them.

You knew. And you signed off any­way. Because the al­ter­na­tive was los­ing the job, and the job was the mort­gage, and the school fees, and the visa, and the ver­sion of your­self who’d fix it later once things sta­bi­lized.

Later is never. We all knew that. I signed a list too. We’re still point­ing at each other about whose list was worse.

There are no more ju­niors. There was a fu­neral for their pass­ing in 2024. Nobody came. The ma­chine does what they do now, but cheaper. Of course, ju­niors weren’t valu­able for what they pro­duced, they were valu­able for who they would be­come: the se­nior en­gi­neer who knows where the bod­ies are buried. We op­ti­mized for out­put, and abol­ished ap­pren­tice­ship. A few years from now, we’ll won­der where all the se­niors are. We shot them. Nobody will re­mem­ber.

And yet…

Somewhere in your in­fra­struc­ture is a cron job. It runs at 3am. It has been run­ning since 2016. It does some­thing crit­i­cal. You could­n’t tell me ex­actly what, but you know the one per­son who could, and they left in 2019. The com­ment at the top says # DO NOT CHANGE!!! Ask Ben. Ben is not reach­able. Every roadmap plan­ning ses­sion for the last four years has in­cluded “modernize legacy cron” as a can­di­date ini­tia­tive. It has never made the cut. You have per­son­ally re­moved it from the list twice.

Someone keeps it run­ning. Her name is Sara. You don’t know this.

She’s in her mid 50s. She did­n’t go to Captainpalooza. She used to work from a small of­fice three streets from head­quar­ters. Somebody closed it last year to save money. The ship was the clos­est place with a desk and a net­work con­nec­tion, so she packs a lunch now and takes the gang­way down to a cabin be­lowdecks. Nobody on the ship knows she’s there. Remember Ben? Well, she in­her­ited the cron job from Ben, who’s men­tored her since 1998.

She knows Ben passed a few years back. She went to his fu­neral. You don’t know this.

When the job gets stuck, which it does reg­u­larly, she gives it a nudge and it tries again. The phone rings. She ac­knowl­edges the is­sue. She gives the nudge. The job de­pends on a mod­ule that’s been lost to time. Well, al­most, be­cause she has a copy on a USB stick she found in Ben’s desk af­ter his pass­ing. No agent has touched it. None ever will.

She’s not the safest per­son in the in­dus­try. She’s the shape of what you can­not touch. She is every piece of in­sti­tu­tional knowl­edge your trans­for­ma­tion just deleted, walk­ing around in a fifty-five-year-old body. She came up through the ap­pren­tice­ship you abol­ished: Ben, 1998, the USB stick. She is the pipeline. When she dies, the thing that pro­duces peo­ple like her is al­ready gone. You killed it three years ago. You will not be able to hire her re­place­ment, be­cause you broke the ma­chine that makes her.

She’s the man tun­nel­ing un­der Mordor with a spoon. The spoon is hers. So is the tun­nel. Nobody else wants the spoon or the tun­nel, and when she dies, the cron job dies, salaries stop be­ing paid, a com­pany of 30,000 souls will need to fig­ure out how to pay every­body, and there will be only one an­swer: hire some­one with a spoon. You won’t find them. You made sure of that.

The cron job pays salaries. You don’t know this.

The Guy at the party is still wait­ing for an an­swer. I’m too drunk now to lie. I tell him: AI did­n’t take our jobs. Greed did. Same greed that moved fac­to­ries to Bangladesh and keeps slaves in cobalt mines in the Congo, wear­ing a new mask. Tell the nephew to do some­thing else. Anything. It won’t save him ei­ther, but at least he won’t have to pre­tend the thing de­stroy­ing his life is a ro­bot.

Except Sara. Below decks, with her USB stick. They can’t come for her be­cause they don’t know she’s there.

The rest of us are above deck, won­der­ing why the masts are up­side down, and what that doll over there does.

The doll catches fire.

Released on May 6, 2026.

