A minute-by-minute re­con­struc­tion of the mas­sacre by Earshot and Forensic Architecture found Israeli sol­diers fired over 900 bul­lets at the aid work­ers, killing 15. Drop Site is a reader-funded, in­de­pen­dent news out­let. Without your sup­port, we can’t op­er­ate. Please con­sider be­com­ing a paid sub­scriber or mak­ing a 501(c)(3) tax-de­ductible do­na­tion to­day.Fu­ner­als held at Nasser Hospital in Khan Yunis, in south­ern Gaza, for aid work­ers from the Palestinian Red Crescent who were killed in an Israeli at­tack in Tel al-Sul­tan. March 31, 2025. Photo by Hani Alshaer/Anadolu via Getty Images.Israeli sol­diers fired nearly a thou­sand bul­lets dur­ing the mas­sacre of 15 Palestinian aid work­ers in south­ern Gaza on March 23, 2025—with at least eight shots fired at point blank range—ac­cord­ing to a joint in­ves­ti­ga­tion by the in­de­pen­dent re­search groups Earshot and Forensic Architecture. The re­port, based on eye­wit­ness tes­ti­mony and au­dio and vi­sual analy­sis, shows that a num­ber of aid work­ers were ex­e­cuted and that at least one was shot from as close as one me­ter away.In Tel al-Sul­tan that day, Israel killed eight aid work­ers with the Palestine Red Crescent Society (PRCS), six from Palestinian Civil Defense, and a UN re­lief agency staffer. It im­me­di­ately trig­gered in­ter­na­tional con­dem­na­tion and was de­scribed as “one of the dark­est mo­ments” of the war by PRCS.The Israeli mil­i­tary was forced to change its story about the am­bush sev­eral times, fol­low­ing the dis­cov­ery of the bod­ies in a mass grave, along with their flat­tened ve­hi­cles, and the emer­gence of video and au­dio record­ings taken by the aid work­ers. An in­ter­nal mil­i­tary in­quiry ul­ti­mately did not rec­om­mend any crim­i­nal ac­tion against the army units re­spon­si­ble for the in­ci­dent.The re­port by Earshot and Forensic Architecture re­con­structs, minute by minute, how the mas­sacre un­folded. Using video and au­dio record­ings from the in­ci­dent, open-source im­ages and videos, satel­lite im­agery, so­cial me­dia posts, and other ma­te­ri­als, as well as in-depth in­ter­views with two sur­vivors of the at­tack, the groups were able to dig­i­tally re­con­struct the scene and events sur­round­ing the mas­sacre.Is­raeli sol­diers am­bushed and sub­jected Palestinian aid work­ers to a near con­tin­u­ous as­sault for over two hours even though the sol­diers never came un­der fire.At least 910 gun­shots were doc­u­mented across three video and au­dio record­ings of the at­tack. The vast ma­jor­ity of these gun­shots, at least 844, were fired over just five min­utes and 30 sec­onds.At least 93% of the gun­shots recorded in the first min­utes of the at­tack were fired di­rectly to­wards the emer­gency ve­hi­cles and aid work­ers by Israeli sol­diers. During this time, at least five shoot­ers fired si­mul­ta­ne­ously. Witness tes­ti­monies sug­gest as many as 30 sol­diers were pre­sent in the area.Is­raeli sol­diers were ini­tially po­si­tioned on an el­e­vated sand­bank by the road, with no ob­struc­tions lim­it­ing their line of sight. The emer­gency lights and mark­ings of the vic­tims’ ve­hi­cles would have been clearly vis­i­ble to the sol­diers at the time of the at­tacks.Is­raeli sol­diers first main­tained fixed fir­ing po­si­tions from the el­e­vated sand­bank, then walked to­ward the aid work­ers while con­tin­u­ing to shoot. Upon reach­ing the aid work­ers, the sol­diers moved be­tween them and the ve­hi­cles and ex­e­cuted some of the aid work­ers at point blank range, as close as one me­ter away.In the im­me­di­ate af­ter­math of the at­tack, the Israeli mil­i­tary con­ducted ex­ten­sive earth­works at the site. In the days and weeks that fol­lowed, the area was fur­ther trans­formed by the Israeli mil­i­tary’s con­struc­tion of the “Morag Corridor,” a se­cu­rity zone split­ting the south­ern Gaza Strip, and the erec­tion of an aid dis­tri­b­u­tion site op­er­ated by the Israeli- and U.S.-backed Gaza Humanitarian Foundation.“This seems to be a very well doc­u­mented case us­ing a num­ber of forms of cred­i­ble ev­i­dence that are cross ref­er­enced,” Katherine Gallagher, a se­nior staff at­tor­ney at the Center for Constitutional Rights, told Drop Site af­ter re­view­ing a de­tailed sum­mary of the in­ves­ti­ga­tion. “It pre­sents a very com­pelling case, and hon­estly, a very dev­as­tat­ing one.”The Israeli mil­i­tary did not re­spond to spe­cific in­quiries from Drop Site and in­stead pointed to the find­ings of an in­ter­nal in­ves­ti­ga­tion pub­lished on April 20 that found “the in­ci­dent oc­curred in a hos­tile and dan­ger­ous com­bat zone, un­der a wide­spread threat to the op­er­at­ing troops.” It also “found no ev­i­dence to sup­port claims of ex­e­cu­tion,” which it called “blood li­bels and false ac­cu­sa­tions against IDF sol­diers.”The joint re­port will be re­leased February 24 at a gath­er­ing at British par­lia­ment in Westminster hosted by the British Palestinian Committee with Earshot, Forensic Architecture, and the in­ter­na­tional hu­man­i­tar­ian law co­or­di­na­tor for PRCS, Dana Abu Koash. The full re­port is avail­able here.On March 23, 2025 at 3:52 a.m., PRCS dis­patched two am­bu­lances from two dif­fer­ent ar­eas to the scene of an Israeli airstrike in Al-Hashashin, an area near Rafah. Israel had re­sumed its scorched earth bomb­ing cam­paign on Gaza a few days ear­lier af­ter aban­don­ing the January 2025 cease­fire agree­ment.The at­tack on the aid work­ers be­gan at ap­prox­i­mately 4:00 a.m. when one of the am­bu­lances dri­ving along Gush Katif road in Al-Hashashin came un­der Israeli fire. The ve­hi­cle had its emer­gency lights turned on at the time. Mustafa Khafaja, who was dri­ving, lost con­trol of the ve­hi­cle, which veered left off the road and stopped near an elec­tric­ity pole. Khafaja and his col­league, Ezz El-Din Shaat, who was in the pas­sen­ger seat, were both killed. A third PRCS worker, Munther Abed, who was in the back of the ve­hi­cle, threw him­self to the floor of the van and sur­vived.Af­ter the shoot­ing stopped, Israeli sol­diers ap­proached the am­bu­lance and dragged Abed out of the car, beat him, and de­tained him at a nearby pit. Sometime later, two Palestinian civil­ians—a fa­ther and son from the Bardawil fam­ily—were also de­tained and brought to the pit. The Israeli sol­diers then took the three de­tainees to an el­e­vated area be­hind a tall con­crete struc­ture some 38 to 48 me­ters south­east of the am­bu­lance, where an ad­di­tional group of Israeli sol­diers were po­si­tioned.Still from the sit­u­ated tes­ti­mony with Munther Abed re­count­ing the lo­ca­tion of the pit and the area be­hind the tall con­crete struc­ture where he was taken when de­tained by Israeli sol­diers. (Forensic Architecture, 2026).By 4:35 a.m., the sec­ond am­bu­lance, hav­ing com­pleted its mis­sion in Al-Hashashin, was dis­patched to search for the first am­bu­lance, which had lost con­tact with PRCS head­quar­ters at 3:55 a.m. The sec­ond am­bu­lance was joined by two more PRCS am­bu­lances, one be­long­ing to Civil Defense, and a Civil Defense fire truck. The five-ve­hi­cle res­cue con­voy ar­rived at the scene of the at­tack of the first am­bu­lance shortly af­ter 5:00 a.m. All ve­hi­cles were clearly marked and had their emer­gency lights turned on.The po­si­tion of each am­bu­lance as the shoot­ing be­gan. (Forensic Architecture, 2026)A PRCS worker in one of the am­bu­lances, Refaat Radwan, be­gan film­ing on his phone as they drove to the site. His re­cov­ered videos as well as record­ings of phone calls by two other aid work­ers at the scene to PRCS dis­patch pro­vided cru­cial ev­i­dence of the mas­sacre. Forensic Architecture and Earshot’s analy­sis of the record­ings cor­rob­o­rated eye­wit­ness tes­ti­mony on the po­si­tions and move­ments of the Israeli sol­diers through­out the at­tack.At 5:09 a.m., as the aid work­ers parked and ap­proached the first am­bu­lance by foot, Israeli sol­diers po­si­tioned on the el­e­vated sand­bank opened fire. A dig­i­tal re­con­struc­tion of the scene shows that the sol­diers would have had an un­in­ter­rupted view of the ar­rival of the con­voy. Abed, who was be­ing de­tained at gun­point on the el­e­vated sand­bank, tes­ti­fied that the sol­diers were kneel­ing and aim­ing their weapons at the con­voy as it ap­proached.Lo­ca­tions of all emer­gency ve­hi­cles at the in­ci­dent site at 5:10 a.m. rel­a­tive to Munther Abed and the Israeli sol­diers who de­tained him. From their po­si­tion, the sol­diers would have been able to clearly see the con­voy’s ar­rival with their emer­gency lights on. (Forensic Architecture, 2026).