Contents (click to ex­pand/​col­lapse)

1 Changes and Bug Fixes

1.1 Highlights 1.2 Crash Fixes 1.3 General User Interface

1.3.1 Canvas 1.3.2 General 1.3.3 Clipping 1.3.4 Copy / Paste

1.4 Dialogs

1.4.1 Fill and Stroke Dialog

1.4.2 Layers and Objects Dialog

1.4.3 Object Properties Dialog

1.4.4 Preferences Dialog 1.4.5 Welcome Dialog

1.5 Tools

1.5.1 Gradient Tool 1.5.2 Star / Polygon Tool 1.5.3 Text Tool

1.6 Keyboard Shortcuts 1.7 Palettes 1.8 Templates 1.9 Command Line

1.10 Windows-specific Fixes

1.11 Improvements for Development / Deployment / Testing

1.1 Highlights

1.2 Crash Fixes

1.3 General User Interface

1.3.1 Canvas 1.3.2 General 1.3.3 Clipping 1.3.4 Copy / Paste

1.3.1 Canvas

1.3.2 General

1.3.3 Clipping

1.3.4 Copy / Paste

1.4 Dialogs

1.4.1 Fill and Stroke Dialog

1.4.2 Layers and Objects Dialog

1.4.3 Object Properties Dialog

1.4.4 Preferences Dialog 1.4.5 Welcome Dialog

1.4.1 Fill and Stroke Dialog

1.4.2 Layers and Objects Dialog

1.4.3 Object Properties Dialog

1.4.4 Preferences Dialog

1.4.5 Welcome Dialog

1.5 Tools

1.5.1 Gradient Tool 1.5.2 Star / Polygon Tool 1.5.3 Text Tool

1.5.1 Gradient Tool

1.5.2 Star / Polygon Tool

1.5.3 Text Tool

1.6 Keyboard Shortcuts

1.7 Palettes

1.8 Templates

1.9 Command Line

1.10 Windows-specific Fixes

1.11 Improvements for Development / Deployment / Testing

2 Known Issues

3 Translations

3.1 Contributing to in­ter­face trans­la­tions

3.1 Contributing to in­ter­face trans­la­tions

4 Documentation

4.1 Contributing to doc­u­men­ta­tion and doc­u­men­ta­tion trans­la­tion

4.1 Contributing to doc­u­men­ta­tion and doc­u­men­ta­tion trans­la­tion

Get Inkscape 1.4.4!

Changes and Bug Fixes

Highlights

Inkscape 1.4.4 is a main­te­nance and bug­fix re­lease, which brings you

20 crash fixes, among them for three nasty bugs where Inkscape would­n’t even start

al­most 20 bug fixes

6 per­for­mance im­prove­ments

a new palette

a new but­ton for ro­tat­ing stars and poly­gons into their ‘neutral’ or ‘upright’ po­si­tion

27 up­dated in­ter­face trans­la­tions

15 up­dated doc­u­men­ta­tion trans­la­tions

in­stal­la­tion files for Windows on Arm

Like its pre­de­ces­sor, Inkscape 1.4.4 is also a bridge re­lease in the sense that it can be used to con­vert the planned Inkscape 1.5 mul­ti­page file for­mat to the pre-1.5 mul­ti­page for­mat. Versions lower than Inkscape 1.4.3 will not be able to in­ter­pret pages cre­ated in Inkscape ver­sions 1.5 and up­wards. Opening a doc­u­ment in Inkscape 1.4.3 and sav­ing it will con­vert it to the cur­rent (‘old’) page for­mat (MR #7608).

Background: While the ‘old’ for­mat of pages in Inkscape is a cus­tom ad­di­tion that only works in Inkscape, the new for­mat will make use of the svg:view el­e­ment, which is stan­dard­ized and can work in other SVG view­ers, too. Find more in­for­ma­tion about this in MR #7525.

Crash Fixes

Fixed a crash …

… try­ing to start Inkscape when there are two en­tries for the same file in the list of re­cently used files (Bug 6002, MR #7750)

… try­ing to start Inkscape on Windows, when two re­cently opened files are in the same folder on dif­fer­ent dri­ves (Bug #6028, MR #7754)

… when start­ing Inkscape with a graph­ics tablet plugged in (Bug #5618, MR #7665)

… when cre­at­ing a new page (Bug #5904, MR #7417)

… when un­do­ing the cre­ation of a new doc­u­ment page (Bug #6060, MR #7787)

… when clos­ing the Unicode Characters di­a­log (Bug #6014, MR #7853)

… when try­ing to open some spe­cific PDF files (Bug #6021, MR #7690)

… when try­ing to open an SVG file with bro­ken mark­ers (Bug #6040, MR #7768)

… when open­ing or clos­ing cer­tain SVG files with the Export di­a­log open (Bug #5141, MR #7139)

… when try­ing to open an SVG file with a bro­ken Rotate Copies Live Path Effect cre­ated with Inkscape older than ver­sion 1.2 (Bug #5991, MR #7782)

… when set­ting the width or height field of an im­ported raster im­age with locked width/​height ra­tio to zero or no value (Bug #5428, MR #7139)

… when us­ing the Tweak tool with an empty text ob­ject in the se­lec­tion (Bug #5918, MR #7474)

… when us­ing the XML ed­i­tor to delete the path data (‘d’) of a con­nec­tor cre­ated with the Connector Tool (MR #7772)

… when try­ing to undo a line cre­ated with the Connector Tool un­der cer­tain cir­cum­stances (Bug #5949, MR #7510)

… when try­ing to use the Connector Tool to con­nect two ob­jects that over­lap (Bug #5314, MR #7535)

… when se­lect­ing an ob­ject with the PowerStroke Live Path Effect (Bug #5997, MR #7723)

… when try­ing to ap­ply the Corners LPE to a group (which is­n’t pos­si­ble) (Bug #5984, MR #7845)

… when try­ing to edit a gra­di­ent af­ter re­mov­ing one of its stops by us­ing the XML Editor (Bug #1299, MR #7532)

… when try­ing to use Break Apart with cer­tain com­plex paths (Bug #6067, MR #7800)

… when try­ing to trace a raster im­age with the max­i­mum num­ber of traces (Bug #5475, MR #7880)

General User Interface

Canvas

When us­ing the Layers and Objects di­a­log to move ob­jects be­tween groups, the bound­ing boxes on the can­vas will now show the cor­rect size and po­si­tion again (Bug #5996, MR #7704).

When zoom­ing in on a doc­u­ment with lots of paths, Inkscape is much faster now (Bug #6110, MR #7876).

General

Graphics that con­tain the ver­sion num­ber (1.4.4) have been up­dated for the new re­lease (MR #7855).

Clipping

Releasing an Inverse Clip (Live Path Effect) will no longer leave the clip path in­vis­i­ble (Bug #5966, MR #7521).

Copy / Paste

Copy-pasting large num­bers of ob­jects with gra­di­ents is faster now (Bug #2403, MR #7856).

When copy­ing some­thing to the clip­board, Inkscape could ran­domly be very slow with some clip­board man­ager con­stel­la­tions / PovRay be­ing used, and con­tent pasted could some­times be in the wrong for­mat (MR #7858).

Dialogs

Fill and Stroke Dialog

The agen­tic web — where au­tonomous AI agents rea­son, plan, and ex­e­cute com­plex trans­ac­tions us­ing the open web and in­dus­try stan­dard pro­to­cols — aims to cre­ate an au­tonomous cus­tomer ex­pe­ri­ence. While these agents can sig­nif­i­cantly en­hance on­line in­ter­ac­tions, they also in­tro­duce new abuse and fraud vec­tors, cre­at­ing unique chal­lenges for se­cu­rity plat­forms.

This rise in so­phis­ti­cated au­toma­tion re­quires a fun­da­men­tal shift in risk man­age­ment. Today at Google Cloud Next, we are launch­ing Google Cloud Fraud Defense, a trust plat­form for the agen­tic web. As the next evo­lu­tion of re­CAPTCHA, Fraud Defense is a com­pre­hen­sive plat­form de­signed to ver­ify the le­git­i­macy of bots, hu­mans, and AI agents, pro­vid­ing busi­nesses with the in­tel­li­gence needed to se­cure their dig­i­tal in­ter­ac­tions and com­merce.

Agentic ac­tiv­ity in the Fraud Defense dash­board.

As part of our mis­sion to en­able a safe agen­tic web, Fraud Defense in­tro­duces a pow­er­ful suite of ca­pa­bil­i­ties that al­low cus­tomers to mea­sure and con­trol agen­tic ac­tiv­ity on their web­sites. By us­ing the same global sig­nals that pro­tect Google’s own ecosys­tem, busi­nesses can now en­able trusted ex­pe­ri­ences for both hu­man users and AI agents alike.

Creating poli­cies for agen­tic traf­fic in the Fraud Defense pol­icy en­gine.

These new ca­pa­bil­i­ties in­clude:

Agentic ac­tiv­ity mea­sure­ment: A new dash­board to help you mea­sure and un­der­stand agen­tic ac­tiv­i­ties. We are in­te­grat­ing with in­dus­try stan­dards such as Web Bot Auth and SPIFEE, as well as us­ing tra­di­tional meth­ods, to iden­tify, clas­sify, and an­a­lyze agen­tic traf­fic, and con­nect­ing agent and hu­man iden­ti­ties to bet­ter un­der­stand risk and trust.