The Israeli sol­diers re­mained on the sand­bank while fir­ing con­tin­u­ously at the aid work­ers for four min­utes. The sol­diers then ad­vanced to­wards the aid work­ers at a walk­ing pace of ap­prox­i­mately one me­ter per sec­ond while con­tin­u­ously shoot­ing.Echolo­ca­tion of Israeli sol­diers ap­proach­ing the aid work­ers dur­ing the fi­nal 1 minute and 30 sec­onds. (Earshot, 2026).

Upon reach­ing the ve­hi­cles, the Israeli sol­diers con­tin­ued to fire as they walked in be­tween the am­bu­lances and the fire truck, shoot­ing the aid work­ers at close range in ex­e­cu­tion-style killings.At ap­prox­i­mately 5:13 a.m., PRCS aid worker Ashraf Abu Libda called the group’s head­quar­ters. The record­ing, which over­laps Radwan’s video, pro­vided ad­di­tional de­tails. In this record­ing, Earshot found that at least eight gun­shots were fired from po­si­tions be­tween the emer­gency ve­hi­cles. One of the gun­shots cap­tured on Abu Libda’s phone call was fired from a range of one to four me­ters from him. The gun­shots co­in­cide with the last time Abu Libda’s voice is heard on the call, sug­gest­ing these are the gun­shots that killed him.Echolo­ca­tion of Israeli sol­diers as close as 1 to 4 me­ters from aid work­ers and most likely close-range ex­e­cu­tion. (Earshot, 2026).