Agentic ac­tiv­ity mea­sure­ment: A new dash­board to help you mea­sure and un­der­stand agen­tic ac­tiv­i­ties. We are in­te­grat­ing with in­dus­try stan­dards such as Web Bot Auth and SPIFEE, as well as us­ing tra­di­tional meth­ods, to iden­tify, clas­sify, and an­a­lyze agen­tic traf­fic, and con­nect­ing agent and hu­man iden­ti­ties to bet­ter un­der­stand risk and trust.

Agentic pol­icy en­gine: To pro­vide you with gran­u­lar con­trol at dif­fer­ent stages of the end user in­ter­ac­tion across the en­tire jour­ney, Fraud Defense’s agen­tic pol­icy en­gine al­lows you to al­low and block agents and users based on con­di­tions that in­clude risk scores, au­toma­tion types, and agent iden­tity.

AI-resistant chal­lenge: As we iden­tify po­ten­tially fraud­u­lent be­hav­ior from agents, we en­able ap­pli­ca­tion providers to de­ter and mit­i­gate ma­li­cious re­quests by re­quest­ing hu­mans to be in the loop us­ing the new QR code-based chal­lenge. This AI-resistant mit­i­ga­tion chal­lenge to prove hu­man pres­ence is de­signed to make au­to­mated fraud eco­nom­i­cally un­vi­able.

New QR-code chal­lenge in a shop­ping web­site.

re­CAPTCHA will con­tinue to be the core bot de­fense pil­lar of the broader Fraud Defense plat­form. Existing re­CAPTCHA cus­tomers are au­to­mat­i­cally Fraud Defense cus­tomers, with no mi­gra­tion re­quired, no ac­tion needed, and no change to pric­ing. Your ex­ist­ing site keys and in­te­gra­tions re­main ex­actly as they are to­day.

The trust plat­form for the agen­tic web

At Google Cloud, we be­lieve pre­vent­ing fraud and abuse in the agen­tic web should fun­da­men­tally re­sult in a sim­pler cus­tomer ex­pe­ri­ence. Fraud Defense uses a three-pronged ap­proach to help en­able a safe agen­tic web and drive busi­ness growth:

1. Preventing evolv­ing threats We pro­tect your busi­ness with the same fraud in­tel­li­gence that se­cures many of Google’s ser­vices. As threats shift from bot au­toma­tion and in­valid traf­fic to agent takeover and large-scale, AI-driven syn­thetic iden­tity fraud, Fraud Defense iden­ti­fies emerg­ing threats be­fore they reach your site.

This un­ri­valed vis­i­bil­ity, built upon a mas­sive fraud in­tel­li­gence graph that al­ready pro­tects 50% of Fortune 100 com­pa­nies and over 14 mil­lion do­mains glob­ally, pro­vides a level of col­lec­tive im­mu­nity and ver­i­fied trust that lo­cal data alone can not match.

2. Securing the cus­tomer jour­ney­At­tack­ers don’t tar­get end­points in iso­la­tion; they tar­get dig­i­tal jour­neys. This is even more true in the agen­tic web as agents are be­ing tasked to per­form end to end jour­neys. Fraud Defense pro­vides a uni­fied view of risk — from reg­is­tra­tion and lo­gin to pay­ment and check­out.

By cor­re­lat­ing teleme­try across the en­tire life­cy­cle, our uni­fied trust model iden­ti­fies com­plex, multi-stage fraud cam­paigns that dis­con­nected point so­lu­tions miss. This holis­tic view has demon­strated a 51% av­er­age re­duc­tion in ac­count takeover (ATO) by ac­cu­rately dis­tin­guish­ing be­tween le­git­i­mate cus­tomer ac­tiv­ity and so­phis­ti­cated abuse.

3. Accelerating busi­ness growthIn the agen­tic econ­omy, fric­tion kills con­ver­sion. Fraud Defense is de­signed to be in­vis­i­ble for the ma­jor­ity of users, re­plac­ing dis­rup­tive puz­zles with silent back­ground ver­i­fi­ca­tion. By us­ing our in­tel­li­gent trust model, we al­low you to sur­gi­cally block ma­li­cious bots, hu­mans and agents, while con­fi­dently wel­com­ing le­git­i­mate users, in­clud­ing AI shop­ping as­sis­tants that drive a pro­jected 25% in­crease in av­er­age or­der value, ac­cord­ing to the 2025 Shopify Retail Report.