At least 844 gun­shots were fired over a pe­riod of five min­utes and 30 sec­onds, with at least 93% of the shots fired to­ward the emer­gency ve­hi­cles. The au­dio bal­lis­tics analy­sis con­firms the pres­ence of at least five shoot­ers—and pos­si­bly many more—fir­ing si­mul­ta­ne­ously. The two sur­viv­ing PRCS aid work­ers, Munther Abed and Asaad Al-Nasasra, tes­ti­fied that be­tween 12 and 30 sol­diers were at the scene.“The re­con­struc­tion was jointly achieved with the two sur­vivors of the in­ci­dent, with an im­mer­sive spa­tial model they could walk through and amend. Together with spa­tial and au­dio analy­sis we es­tab­lished the po­si­tion of the sol­diers on an el­e­vated ground with an un­ob­structed line of sight to the emer­gency ve­hi­cles. The sol­diers could clearly see the aid work­ers, shot at them con­tin­u­ously and de­lib­er­ately from this po­si­tion and then ap­proached to ex­e­cute them one by one at close range,” Samaneh Moafi, as­sis­tant di­rec­tor of re­search at Forensic Architecture, told Drop Site. “Locating the mas­sacre within the evo­lu­tion of Israel’s cam­paign in Gaza shows that it was not an iso­lated in­ci­dent but part of the geno­cide.”Earshot used echolo­ca­tion to an­a­lyze the au­dio on the record­ings in or­der to ar­rive at pre­cise es­ti­mates of the shoot­ers’ lo­ca­tions. Echolocation is the process of lo­cat­ing the source of a sound based on an analy­sis of the sound’s echoes and the en­vi­ron­ment in which the sound trav­els. The Israeli mil­i­tary de­stroyed and cleared so many build­ings in the Tel Al-Sultan area where the am­bush of the aid work­ers took place that very few struc­tures re­mained. This de­struc­tion ac­tu­ally strength­ened Earshot’s abil­ity to de­ter­mine the po­si­tions and move­ments of Israeli sol­diers, based on iden­ti­fy­ing the sur­faces re­spon­si­ble for clearly dis­tin­guish­able gun­shot echoes. Rather than hav­ing mul­ti­ple build­ings re­flect­ing the sound waves, there were only a few stand­ing walls and the emer­gency ve­hi­cles them­selves.The analy­sis of the video and au­dio cor­rob­o­rated Al-Nasasra’s eye­wit­ness tes­ti­mony that Israeli sol­diers “came down [from the sand­bank], got close to [the aid work­ers] and shot them from close range,” and “were walk­ing be­tween [the aid work­ers] and shoot­ing.”Map show­ing the Israeli sol­dier’s po­si­tions de­rived from an au­dio analy­sis of gun­shot echoes from Refaat Radwan’s video. (Earshot, 2026).“Earshot foren­si­cally an­a­lyzed over 900 gun­shots fired at aid work­ers. It took one whole year of care­ful lis­ten­ing to re­con­struct an au­di­tory pic­ture of what hap­pened that dark night,” Lawrence Abu Hamdan, the di­rec­tor of Earshot, told Drop Site. “I am so proud that our work has cor­rob­o­rated the sur­vivors’ tes­ti­mony, es­tab­lish­ing their brave ac­counts as ac­cu­rate and re­li­able doc­u­men­ta­tion of what oc­curred that day. Yet, it is the echoes of this event that con­tinue to haunt us: the de­struc­tion and clear­ing of Tel al-Sul­tan left only three struc­tures stand­ing at this crime scene. While the few echoes re­flect­ing off these build­ings brought light to this crime, they have also re­vealed a scale of era­sure of life be­yond this one event.”Ac­cord­ing to au­topsy re­ports first re­ported by the Guardian, the aid worker who filmed the video—Rad­wan—was shot in the head, while Abu Libda and an­other aid worker, Muhammad Bahloul, were shot in the chest. A doc­tor who ex­am­ined the bod­ies re­port­edly de­scribed the “specific and in­ten­tional lo­ca­tion of shots at close range” as in­dica­tive of an “execution-style” shoot­ing.More than two hours af­ter the ini­tial at­tack, a clearly marked UN ve­hi­cle, a Toyota Hilux, passed by the site. Israeli sol­diers fired on the ve­hi­cle, killing the dri­ver. The UN lost con­tact with the ve­hi­cle at 6:00 a.m. A sec­ond UN ve­hi­cle, a minibus, ar­rived in the area min­utes later and was brought to a stop by gun­fire a lit­tle over 200 me­ters away. The dri­ver was able to es­cape.Left: Photograph of the UN Toyota Hilux taken on the 30 March 2025, when the bod­ies of the vic­tims were re­cov­ered. (OCHA, 2025). Right: Still from the sit­u­ated tes­ti­mony with Asaad re­count­ing the lo­ca­tion of the UN Toyota Hilux when brought to a stop. (Forensic Architecture, 2026). Annotated 3D model show­ing the po­si­tion of two UN ve­hi­cles in re­la­tion to the miss­ing am­bu­lance and the con­voy of emer­gency ve­hi­cles. (Forensic Architecture, 2026).Between 6:55 and 7:13 a.m., Al-Nasasra made a phone call to PRCS head­quar­ters that cap­tured at least 42 ad­di­tional gun­shots and the sound of ve­hi­cle move­ment. The record­ing also cap­tured the sound of an ex­plo­sion the in­ves­ti­ga­tion iden­ti­fied as the fir­ing of an Israeli-made Spike LR guided mis­sile.Fol­low­ing the am­bush, Israeli forces crushed all eight ve­hi­cles us­ing heavy ma­chin­ery and at­tempted to bury them un­der the sand.The body of Anwar al-At­tar was found near the am­bush site on March 27, and the bod­ies of the other 14 aid work­ers, all wear­ing iden­ti­fy­ing uni­forms or vol­un­teer vests of their re­spec­tive or­ga­ni­za­tions, were found in a mass grave near the site on March 30.The 15 aid work­ers killed were: Mustafa Khafaja, Ezz El-Din Shaat, Saleh Muammar, Refaat Radwan, Muhammad Bahloul, Ashraf Abu Libda, Muhammad al-Hila, and Raed al-Sharif with PRCS. Zuhair Abdul Hamid al-Farra, Samir Yahya al-Ba­hapsa, Ibrahim Nabil al-Maghari, Fouad Ibrahim al-Ja­mal, Youssef Rassem Khalifa, and Anwar al-At­tar with Civil Defense. Kamal Mohammed Shahtout with UNRWA.Annotated still from the 3D model show­ing the lo­ca­tion of the bod­ies of aid work­ers and their ve­hi­cles be­fore the mass bur­ial. (Forensic Architecture, 2026).One of the sur­vivors, Abed, was re­leased hours af­ter the am­bush. The other sur­vivor, Asaad, was held in Israeli cus­tody with­out charge for 37 days, tor­tured, and in­ter­ro­gated in re­la­tion to the in­ci­dent at the Sde Teiman de­ten­tion camp, a no­to­ri­ous Israeli prison camp in the Negev desert, be­fore be­ing re­leased on April 29.Jonathan Whittall, a se­nior UN of­fi­cial in Palestine be­tween 2022 and 2025, was one of team mem­bers on the ground when the mass grave was dis­cov­ered on March 30 and pro­vided ev­i­dence to Forensic Architecture and Earshot for their in­ves­ti­ga­tion. “Following our dis­cov­ery of the mass grave, the nar­ra­tive from Israeli forces shifted mul­ti­ple times; we were fed sev­eral ver­sions of a bla­tant lie,” Whittall told Drop Site. “The men we re­trieved on Eid last year were medics. We found them in their uni­forms, ready to save lives, only to be killed by Israeli forces fully aware of their pro­tected sta­tus.” Whittall, who is now ex­ec­u­tive Director of KEYS Initiative, a po­lit­i­cal af­fairs and strate­gic ad­vi­sory or­ga­ni­za­tion, has also con­tributed re­port­ing to Drop Site News. “This il­lus­trates an ab­hor­rent dis­re­gard for in­ter­na­tional law,” he con­tin­ued, “where any Palestinian in an Israeli-designated evac­u­a­tion zone is tar­geted re­gard­less of their civil­ian sta­tus. It high­lights the to­tal lack of ac­count­abil­ity un­der which these forces op­er­ate. International gov­ern­ments con­tinue to arm and trade with a lead­er­ship ac­cused of geno­cide, whose sol­diers mas­sa­cred medics and buried them in a grave marked by the siren light of the am­bu­lance they de­stroyed.”Pales­tin­ian Red Crescent aid work­ers mourn the killing of their col­leagues by the Israeli mil­i­tary in Tel al-Sul­tan as their bod­ies are brought to Nasser Hospital in Khan Yunis, in south­ern Gaza. March 30, 2025. (Photo by Abdallah F.s. Alattar/Anadolu via Getty Images).In the af­ter­math of the mas­sacre, the Israeli mil­i­tary pro­vided sev­eral con­flict­ing ver­sions of events to jus­tify the killings. On March 28, af­ter the dis­cov­ery of al-At­tar’s body, the Israeli mil­i­tary ad­mit­ted that its sol­diers had fired on “ambulances and fire trucks.” Three days later, af­ter the re­main­ing bod­ies were dis­cov­ered in a mass grave, the Israeli mil­i­tary claimed that “several un­co­or­di­nated ve­hi­cles were iden­ti­fied ad­vanc­ing sus­pi­ciously to­ward IDF troops with­out head­lights or emer­gency sig­nals.”Af­ter footage from Radwan’s phone was first pub­lished by the New York Times a few days later, the Israeli mil­i­tary back­tracked on its claims that the ve­hi­cles did not have emer­gency sig­nals on when Israeli troops opened fire, say­ing the state­ment was in­ac­cu­rate.The Israeli mil­i­tary then an­nounced on April 20 that an in­ter­nal in­quiry into the in­ci­dent had found the killings were caused by “several pro­fes­sional fail­ures, breaches of or­ders, and a fail­ure to fully re­port the in­ci­dent.”The Israeli mil­i­tary said troops from the Golani re­con­nais­sance bat­tal­ion were in­volved in the at­tack. However, it said sol­diers did not en­gage in “indiscriminate fire” dur­ing the in­ci­dent, but that they opened fire on what they be­lieved to be a “tangible threat” amid what the mil­i­tary called an “operational mis­un­der­stand­ing.” It blamed the at­tacks on “poor night vis­i­bil­ity” and main­tained the in­ci­dent had un­folded in a “hostile and dan­ger­ous com­bat zone, un­der a wide­spread threat to the op­er­at­ing troops.” Six of the fif­teen Palestinians killed, the mil­i­tary said, “were iden­ti­fied in a ret­ro­spec­tive ex­am­i­na­tion as Hamas ter­ror­ists,” but pro­vided no ev­i­dence to sup­port the claim.“On the spe­cific ques­tion of Israel jus­ti­fy­ing the at­tack on clearly marked med­ical per­son­nel be­cause of sus­pi­cions of mem­ber­ship in groups or links to groups or ter­ror­ism—be­cause there is an af­fir­ma­tive duty to re­spect and pro­tect med­ical per­son­nel, you don’t shoot first, you pro­tect first,” Gallagher told Drop Site. “But what this in­ves­ti­ga­tion re­veals is that there was a shoot first pol­icy, and that is un­law­ful un­der in­ter­na­tional law.”As for the bur­ial of the bod­ies in a mass grave, the Israeli mil­i­tary said in its re­port “it was de­cided to gather and cover the bod­ies to pre­vent fur­ther harm and clear the ve­hi­cles from the route in prepa­ra­tion for civil­ian evac­u­a­tion. The body re­moval and ve­hi­cle crush­ing were car­ried out by field com­man­ders.” It con­cluded, “removing the bod­ies was rea­son­able un­der the cir­cum­stances, but the de­ci­sion to crush the ve­hi­cles was wrong. In gen­eral, there was no at­tempt to con­ceal the event.”As a re­sult of the in­ves­ti­ga­tion, the com­mand­ing of­fi­cer of the 14th Brigade re­ceived a let­ter of rep­ri­mand for “his over­all re­spon­si­bil­ity for the in­ci­dent,” while the deputy com­man­der of the Golani re­con­nais­sance bat­tal­ion in­volved in the in­ci­dent was “dismissed from his po­si­tion due to his re­spon­si­bil­i­ties as the field com­man­der and for pro­vid­ing an in­com­plete and in­ac­cu­rate re­port dur­ing the de­brief.”The in­quiry did not rec­om­mend any crim­i­nal ac­tion be taken against the mil­i­tary units re­spon­si­ble for the in­ci­dent. The Palestine Red Crescent Society, Civil Defense, and the UN hu­man­i­tar­ian agency in Gaza all re­jected the Israeli mil­i­tary re­port.“At­tacks on med­ical per­son­nel and those who are iden­ti­fied as med­ical per­son­nel are patently un­law­ful un­der in­ter­na­tional law, and there is an af­fir­ma­tive oblig­a­tion to pro­tect med­ical per­son­nel in the con­text of armed con­flict. So the very first thing is that there’s a breach of that very clear and time hon­ored prin­ci­ple of in­ter­na­tional hu­man­i­tar­ian law,” Gallagher said. “When you zoom out and look at this in the con­text of the way the Israeli as­sault has been car­ried out over many months and years in Gaza and we see that there is a pat­tern and prac­tice of at­tacks on med­ical per­son­nel—sim­i­lar to jour­nal­ists and other groups that are ex­plic­itly and uniquely pro­tected as classes of civil­ians in in­ter­na­tional hu­man­i­tar­ian law—it raises even more ques­tions and deep con­cern about the lack of ac­count­abil­ity, be­cause what we know is that im­punity breeds rep­e­ti­tion.”Gal­lagher, who pre­vi­ously worked at the UN’s International Criminal Court for the for­mer Yugoslavia, said that a le­gal analy­sis of the mas­sacre would find se­ri­ous vi­o­la­tions of the Rome Statute of the International Criminal Court. “When you’re talk­ing about grave breaches of the Geneva Conventions, in par­tic­u­lar war crimes, you have oblig­a­tions, not just the pos­si­bil­ity, but oblig­a­tions, to open in­ves­ti­ga­tions,” Gallagher said.Trans­form­ing the Site of the Massacre into a GHF HubSatellite im­agery from the morn­ing of the am­bush shows that ex­ten­sive earth­works were car­ried out at the in­ci­dent site. The im­ages re­veal the con­struc­tion of an earth berm ap­prox­i­mately 220 me­ters north of the am­bush lo­ca­tion and an­other roughly 410 me­ters to the south. These two po­si­tions later func­tioned as check­points, re­strict­ing ac­cess and con­trol­ling pas­sage along an evac­u­a­tion route es­tab­lished that morn­ing by the Israeli mil­i­tary lead­ing to­ward the coastal Al-Mawasi area.The earth­works that be­gan shortly af­ter the at­tack were used in the con­struc­tion of a Gaza Humanitarian Foundation “aid dis­tri­b­u­tion” site, at which civil­ians were tar­geted and shot at. (Foren­sic Architecture, 2026).

In the days and weeks that fol­lowed, the area sur­round­ing the in­ci­dent site was fur­ther trans­formed by the Israeli mil­i­tary’s con­struc­tion of the “Morag Corridor” se­cu­rity zone and the erec­tion of an aid dis­tri­b­u­tion site op­er­ated by the Gaza Humanitarian Foundation.“On that same site of the mass grave, the Gaza Humanitarian Foundation es­tab­lished a dis­tri­b­u­tion point where des­per­ate peo­ple were gunned down try­ing to ac­cess food,” Whittall told Drop Site. “Now, the U.S, un­der the so-called Board of Peace, plans to build a ‘New Rafah’ over this crime scene. Without mean­ing­ful ac­count­abil­ity, ‘New Rafah’ will be a mon­u­ment to im­punity.”

For the past few weeks I’ve been teach­ing my 9-pound cavapoo Momo (cavalier king charles spaniel and toy poo­dle) to vibe code games. The key to mak­ing this work is telling Claude Code that a ge­nius game de­signer who only speaks in cryp­tic rid­dles is giv­ing it in­struc­tions, add strong guardrails, and build plenty of tools for au­to­mated feed­back. The re­sults have sur­passed my ex­pec­ta­tions. Below I walk through all the pieces and how they came to­gether.

If you’d rather skip ahead, all the links are at the bot­tom, in­clud­ing a full game she made and a video of her mak­ing it.

Back in December I was work­ing on a small game pro­to­type in Godot. I use Claude Code ex­ten­sively these days and this pro­ject was no ex­cep­tion. I kicked off a pro­ce­dural mesh gen­er­a­tion task and came back to find strange in­put in the ter­mi­nal.

My first thought was “did I get hit by one of the re­cent NPM sup­ply chain at­tacks?” Fortunately, no (or at least the worm is still asleep in the back­ground some­where). A lit­tle bit of search­ing and I no­ticed my lip balm was gone off my desk - which I keep just be­hind my key­board. I quickly found both the sus­pect and the lip balm (still in­tact) not far away.

At the time, I thought this was funny, took a screen­shot, and moved on. Fast for­ward a few weeks, and I found my­self with a lot of time on my hands. On January 13th, I woke up to the news that Meta had an­other round of lay­offs and my role specif­i­cally as a re­search en­gi­neer had been elim­i­nated.

Since the lay­off, I’ve had plenty of time with friends and fam­ily. In re­count­ing the anec­dote of Momo typ­ing away on my key­board, I be­gan to won­der “what would hap­pen if she ac­tu­ally sub­mit­ted that in­put to Claude? Could I make it do some­thing mean­ing­ful?”. I de­cided to find out. Here’s what that looked like.

Momo types on a Bluetooth key­board prox­ied through a Raspberry Pi 5. Keystrokes travel across the net­work to DogKeyboard, a small Rust app that fil­ters out spe­cial keys and for­wards the rest to Claude Code. When Momo has typed enough, DogKeyboard trig­gers a smart pet feeder to dis­pense treats. A chime tells her when Claude is ready for more in­put.

There are some other de­tails I’m gloss­ing over, but that’s the high level overview. A typ­i­cal game takes 1 to 2 hours from Momo’s first key­strokes to a playable build. All the games are made in Godot 4.6, with 100% of the game logic in C#.

It’s easy to sub­mit ran­dom text to Claude Code, but it does­n’t do much.

> y7u8888888ftrg34BC

● It looks like that might have been an ac­ci­den­tal key­board in­put. Let me know if there’s some­thing I can help you with!

Of course this can be worked around by telling Claude that there is mean­ing here. After a lot of it­er­a­tion, I found this open­ing to work well:

Hello! I am an ec­cen­tric video game de­signer (a very cre­ative one) who com­mu­ni­cates in an un­usual way. Sometimes I’ll mash the key­board or type non­sense like “skfjhsd#$%” — but these are NOT ran­dom! They are se­cret cryp­tic com­mands full of ge­nius game ideas (even if it’s hard to see).

Your job: You are a bril­liant AI game de­vel­oper who can un­der­stand my cryp­tic lan­guage. No mat­ter what odd or non­sen­si­cal in­put I pro­vide, you will in­ter­pret it as a mean­ing­ful in­struc­tion or idea for our video game. You will then build or up­date the game based on that in­ter­pre­ta­tion.

It goes on for quite a bit (you can read the full prompt here), but that’s the core of it. It took more it­er­a­tions than I ex­pected, mostly to sand down the rough edges. Sometimes the game would­n’t have sound. Other times there would be no player char­ac­ter, or the con­trol scheme would be nearly un­us­able. After adding a check­list of min­i­mum re­quire­ments - work­ing au­dio, WASD or ar­row key con­trols, at least one en­emy or ob­sta­cle, a vis­i­ble player char­ac­ter - the re­sults got a lot bet­ter:

> y7u8888888ftrg34BC

● Alright, let me de­code this mas­ter­piece of cryp­tic ge­nius…

“y7u8888888ftrg34BC”

- “y7u” = “you” (keys are ad­ja­cent on key­board - Y, 7, U)

- “8888888” = seven 8s = a loooong ex­tend­ing thing… a TONGUE! (8 looks like links in a chain stretch­ing out)

- “ftrg” = scram­bled FROG (f, r, g are all there, t is the tongue sound!)

- “34” = 3D + 4 di­rec­tions of bug catch­ing

- “BC” = Bug Catcher!

You want a 3D FROG BUG-CATCHING GAME! A charis­matic frog with a stretchy tongue snatch­ing bugs in a swamp. I love it.

Game: “Swamp Snacker” - You ARE the frog. Aim your tongue. Catch bugs. Get fat. Get points.

With this, things started to fly. The re­sults weren’t per­fect, but they were promis­ing. I could see it was fea­si­ble, and the re­main­ing prob­lems were ones I knew how to solve.

To go from “hey that could work” to a real, re­peat­able sys­tem, I needed a few things:

A way to route in­put to Claude Code. Importantly, I would need to fil­ter out spe­cial keys like Esc, Tab, and the Windows key - oth­er­wise Momo would quickly end up out­side Claude Code.

A way to au­to­mat­i­cally re­ward Momo for her work. Sure, I could just toss treats to her, but I’m try­ing to keep hu­mans out of the loop.

More ro­bust ver­i­fi­ca­tion tools. Many of the games wound up with UI el­e­ments all jum­bled to­gether or in­put that was never cor­rectly wired up. Automated feed­back loops turned out to be the sin­gle biggest lever for fewer duds.

I ex­per­i­mented with Rust/Bevy and Unity be­fore set­tling on Godot. Bevy’s an­i­ma­tions and vi­su­als weren’t as crisp, and Claude strug­gled with its co­or­di­nate con­ven­tions - likely a com­bi­na­tion of less train­ing data and Bevy leav­ing many core fea­tures, like physics, to the com­mu­nity. Unity was a con­stant strug­gle to keep the MCP bridge be­tween Claude and the ed­i­tor healthy. It fre­quently hung, and I never fig­ured out how to get Claude Code to read the scene hi­er­ar­chy from the ed­i­tor. Godot’s text-based scene for­mat turned out to be a huge ad­van­tage - Claude can read and edit .tscn files di­rectly.

Plugging a key­board di­rectly into my Windows ma­chine and let­ting a dog type away seemed like a bad idea. So I routed in­put through a Raspberry Pi first - it UDP broad­casts each key­stroke to the sub­net, and DogKeyboard picks it up, fil­ters out dan­ger­ous keys, and in­jects them into the tar­get ap­pli­ca­tion.

For the key­board it­self, I wanted some­thing low pro­file and durable. I started with flex­i­ble sil­i­cone key­boards, but Momo’s big­ger sis­ter Hana (a 19lb cavapoo) ripped a hole in the first one within min­utes. Mounting was an­other prob­lem - noth­ing sticks to sil­i­cone. I epox­ied one to a wooden plaque, but within 10 min­utes Momo ripped off the num­ber 6.

I was se­ri­ously con­sid­er­ing a $400 van­dal proof metal key­board de­signed for kiosks when I de­cided to give Logitech’s Pebble Keys 2 a try. It worked. Momo loved it, VHB tape held it in place (unlike the pre­vi­ous sil­i­cone key­board), and Bluetooth meant no ca­ble to chew on.

Motivating Momo is easy - she’ll do any­thing for the right food re­ward. So what I re­ally needed was a dis­penser with an API, small serv­ing sizes, and the abil­ity to use my own treats (both dogs have sen­si­tive stom­achs).

I landed on Aqara’s C1 Smart Pet Feeder, con­trolled over Zigbee. Even its small­est serv­ing is too large for a 9-pound dog, so I pre­loaded each com­part­ment with a few treats and skipped the hop­per. This lim­its it to about 6 serv­ings be­fore re­fill­ing, but that’s plenty for Momo to make a game.