Learn more about how Fraud Defense works

We in­vite you to join us at Next ’26 to talk about new ca­pa­bil­i­ties de­signed to help pro­tect you as you con­tinue your jour­ney on the agen­tic web. While you’re there, be sure to at­tend our break­out ses­sion and visit our demo pod, where you can see Fraud Defense in ac­tion and learn more di­rectly from our ex­perts. We look for­ward to meet­ing you there and dis­cussing how we can safe­guard your or­ga­ni­za­tion’s fu­ture in this chang­ing land­scape.

To take the next step in your jour­ney to the agen­tic web, please check out the Fraud Defense web­site and log into the con­sole. You can fol­low all of our se­cu­rity an­nounce­ments at Next ’26 here.

Security & Identity

Google Cloud Next

US

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CNN founder Ted Turner dead at 87

2:25

• Source:

CNN

CNN founder Ted Turner dead at 87

2:25

Ted Turner, the me­dia mav­er­ick and phil­an­thropist who founded CNN, a pi­o­neer­ing 24-hour net­work that rev­o­lu­tion­ized tele­vi­sion news, died peace­fully Wednesday, sur­rounded by his fam­ily, ac­cord­ing to a news re­lease from Turner Enterprises. He was 87.

The Ohio-born Atlanta busi­ness­man, nick­named “The Mouth of the South” for his out­spo­ken na­ture, built a me­dia em­pire that en­com­passed ca­ble’s first su­per­sta­tion and pop­u­lar chan­nels for movies and car­toons, plus pro­fes­sional sports teams like the Atlanta Braves.

Turner was also an in­ter­na­tion­ally known yachts­man; a phil­an­thropist who founded the United Nations Foundation; an ac­tivist who sought the world­wide elim­i­na­tion of nu­clear weapons; and a con­ser­va­tion­ist who be­came one of the fore­most landown­ers in the United States. He played a cru­cial role in rein­tro­duc­ing bi­son to the American west. He even cre­ated the Captain Planet car­toon to ed­u­cate kids about the en­vi­ron­ment.

But it was his au­da­cious vi­sion to de­liver news from around the world in real time, at all hours, that re­ally made him fa­mous — once his idea fi­nally took off.

Ted Turner’s life in pic­tures

In 1991, Turner was named Time mag­a­zine’s Man of the Year for “influencing the dy­namic of events and turn­ing view­ers in 150 coun­tries into in­stant wit­nesses of his­tory.”

Turner even­tu­ally sold his net­works to Time Warner and later ex­ited the busi­ness, but con­tin­ued to ex­press pride in CNN, call­ing it the “greatest achieve­ment” of his life.

“Ted was an in­tensely in­volved and com­mit­ted leader, in­tre­pid, fear­less and al­ways will­ing to back a hunch and trust his own judge­ment,” Mark Thompson, Chairman and CEO of CNN Worldwide, said in a state­ment. “He was and al­ways will be the pre­sid­ing spirit of CNN. Ted is the gi­ant on whose shoul­ders we stand, and we will all take a mo­ment to­day to rec­og­nize him and his im­pact on our lives and the world.”

Turner was “a leg­end, he rev­o­lu­tion­ized the tele­vi­sion busi­ness by cre­at­ing the first 24-hour news chan­nel right here at CNN,” Wolf Blitzer said Wednesday morn­ing as he an­nounced Turner’s death on-air.

Ted Turner speaks on CNN Newsroom in 1995

0:58

• Source:

CNN

Ted Turner speaks on CNN Newsroom in 1995

0:58

“We’re all here do­ing this be­cause of Ted,” Blitzer’s co-an­chor Pamela Brown said.

“He was the orig­i­nal,” Christiane Amanpour said. “He made us all proud, he made us all hope­ful, and he made us all strive for his vi­sion of a bet­ter world.”

Just over a month be­fore his 80th birth­day in 2018, Turner re­vealed that he had Lewy body de­men­tia, a pro­gres­sive brain dis­or­der. In early 2025, Turner was hos­pi­tal­ized with a mild case of pneu­mo­nia be­fore re­cov­er­ing at a re­ha­bil­i­ta­tion fa­cil­ity.

Turner is sur­vived by his five chil­dren, 14 grand­chil­dren, and two great-grand­chil­dren.

Turner be­gan his me­dia ca­reer at the age of 24 when he took over his fa­ther’s bill­board com­pany, Turner Outdoor Advertising, in the wake of the el­der Turner’s sui­cide. He buried his shock and grief in work — but Turner was­n’t con­tent to push other peo­ple’s prod­ucts for­ever.