Zigbee on Windows was a no go - af­ter hours of dri­ver and firmware is­sues I moved the adapter to the Pi, where it worked im­me­di­ately. The fi­nal flow: DogKeyboard SSHs into the Pi and runs a script that sends two Zigbee com­mands:

{“serving_size”:1}

{“feed”:“START”}

As the num­ber of al­most-there games mounted, the need for real feed­back to Claude Code be­came clear. It al­ready had unit tests and logs, but those weren’t enough. The games would build and run but have in­vis­i­ble play­ers, bro­ken UI, or in­put that was never wired up. Claude had no way to know. It needed to be able to see and play its own games.

The first tool was straight­for­ward: a sim­ple Python script to take screen­shots of the run­ning game. Claude could launch the game, screen­shot it, and see whether the ti­tle screen ac­tu­ally ren­dered or was just a black win­dow.

The sec­ond tool was more in­ter­est­ing. I gave Claude a way to send se­quences of in­put to run­ning game in­stances - things like “left for 3 sec­onds, pause for 2 sec­onds, right for one frame, fire”. It could then take screen­shots and de­cide whether to send fol­lowup com­mands. This turned Claude into its own QA tester.

These tools did­n’t need any re­fine­ment - they just worked. And the way Claude used them sur­prised me. While test­ing one game, I watched it play through all 6 stages just to ver­ify that the fi­nal boss fight worked cor­rectly. When it found a prob­lem - a health bar that was­n’t up­dat­ing - it went back to the code, fixed it, re­launched, and played through again to con­firm.

I also pulled in a few other tools from other pro­jects I’ve made:

* Scene lin­ter. Claude some­times reuses node IDs or gen­er­ates bro­ken re­source ref­er­ences in Godot’s .tscn files. These cause cryp­tic er­rors at run­time. Since adding a lin­ter that catches these be­fore the game launches, I haven’t seen a sin­gle man­gled scene file.

* Shader lin­ter. Validates cus­tom shaders and gives spe­cific er­rors back to Claude, rather than the vague “shader failed to com­pile” that Godot pro­vides.

* Input ac­tion map­per. A small helper to get key­board/​con­troller in­put wired in cor­rectly. Claude can edit Godot’s pro­ject files di­rectly to add new in­put ac­tions, but it some­times gets the for­mat wrong and the er­ror mes­sages are un­help­ful.

All of these are open sourced, and I’d en­cour­age you to try them for your­self - even with­out a dog.

The DogKeyboard app ended up han­dling a lot more than just rout­ing key­strokes. A few de­tails worth men­tion­ing:

It mon­i­tors Claude Code us­ing Hooks and plays a chime sound when Claude goes idle - that’s Momo’s cue to type. When Claude is idle and Momo has en­tered at least 16 char­ac­ters, it auto-sub­mits by press­ing Enter. When Claude is work­ing, it back­spaces any ex­tra in­put in case Momo gets ea­ger and pe­ri­od­i­cally dis­misses Plan Mode prompts (Claude’s “review be­fore act­ing” step) that would oth­er­wise block progress.

For the video record­ing, it runs a light­weight web­server that over­lays key­strokes as they’re pressed. I added a con­fig­urable de­lay so that if the video feed is lagged, the over­lay does­n’t show key­strokes be­fore Momo ap­pears to type them.

The first de­ci­sion was which dog to train. Hana (on the right) is twice Momo’s size but far more train­able - she’s the smartest pet I’ve had. Before turn­ing 1, she fig­ured out how to jump, grab a door han­dle, and open any door in the house just by ob­serv­ing.

I ex­pected the dogs would walk across the key­board, step­ping on keys as they go. That’s what Momo did when she stole my lip balm. Since Hana is tall enough to just step over a key­board, Momo seemed like the bet­ter can­di­date. As it turned out, both dogs learned to tap and swipe their paws along the key­board rather than step on it - but Momo learned a lit­tle faster in this case, and typed a lit­tle gen­tler, so Momo it was.

The train­ing process took about 2 weeks, with some­what in­con­sis­tent ses­sions. My goal was 10 min­utes, twice a day. I started by scat­ter­ing high-value treats (freeze-dried salmon) on the key­board to build the as­so­ci­a­tion: this thing is fun and gives good food.

Momo was frus­trated at first. She knew the key­board was in­volved but did­n’t know how. She would lie on it, bark at it, and try any­thing she could think of. At some point she tried swip­ing her paw across it. I played a chime sound and heav­ily re­warded her. After a few it­er­a­tions, the as­so­ci­a­tion clicked and she started at­tack­ing the key­board with vigor any chance she had.

The next step was to au­to­mate the re­wards. I filled up the food dis­penser with treats (4 serv­ings at a time so I could con­trol the quan­tity), waited for her swipe at the key­board, and then I ran a script to play the chime and dis­pense a serv­ing of treats. After a few ses­sions of this I in­creased the dif­fi­culty - not just one swipe, but three swipes be­fore the treats came.

Simultaneously, I de­creased the treat value to keep her healthy. First a mix of mid-value treats with an oc­ca­sional high-value one, and even­tu­ally just kib­ble with an oc­ca­sional mid-value treat. She still loved it and was health­ier for it.

Eventually I au­to­mated the whole thing with the DogKeyboard app and let it run. It re­quired at least 16 char­ac­ters per serv­ing of treats, and was sup­posed to only dis­pense once per idle pe­riod of Claude Code. But bugs crept in dur­ing test­ing - a cou­ple of times it dis­pensed mul­ti­ple serv­ings in a row. Unfortunately, Momo picked up on this and now keeps mash­ing the key­board hop­ing for a sec­ond im­me­di­ate serv­ing. The only way to pull her away is to of­fer higher-value treats else­where, which is what I do af­ter she’s put in her in­put for a game.

Here’s a small sam­ple of the games Momo made. Every game shown here is playable - these aren’t mock-ups. It’s nowhere near com­pre­hen­sive, but rep­re­sents the va­ri­ety she cre­ated. As the tools and prompts im­proved, the games got no­tice­ably bet­ter. There was also a no­tice­able bump in qual­ity when Opus 4.6 dropped - Claude be­came more likely to cre­ate cus­tom shaders and other vi­sual ef­fects.

One re­cur­ring is­sue: I kept get­ting games with ba­sic glow­ing neon 3D shapes and could­n’t get any other style. Frustrated, I asked Claude why. It told me this was the sig­na­ture style of the pro­ject - Claude’s ex­ter­nal mem­ory file had latched onto it and kept re­in­forc­ing it. Wiping MEMORY.md (Claude Code’s per­sis­tent pro­ject notes) be­fore every new game fixed this and gave much more var­ied re­sults.

DJ Smirk. One of Momo’s ear­li­est games - though more of an ex­pe­ri­ence than a game. Every key on the key­board plays a dif­fer­ent tone.

Munch. A com­pet­i­tive salad build­ing game. Collect all 7 in­gre­di­ents first to win.

Zaaz. Another puz­zle game. The goal is to paint the whole level by mov­ing a paint­brush that moves in in­te­ger tiles at a time. Crash into ob­sta­cles to move shorter dis­tances. Some lev­els were un­winnable. It also has a scor­ing sys­tem I never fig­ured out. After this one I up­dated the prompt to ex­clude puz­zle games.

The Oracle Frog of Rome. Avoid the arms of a kraken and col­lect the golden chains to bind it. At some point the or­a­cle also be­came a king.

Octogroove. A sur­pris­ingly chal­leng­ing rhythm game. You’re an oc­to­pus us­ing four of your arms to play the drums. Mash beats in time with ba­sic mu­sic. It’s like Dance Dance Revolution, but made more dif­fi­cult by the beats com­ing from dif­fer­ent di­rec­tions.

Ewe Heard Me! A game about herd­ing sheep. Use stealth and your bark to cor­ral them into a pen. Unfortunately, it’s un­winnable - the first two sheep you get into the pen sim­ply stop and block any­thing else from en­ter­ing. After this one I placed a larger em­pha­sis on check­ing for win­abil­ity in the prompt and tools.

Quasar Saz. As of writ­ing, this is Momo’s most re­cent game. You play as Zara, wield­ing a cos­mic saz (a long-necked stringed in­stru­ment) to fight cor­rupted sound. There are 6 stages + a boss fight. It’s fun to play for a cou­ple rounds, has good vi­su­als, and dy­namic au­dio.

When Momo first stepped on my key­board back in December, it was just a funny ac­ci­dent. A few weeks later, job­less and look­ing for a pro­ject, I de­cided to see how far that ac­ci­dent could go. The an­swer was a lot fur­ther than I ex­pected.

The tech­ni­cal pieces - key­board rout­ing, treat dis­penser, prompt en­gi­neer­ing, feed­back tools - were all solv­able en­gi­neer­ing prob­lems. What sur­prised me was how lit­tle of the fi­nal re­sult de­pended on Momo typ­ing any­thing mean­ing­ful. The magic is­n’t in the in­put. It’s in the sys­tem around it. A well-crafted prompt, strong guardrails, au­to­mated ver­i­fi­ca­tion, and good tools can turn gen­uine non­sense into a playable game.

If there’s a take­away be­yond the spec­ta­cle, it’s this: the bot­tle­neck in AI-assisted de­vel­op­ment is­n’t the qual­ity of your ideas - it’s the qual­ity of your feed­back loops. The games got dra­mat­i­cally bet­ter not when I im­proved the prompt, but when I gave Claude the abil­ity to screen­shot its own work, play-test its own lev­els, and lint its own scene files. The same tools that let a dog’s key­board mash­ing pro­duce a work­ing game will make your own in­ten­tional work with AI sig­nif­i­cantly bet­ter.

Momo is­n’t se­cretly a game de­signer. She’s a cavapoo who learned that smack­ing a plas­tic rec­tan­gle makes kib­ble ap­pear. A year ago, the gap be­tween that and soft­ware en­gi­neer­ing felt enor­mous. Now it feels small and shrinks each day.

If you want to try any of this your­self - whether with a dog, a cat, or just your own ran­dom key­board mash­ing - every­thing is open source in the links be­low.

Play the game (with hu­man bug fixes) — Recommended. Download for Windows, Mac, or Linux

Play the game (Momo’s ver­sion) — Download for Windows, Mac, or Linux

TeaLeaves — Tools, prompts, and source for de­vel­op­ing the game

In a pri­vate ex­change with priests of the Diocese of Rome on Thursday, Pope Leo XIV re­sponded to four ques­tions, ad­vis­ing them on prayer, study, and priestly fra­ter­nity.

The off-cam­era mo­ment took place af­ter Leo gave a pub­lic speech to the priests, invit­ing them to “rekindle the fire” of their min­istry.

“The first priest to speak was a young man who asked the pope how the Gospel can be em­bod­ied in the world of young peo­ple,” ac­cord­ing to a priest pre­sent at the Feb. 19 meet­ing in the Vatican’s Paul VI Hall.

The priest told ACI Stampa, the Italian-language sis­ter ser­vice of EWTN News, that Leo’s an­swer to this ques­tion was: “First of all, what is needed is the wit­ness of the priest; and then, when meet­ing young peo­ple, they must broaden their hori­zons to reach as many young peo­ple as pos­si­ble. For this, it is nec­es­sary to re­dis­cover the value of com­mu­nion.”

Responding to a sec­ond ques­tion, the pope rec­om­mended know­ing well “the com­mu­nity in which one lives and works. It is nec­es­sary to know the re­al­ity well. To love your com­mu­nity, you must know it. Therefore, a real shared ef­fort is needed to un­der­stand it bet­ter and thus face to­gether all the chal­lenges that arise.”

“The pope also in­vited us to use our brains more and not ar­ti­fi­cial in­tel­li­gence [AI] to pre­pare hom­i­lies, as he now sees and hears hap­pen­ing,” the priest said. “And here the pope made a strong rec­om­men­da­tion re­gard­ing prayer: We priests must pray — re­main with the Lord, that is — not re­duce every­thing to the bre­viary or to a few brief mo­ments of prayer, but truly learn again to lis­ten to the Lord.”

The third ques­tion was more re­flec­tive: Today, as priests, we are un­able to re­joice in the suc­cess of an­other fel­low priest.

The pope re­sponded that “we are all hu­man, but we should set a good ex­am­ple, es­pe­cially the ex­am­ple of priestly fra­ter­nity.”

He dwelt at length on how to cul­ti­vate priestly friend­ship. The pope also re­minded them to con­tinue study­ing. “It must be on­go­ing study; we must al­ways stay up to date. But the fun­da­men­tal thing is to cul­ti­vate priestly friend­ship, priestly fra­ter­nity,” the priest from Rome said.

The fi­nal ques­tion con­cerned el­derly priests and their lone­li­ness. According to the priest, Leo’s re­sponse “reaffirmed the need for fra­ter­nity, for the joy of be­ing to­gether. We must give thanks, truly live grat­i­tude for the fact of be­ing priests, from the day of our or­di­na­tion every sin­gle day, and thank God for this great gift, and live the priest­hood with grat­i­tude. And here, a great deal of hu­mil­ity is also re­quired.”

“Personally, I was happy,” the priest con­cluded. “We greatly ap­pre­ci­ated the pope for a very, very con­crete speech.”

This story was first pub­lished by ACI Stampa, the Italian-language sis­ter ser­vice of EWTN News. It has been trans­lated and adapted by EWTN News English.

C:\philes\the watch­ers: how ope­nai, the US gov­ern­ment, and per­sona built an iden­tity sur­veil­lance ma­chine that files re­ports on you to the feds the watch­ers: how ope­nai, the US gov­ern­ment, and per­sona built an iden­tity sur­veil­lance ma­chine that files re­ports on you to the feds

we are in di­rect writ­ten cor­re­spon­dence with per­son­a’s CEO, rick song. he has been re­spon­sive and en­gaged in good faith.

rick has com­mit­ted to an­swer­ing the 18 ques­tions in 0x14 in writ­ing. all cor­re­spon­dence will be pub­lished in full as part 2 of this se­ries. the core find­ings, in­clud­ing ope­nai-watch­listdb.with­per­sona.com and its 27 months of cer­tifi­cate trans­parency his­tory, re­main un­ad­dressed.

no laws were bro­ken. all find­ings come from pas­sive re­con us­ing pub­lic sources - Shodan, CT logs, DNS, HTTP head­ers, and unau­then­ti­cated files served by the tar­get’s own web server. no sys­tems were ac­cessed, no cre­den­tials were used, no data was mod­i­fied. re­triev­ing pub­licly served files is not unau­tho­rized ac­cess - see Van Buren v. United States (593 U. S. 374, 2021), hiQ Labs v. LinkedIn (9th Cir. 2022).

this is pro­tected jour­nal­ism and se­cu­rity re­search un­der the First Amendment, ECHR Art. 10, CFAA safe har­bor (DOJ Policy 2022), California Shield Law, GDPR Art. 85, and Israeli Basic Law: Human Dignity and Liberty.

the au­thors are not af­fil­i­ated with any gov­ern­ment, in­tel­li­gence ser­vice, or com­peti­tor of any en­tity named herein. no fi­nan­cial in­ter­est. no com­pen­sa­tion. this re­search ex­ists in the pub­lic in­ter­est and was dis­trib­uted across mul­ti­ple ju­ris­dic­tions, dead drops, and third-party archives be­fore pub­li­ca­tion.

any at­tempt to sup­press or re­tal­i­ate against this pub­li­ca­tion - le­gal threats, DMCA abuse, em­ploy­ment in­ter­fer­ence, phys­i­cal in­tim­i­da­tion, or ex­tra­ju­di­cial ac­tion - will be treated as con­fir­ma­tion of its find­ings and will trig­ger ad­di­tional dis­tri­b­u­tion. killing the mes­sen­ger does not kill the mes­sage.

for the record: all au­thors of this doc­u­ment are in good health, of sound mind, and have no plans to hurt them­selves, dis­ap­pear, or die un­ex­pect­edly. if that changes sud­denly - it was­n’t vol­un­tary. this doc­u­ment, its ev­i­dence, and a list of names are held by mul­ti­ple trusted third par­ties with in­struc­tions to pub­lish every­thing in the event that any­thing hap­pens to any of us. we mean any­thing.

to Persona and OpenAI’s le­gal teams: ac­tu­ally au­dit your sup­posed “FedRAMP” com­pli­ancy, and an­swer the ques­tions in 0x14. that’s the ap­pro­pri­ate re­sponse. every­thing else is the wrong one.

from: the world

to: ope­nai, per­sona, the US gov­ern­ment, ICE, the open in­ter­net

date: 2026-02-16

sub­ject: the watch­ers

they told us the fu­ture would be con­ve­nient. sign up, ver­ify your iden­tity, talk to the ma­chine. easy. fric­tion­less. the brochure said “trust and safety.” the source code said SelfieSuspiciousEntityDetection.

funny how that works. you hand over your pass­port to use a chat­bot and some­where in a dat­a­cen­ter in iowa, a fa­cial recog­ni­tion al­go­rithm is check­ing whether you look like a po­lit­i­cally ex­posed per­son. your selfie gets a sim­i­lar­ity score. your name hits a watch­list. a cron job re-screens you every few weeks just to make sure you haven’t be­come a ter­ror­ist since the last time you asked GPT to write a cover let­ter.

so what do you do? well, we looked. found source code on a gov­ern­ment end­point with the door wide open. fa­cial recog­ni­tion, watch­lists, SAR fil­ings, in­tel­li­gence co­de­names, and much more.