He bought up ra­dio sta­tions, then branched into tele­vi­sion in 1970 by ac­quir­ing a strug­gling sta­tion in Atlanta known as Channel 17. He tried to boost the rat­ings by air­ing old sit­coms and clas­sic films, at one point even host­ing “Academy Award Theatre” him­self.

Turner was­n’t in­ter­ested in news yet. He de­cided to in­vest in sports in­stead, ac­quir­ing the rights to Atlanta Braves base­ball games. Viewers and ad­ver­tis­ers flocked to the chan­nel, and as Turner turned a profit, he started to think big­ger about TV.

In 1976 he beamed Channel 17’s sig­nal up to a satel­lite and it be­came ca­ble TV’s first su­per­sta­tion, reach­ing ca­ble sub­scribers across the coun­try.

Turner bought the Braves, and then the Atlanta Hawks bas­ket­ball team, partly to keep the long-term rights to the TV pro­gram­ming, and partly be­cause it was just plain fun.

As he built the Superstation WTBS, he set his sights even higher — a 24-hour news chan­nel.

Turner was harshly crit­i­cal of broad­cast TV and es­tab­lish­ment news judg­ments. “Part of the rea­son America had so many prob­lems, he be­lieved, was be­cause his fel­low Americans were so ill-in­formed,” for­mer CNN jour­nal­ist Lisa Napoli wrote in “Up All Night,” a book about the cre­ation of CNN. Turner rec­og­nized “there was no bet­ter place to pro­mote a va­ri­ety of opin­ions than on allmighty tele­vi­sion. With a news chan­nel, he could quite pos­si­bly help save the world.”

A lot of peo­ple thought Turner’s idea was crazy. But he saw a huge open­ing in the mar­ket­place.

“I worked un­til 7 o’­clock, and when I got home the news was over,” he once said, ref­er­enc­ing the 6:30 evening news­casts on the big net­works. “So I missed tele­vi­sion news com­pletely. And I fig­ured there were lots of peo­ple like me.”

Turner wanted to dra­mat­i­cally widen the aper­ture of tele­vi­sion news, en­vi­sion­ing shows about busi­ness, health, sports and other sub­ject mat­ter. He ad­mit­ted he knew “diddley-squat” about the news busi­ness, but he re­cruited the right peo­ple who did, like Reese Schonfeld, CNN’s found­ing pres­i­dent.

On June 1, 1980, CNN, the first 24-hour news chan­nel, went live and has been on the air ever since.

Turner quickly ex­panded, adding a sec­ond 24-hour news net­work CNN2 (later re­named Headline News, then HLN) in 1982 and CNN International, which broad­cast around the world, in 1985. He later added non-news ca­ble chan­nels in­clud­ing Turner Network Television (TNT), Turner Classic Movies (TCM) and the Cartoon Network.

In the mid-1980s, he ac­quired MGM’s li­brary of more than 4,000 old films and stirred up con­tro­versy in the film com­mu­nity for col­oriz­ing many black-and-white movies, in­clud­ing “Casablanca.”

Out of all his net­works, CNN was al­ways his “baby,” but the net­work’s early years were marked by tech­ni­cal sna­fus dur­ing its long stretches of live broad­cast­ing. Some crit­ics dubbed it “Chicken Noodle News.”

Yet, Turner and his deputies knew they were cre­at­ing some­thing rev­o­lu­tion­ary.

“I lived for 20 years in my of­fice,” Turner said. His of­fice was in­side CNN’s broad­cast build­ing in Atlanta. “I lived on a couch in my of­fice the first 10 years.”

Longtime em­ploy­ees re­call Turner saun­ter­ing into the news­room wear­ing a bathrobe.

“He was one of us,” for­mer CNN pres­i­dent Tom Johnson re­called. “He would be in his house­coat down hav­ing break­fast in the Hard News Café (the com­pa­ny’s cafe­te­ria).”

When the Persian Gulf War broke out in 1990, the im­por­tance of a 24-hour news chan­nel be­came clear. It was the first time a war was broad­cast live — and it was only on CNN.

“What Ted made hap­pen was just as im­por­tant as the Internet rev­o­lu­tion,” said for­mer Turner Broadcasting CEO Terry McGuirk.

Turner was hailed as a vi­sion­ary and earned TIME Magazine’s “Man of the Year” in 1991.

In 1996, Turner sold his net­works to Time Warner for nearly $7.5 bil­lion. He stayed on as a vice-chair­man of Time Warner, head­ing up the com­pa­ny’s ca­ble TV net­works.

Robert Edward Turner III was born in Cincinnati, Ohio, on November 19, 1938. At the age of 4, shortly af­ter his sis­ter’s birth, his par­ents sent young Ted to a board­ing school, which he did­n’t like.

“I wanted to be home,” he said.

Turner had a dif­fi­cult re­la­tion­ship with his fa­ther, who had a weak­ness for al­co­hol and dis­ci­plined his son with a leather strap or a wire coat hanger.

“It was­n’t dan­ger­ous or any­thing like that,” Turner once re­called. “It just hurt like the devil.”

The fam­ily later moved to Savannah, Georgia, and his sis­ter Mary Jean con­tracted a rare form of lu­pus when she was 12. The ill­ness left her with brain dam­age and in se­vere pain for years un­til her death.

“She was sick for five years be­fore she passed away. And it just seemed so un­fair, be­cause she had­n’t done any­thing wrong,” Turner said. “What had she done wrong? And I could­n’t get any an­swers. Christianity could­n’t give me any an­swers to that. So my faith got shaken some­what.”

Turner was sent to sev­eral strict Southern mil­i­tary schools and his fa­ther had hopes of him get­ting ac­cepted to Harvard. He at­tended an­other Ivy League school — Brown University — but his fa­ther cut off his tu­ition be­cause he dis­ap­proved of his ma­jor, as he made clear in a let­ter he wrote to his son.

“My dear son, I am ap­palled, even hor­ri­fied, that you have adopted Classics as a ma­jor,” the el­der Turner wrote. “I am a prac­ti­cal man, and for the life of me I can­not pos­si­bly un­der­stand why you should wish to speak Greek. With whom will you com­mu­ni­cate in Greek?

“I think you are rapidly be­com­ing a jack­ass, and the sooner you get out of that filthy at­mos­phere, the bet­ter it will suit me.”

Before long, the money ran out and he dropped out, re­turn­ing to Georgia to work for his fa­ther’s bill­board com­pany in Macon.

Turner was just 24 when his fa­ther shot him­self and died in the up­stairs bath­room at the fam­i­ly’s home near Savannah. It was March 5, 1963, and the el­der Turner was un­der the in­flu­ence of al­co­hol and pills, bat­tling de­pres­sion and wor­ried he had overex­tended him­self with a $4 mil­lion pur­chase that ex­panded his com­pany, Turner Outdoor Advertising, into the South’s largest bill­board com­pany.

“He went against every­thing he taught me: ‘Be coura­geous and hang in there,’” Turner said.

At the peak of his ca­reer, Ted Turner — twice di­vorced with five grown chil­dren — be­gan dat­ing ac­tress Jane Fonda in 1989. The two would marry in 1991 and be­come one of the na­tion’s most sto­ried cou­ples.

“At first they did­n’t get along at all,” re­called friend and for­mer President Jimmy Carter. “In fact, they did­n’t like each other. I heard this from both of them. It was months later be­fore they de­cided to try again. And they evolved into one of the nicest ro­mances that I’ve ever known about.”

Ted and Jane stayed to­gether for 10 years and, when they split, his anger at her con­ver­sion to Christianity was blamed, but the truth was more nu­anced. She sim­ply could no longer take a back seat to his larger-than-life per­son­al­ity or sus­tain his need for her con­stant com­pan­ion­ship as they shut­tled be­tween his 28 prop­er­ties. She was push­ing 60 and no longer in­ter­ested in liv­ing out of a suit­case.

“I would never love any­one like I love him,” she said. “But I just could­n’t keep mov­ing in his world, along the sur­face for the rest of my life. I knew that I would get to the end of my life and re­gret not do­ing the things that I also needed to do for me.”

He was dev­as­tated when she left him and, as his mar­riage ended, Turner’s me­dia em­pire be­gan slip­ping away.

Time Warner had agreed to be pur­chased by Internet provider AOL in 2000 with the hopes that the merger would help the legacy me­dia com­pany sur­vive and pros­per dur­ing the dot-com boom.

But the Internet bub­ble burst in 2001 and the fol­low­ing year the new AOL-Time Warner sus­tained a record $99 bil­lion loss, re­sult­ing in count­less job cuts. It soon be­came known as the biggest merg­ers and ac­qui­si­tions fail­ure in cor­po­rate his­tory.

Turner re­signed as AOL Time Warner’s vice-chair­man in 2003, and three years later an­nounced he would not seek re­elec­tion to its board of di­rec­tors.