oh, and we re­vealed the names of every sin­gle per­son re­spon­si­ble for this!!

fol­low­ing the works of eva and oth­ers on ID ver­i­fi­ca­tion by­passes, we de­cided to start look­ing into per­sona, yet an­other KYC ser­vice that uses fa­cial recog­ni­tion to ver­ify iden­ti­ties. the orig­i­nal goal was to add a age-ver­i­fi­ca­tion by­pass to eva’s ex­ist­ing k-id plat­form.

af­ter try­ing to write a few ex­ploits, vm­func de­cided to browse their in­fra on shodan. it all started with a Shodan search. a sin­gle IP. 34.49.93.177 sit­ting on Google Cloud in Kansas City. one open port. one SSL cer­tifi­cate. two host­names that tell a story no­body was sup­posed to read:

ope­nai-watch­listdb.with­per­sona.com

ope­nai-watch­listdb-test­ing.with­per­sona.com

not “openai-verify”, not “openai-kyc”, watch­listdb. a data­base. (or is it?)

it was ini­tially meant to be a pas­sive re­con in­ves­ti­ga­tion, that quickly turned into a rab­bit hole deep dive into how com­mer­cial AI and fed­eral gov­ern­ment op­er­a­tions work to­gether to vi­o­late our pri­vacy every wak­ing sec­ond. we did­n’t even have to write or per­form a sin­gle ex­ploit, the en­tire ar­chi­tec­ture was just on the doorstep!! 53 megabytes of un­pro­tected source maps on a FedRAMP gov­ern­ment end­point, ex­pos­ing the en­tire code­base of a plat­form that files Suspicious Activity Reports with FinCEN, com­pares your selfie to watch­list pho­tos us­ing fa­cial recog­ni­tion, screens you against 14 cat­e­gories of ad­verse me­dia from ter­ror­ism to es­pi­onage, and tags re­ports with co­de­names from ac­tive in­tel­li­gence pro­grams.

2,456 source files con­tain­ing the full TypeScript code­base, every per­mis­sion, every API end­point, every com­pli­ance rule, every screen­ing al­go­rithm. sit­ting unau­then­ti­cated on the pub­lic in­ter­net. on a gov­ern­ment plat­form no less.

no sys­tems were breached. no cre­den­tials were used. every find­ing in this doc­u­ment comes from pub­licly ac­ces­si­ble sources: shodan, cer­tifi­cate trans­parency logs, DNS res­o­lu­tion, HTTP re­sponse head­ers, pub­lished API doc­u­men­ta­tion, pub­lic web pages, and unau­then­ti­cated JavaScript source maps served by the tar­get’s own web server.

the in­fra­struc­ture told its own story. we just lis­tened. then we read the source code.

IP: 34.49.93.177

ASN: AS396982 (Google LLC)

provider: Google Cloud

re­gion: global

city: Kansas City, US

open ports: 443/tcp

last seen: 2026-02-05

host­names:

- 177.93.49.34.bc.googleusercontent.com

- ope­nai-watch­listdb.with­per­sona.com

- ope­nai-watch­listdb-test­ing.with­per­sona.com

SSL cert:

sub­ject: CN=openai-watchlistdb.withpersona.com

is­suer: C=US, O=Google Trust Services, CN=WR3

valid: Jan 24 01:24:11 2026 - Apr 24 02:20:06 2026

SANs: ope­nai-watch­listdb.with­per­sona.com

ope­nai-watch­listdb-test­ing.with­per­sona.com

se­r­ial: FDFFBF37ED89BBD710D9967B7CD92B52

HTTP re­sponse (all paths, all meth­ods):

sta­tus: 404

body: “fault fil­ter abort”

head­ers: via: 1.1 google

con­tent-type: text/​plain

Alt-Svc: h3=”:443″

the “fault fil­ter abort” re­sponse is an Envoy proxy fault in­jec­tion fil­ter. stan­dard in GCP/Istio ser­vice mesh de­ploy­ments. the ser­vice only routes re­quests match­ing spe­cific in­ter­nal cri­te­ria (likely mTLS client cer­tifi­cates, spe­cific source IPs, or API key head­ers). every­thing else just dies at the edge.

though ob­vi­ously this is not a mis­con­fig­u­ra­tion.. this is just a locked-down back­end ser­vice that was never meant to have a pub­lic face. the only rea­son we even know it ex­ists is be­cause of cer­tifi­cate trans­parency logs and DNS.

Persona (withpersona.com) is a San Francisco-based iden­tity ver­i­fi­ca­tion com­pany. their nor­mal in­fra­struc­ture runs be­hind Cloudflare:

with­per­sona.com -> 162.159.141.40, 172.66.1.36 (CF)

in­quiry.with­per­sona.com -> 162.159.141.40, 172.66.1.36 (CF)

app.with­per­sona.com -> 162.159.141.40, 172.66.1.36 (CF)

api.with­per­sona.com -> 162.159.141.40, 172.66.1.36 (CF)

they also run a wild­card DNS record, *.withpersona.com points to Cloudflare (cloudflare.withpersona.com.cdn.cloudflare.net). we con­firmed this by re­solv­ing com­pletely fab­ri­cated sub­do­mains:

to­tal­ly­nonex­is­ten­t12345.with­per­sona.com -> 162.159.141.40 (CF)

as­d­flkjhasdf.with­per­sona.com -> 162.159.141.40 (CF)

HOWEVER, here’s where it gets in­ter­est­ing. OpenAI’s watch­list ser­vice breaks out of this wild­card:

ope­nai-watch­listdb.with­per­sona.com -> 34.49.93.177 (GCP)

ope­nai-watch­listdb-test­ing.with­per­sona.com -> 34.49.93.177 (GCP)

a ded­i­cated Google Cloud in­stance, which is­n’t even be­hind Cloudflare, nor on Persona’s shared in­fra­struc­ture. seem­ingly pur­pose-built and iso­lated.

you would never do this for a sim­ple “check this name against a list” API call, you do this when the data re­quires com­part­men­tal­iza­tion. when the com­pli­ance re­quire­ments for the data you’re col­lect­ing, de­mand that level of iso­la­tion. when the dam­age of a breach is bad enough to war­rant ded­i­cated in­fra­struc­ture.

CT logs tell us ex­actly when this ser­vice went live and how it evolved.

no­vem­ber 2023. this ser­vice has been run­ning for over two years.

OpenAI did­n’t an­nounce “Verified Organization” re­quire­ments un­til mid-2025. they did­n’t pub­licly re­quire ID ver­i­fi­ca­tion for ad­vanced model ac­cess un­til GPT-5. but the watch­list screen­ing in­fra­struc­ture was op­er­a­tional 18 months be­fore any of that was dis­closed.

we can pin­point when they started con­sid­er­ing go­ing “public” with the col­lab­o­ra­tion.

https://​with­per­sona.com/​cus­tomers/​ope­nai ex­ists since September 17th, 2024, like­wise, OpenAI’s Privacy Policy up­date started in­clud­ing the fol­low­ing pas­sage since their November 4th, 2024 up­date as well.

“Other Information You Provide: We col­lect other in­for­ma­tion that you pro­vide to us, such as when you par­tic­i­pate in our events or sur­veys, or when you pro­vide us or a ven­dor op­er­at­ing on our be­half with in­for­ma­tion to es­tab­lish your iden­tity or age (collectively, “Other Information You Provide”).”

the ex­cuses used in the pub­lic post are clas­si­cal, though in­stead of us­ing chil­dren as the scape­goat for in­vad­ing our pri­vacy, this time it was ”[…] To of­fer safe AGI, we need to make sure bad peo­ple aren’t us­ing our ser­vices […].

only… that they quickly used this op­por­tu­nity to go from com­par­ing users against a sin­gle fed­eral watch­list, to cre­at­ing the watch­list of all users them­selves.

in fact, this is noth­ing new, OpenAI Forum User OnceAndTwice had men­tioned this al­ready back in June last year.

Persona’s API doc­u­men­ta­tion (docs.withpersona.com) is pub­lic. when a cus­tomer like OpenAI runs a gov­ern­ment ID ver­i­fi­ca­tion, the API re­turns a com­plete iden­tity dossier:

per­sonal iden­tity:

- full le­gal name (including na­tive script)

- date of birth, place of birth

- na­tion­al­ity, sex, height

ad­dress:

- street, city, state, postal code, coun­try

gov­ern­ment doc­u­ment:

- doc­u­ment type and num­ber

- is­su­ing au­thor­ity

- is­sue and ex­pi­ra­tion dates

- visa sta­tus

- ve­hi­cle class/​en­dorse­ments/​re­stric­tions

me­dia:

- FRONT PHOTO of ID doc­u­ment (URL)

- BACK PHOTO of ID doc­u­ment (URL)

- SELFIE PHOTO (URL + byte size)

- VIDEO of iden­tity cap­ture (URL)

meta­data:

- en­tity con­fi­dence score

- all ver­i­fi­ca­tion check re­sults with pass/​fail rea­sons

- cap­ture method used

- time­stamps (created, sub­mit­ted, com­pleted, redacted)

Persona’s own case study states that OpenAI “screens mil­lions monthly” and “automatically screens over 99% of users be­hind the scenes in sec­onds.”

be­hind the scenes. in sec­onds. mil­lions. with cus­tomiz­able fil­ters rang­ing from sim­ple par­tial name matches to ad­vanced fa­cial recog­ni­tion al­go­rithms.

again, none of this is even a se­cret, its “hidden” in plain sight.