He lost con­trol of Turner Broadcasting, CNN, the Atlanta Braves, the Hawks — and his for­tune, con­sist­ing mostly of com­pany stock, was he­m­or­rhag­ing — more than $7 bil­lion in three years.

“I lost Jane. I lost my job here. I lost my for­tune, most of it. Got a bil­lion or two left. You can get by on that if you econ­o­mize,” he told CNN’s Piers Morgan in May 2012. He said he was “brokenhearted.” He tried to win her back, but it was ob­vi­ous the re­la­tion­ship was be­yond re­pair. “We were so far apart philo­soph­i­cally, we could­n’t do it.”

Despite the breakup, Fonda and Turner al­ways main­tained a close friend­ship, speak­ing on the phone reg­u­larly and show­ing up at each oth­er’s char­ity events.

“Just be­cause peo­ple get di­vorced does­n’t mean they stop lov­ing each other,” she said. “It may be hard for two peo­ple to live to­gether, but I can’t ever for­get the rea­sons that made me fall in love with him.”

Turner ex­plained that he had “loved many peo­ple” but only been “in love” twice — once with Fonda and once with some­one he would­n’t name. Being “in love” im­plies per­ma­nence, he said — some­thing he had­n’t ex­pe­ri­enced in all of his re­la­tion­ships.

Turner al­ways had a phil­an­thropic streak, but it be­gan to move to the fore­front in 1997, the year af­ter he sold Turner Broadcasting to Time Warner. That’s when he pledged $1 bil­lion to the United Nations. Making good on that pledge took a while longer than he had an­tic­i­pated — he made his fi­nal pay­ment to the UN in 2015 — thanks to the beat­ing his for­tune took af­ter the 2001 merger with AOL.

When it was over, he was still a bil­lion­aire, but just barely.

Turner did­n’t do any­thing in a small way, in­clud­ing rein­vent­ing him­self. He was the sec­ond biggest landowner in North America, with 2 mil­lion acres spread over 28 prop­er­ties, in­clud­ing 19 ranches in Nebraska, Colorado, Kansas, Montana, New Mexico and South Dakota, as well as in Argentina. The first of his Ted’s Montana Grill restau­rants opened in 2002, and now there are more than 40 in 16 states. He man­aged to bring bi­son back from the brink of ex­tinc­tion; he had the world’s largest pri­vate bi­son herd, with ap­prox­i­mately 51,000 head.

His five chil­dren — Rhett Turner, Laura Turner Seydel, Jennie Turner Garlington, Teddy Turner and Beau Turner — serve on the board of the Turner Foundation. His other foun­da­tions in­clude his United Nations Foundation, Nuclear Threat Initiative, Captain Planet Foundation and the Turner Endangered Species Fund.

Half a cen­tury ago, his fa­ther’s sui­cide thrust a $1 mil­lion bill­board com­pany into his hands. He of­ten said that his fa­ther, who was 54 at the time he died, ran out of things to work to­ward. As a re­sult, Turner was dri­ven — re­lent­lessly mov­ing for­ward, never look­ing back.

Yet no mat­ter how suc­cess­ful he be­came, Turner was of­ten still try­ing to prove him­self.

Fonda re­called how she cried when Turner told her about his child­hood on their sec­ond date. They were dri­ving around his 60,000-acre ranch in Montana, and he was pass­ing the time, talk­ing as he drove. Tears ran down her face.

“He lit­er­ally could­n’t un­der­stand why I was cry­ing when he told me sto­ries about what his fa­ther did to him,” she said. “Children can’t blame their par­ents. ‘It’s al­ways my fault; it’s be­ing done for my own good. I must not be good enough.’”

“Given his child­hood,” Fonda said, “he should’ve be­come a dic­ta­tor. He should’ve be­come a not nice per­son. The mir­a­cle is that he be­came what he is. A man who will go to heaven, and there’ll be a lot of an­i­mals up there wel­com­ing him, an­i­mals that have been brought back from the edge of ex­tinc­tion be­cause of Ted. He’s turned out to be a good guy. And he says he’s not re­li­gious. But he, the whole time I was with him, every speech — and he likes to give speeches — he al­ways ends his speech with ‘God bless.’ And he’ll get into heaven. He’s a mir­a­cle.”

This story has been up­dated with ad­di­tional in­for­ma­tion.

CNN’s Elise Zeiger, Kimberly Arp Babbit, Liam Reilly and Dan Q. Tham con­tributed to this story.

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