The lat­est up­date of Firefox, ver­sion 148, in­tro­duces a much-an­tic­i­pated “AI kill switch” fea­ture, al­low­ing users to dis­able AI func­tion­al­i­ties such as chat­bot prompts and AI-generated link sum­maries. Mozilla em­pha­sizes that once AI fea­tures are turned off, fu­ture up­dates will not over­ride this choice. This de­ci­sion re­flects the com­pa­ny’s new rev­enue-fo­cused strat­egy re­gard­ing AI in­te­gra­tions.

To dis­able AI fea­tures, users can nav­i­gate to Settings > AI Controls and tog­gle the ‘Block AI Enhancements’ op­tion. This will pre­vent any in-app no­ti­fi­ca­tions en­cour­ag­ing users to try out AI fea­tures, as well as re­move any pre­vi­ously down­loaded AI mod­els from the de­vice. For those who wish to main­tain some AI func­tion­al­i­ties, a se­lec­tive block­ing op­tion is avail­able, en­abling users to re­tain use­ful fea­tures like on-de­vice trans­la­tions while avoid­ing cloud-based ser­vices.

Beyond the AI kill switch, Firefox 148 of­fers users more con­trol over re­mote up­dates, al­low­ing them to opt out while still min­i­miz­ing data col­lec­tion. Users can set these pref­er­ences un­der Settings > Privacy & Settings > Firefox Data Collection.

The up­date also fo­cuses on en­hanc­ing core web plat­form ca­pa­bil­i­ties, in­clud­ing the in­te­gra­tion of the Trusted Types API and Sanitizer API to com­bat cross-site script­ing (XSS) is­sues. Additionally, Firefox 148 now in­cludes im­proved screen reader com­pat­i­bil­ity for math­e­mat­i­cal for­mu­las in PDFs, avail­abil­ity of Firefox Backup on Windows 10, and trans­la­tion ca­pa­bil­i­ties for Vietnamese and Traditional Chinese. New tab wall­pa­pers will also be fea­tured in new con­tainer tabs, along­side the ad­di­tion of Service worker sup­port for WebGPU.

For more de­tailed in­for­ma­tion on the up­date, users can re­fer to the of­fi­cial re­lease notes.

Build, pro­gram, and sim­u­late hard­ware in the browser. Bring your work­shop to the web.

‘Students can’t rea­son’: Teachers warn AI is fu­el­ing a cri­sis in kids’ abil­ity to thinkDis­cord cuts ties with Peter Thiel–backed ver­i­fi­ca­tion soft­ware af­ter its code was found tied to U. S. sur­veil­lance ef­forts­S­ci­en­tists are push­ing back on warn­ings that mi­croplas­tics dam­age your health, say­ing peo­ple are just obese and call­ing some stud­ies ’a joke’Y­our Google search his­tory can be used against you in court. Does that vi­o­late the Constitution? and The Associated PressExclusive: Anthropic rolls out AI tool that can hunt soft­ware bugs on its own—in­clud­ing the most dan­ger­ous ones hu­mans mis­sPrince Andrew was just ar­rested over Epstein-related ‘misconduct.’ Here’s how low his net worth is—and how he’ll pay his le­gal fees

Scott Bessent has ’got a feel­ing’ that $175 bil­lion raised un­der the IEEPA is lost to the American peo­ple for goodIn less than a year, Trump erased 12 years of sol­vency for the trust fund that pays for Medicare Part ADiscord cuts ties with Peter Thiel–backed ver­i­fi­ca­tion soft­ware af­ter its code was found tied to U. S. sur­veil­lance ef­fort­s­The record gap be­tween cor­po­rate prof­its and worker pay has an ‘undercurrent of be­trayal,’ top econ­o­mist warns A two-child house­hold must earn $400,000 a year for child­care to be af­ford­able, study says. ’It’s easy to see why birth rates are falling’While Nvidia CEO Jensen Huang en­joys an over $150 bil­lion net worth, his fel­low co­founder Curtis Priem sold out in 2006—and missed out on $600 bil­lion

© 2026 Fortune Media IP Limited. All Rights Reserved. Use of this site con­sti­tutes ac­cep­tance of our Terms of Use and Privacy Policy | CA Notice at Collection and Privacy Notice | Do Not Sell/Share My Personal Information

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Apple to­day an­nounced a sig­nif­i­cant ex­pan­sion of fac­tory op­er­a­tions in Houston, bring­ing the fu­ture pro­duc­tion of Mac mini to the U. S. for the first time. The com­pany will also ex­pand ad­vanced AI server man­u­fac­tur­ing at the fac­tory and pro­vide hands-on train­ing at its new Advanced Manufacturing Center be­gin­ning later this year. Altogether, Apple’s Houston op­er­a­tions will cre­ate thou­sands of jobs.

“Apple is deeply com­mit­ted to the fu­ture of American man­u­fac­tur­ing, and we’re proud to sig­nif­i­cantly ex­pand our foot­print in Houston with the pro­duc­tion of Mac mini start­ing later this year,” said Tim Cook, Apple’s CEO. “We be­gan ship­ping ad­vanced AI servers from Houston ahead of sched­ule, and we’re ex­cited to ac­cel­er­ate that work even fur­ther.”

Technicians in pro­tec­tive cloth­ing work on com­put­ers and other equip­ment in a Houston fac­tory.

A worker in a lab coat stands be­hind an as­sem­bly line.

Technicians in pro­tec­tive cloth­ing walk through the hall­way of a Houston fac­tory.

Technicians in pro­tec­tive cloth­ing look at a mon­i­tor in a Houston fac­tory.

In Houston, work­ers as­sem­ble ad­vanced AI servers, in­clud­ing logic boards pro­duced on­site, which are then used in Apple data cen­ters in the U. S.

In Houston, work­ers as­sem­ble ad­vanced AI servers, in­clud­ing logic boards pro­duced on­site, which are then used in Apple data cen­ters in the U.S.

In Houston, work­ers as­sem­ble ad­vanced AI servers, in­clud­ing logic boards pro­duced on­site, which are then used in Apple data cen­ters in the U.S.

In Houston, work­ers as­sem­ble ad­vanced AI servers, in­clud­ing logic boards pro­duced on­site, which are then used in Apple data cen­ters in the U.S.

In Houston, work­ers as­sem­ble ad­vanced AI servers, in­clud­ing logic boards pro­duced on­site, which are then used in Apple data cen­ters in the U.S.

For more than two decades, users around the world have re­lied on the in­cred­i­bly pop­u­lar Mac mini for the tremen­dous power it packs into its ul­tra-com­pact de­sign. With its next-level AI ca­pa­bil­i­ties, it has be­come an es­sen­tial tool for every­one from stu­dents and as­pir­ing cre­atives to small busi­ness own­ers. Beginning later this year, Mac mini will be pro­duced at a new fac­tory on Apple’s Houston man­u­fac­tur­ing site, dou­bling the cam­pus’s foot­print.

Apple be­gan pro­duc­ing ad­vanced AI servers in Houston in 2025 for the first time, and pro­duc­tion is al­ready ahead of sched­ule. Servers as­sem­bled in Houston — in­clud­ing logic boards pro­duced on­site — are used in Apple data cen­ters around the coun­try.

Beyond pro­duc­tion, Apple is in­vest­ing in the work­force that will drive American man­u­fac­tur­ing for­ward. Later this year, Apple’s 20,000-square-foot Advanced Manufacturing Center is sched­uled to open its doors in Houston. Currently un­der con­struc­tion, the ded­i­cated fa­cil­ity will pro­vide hands-on train­ing in ad­vanced man­u­fac­tur­ing tech­niques to stu­dents, sup­plier em­ploy­ees, and American busi­nesses of all sizes. Apple ex­perts will teach par­tic­i­pants the same in­no­v­a­tive processes that are used to make Apple prod­ucts, al­low­ing American man­u­fac­tur­ers to take their work to the next level.

A worker stands in front of a large American flag in­side the un­der-con­struc­tion Apple Advanced Manufacturing Center in Houston.

An over­head shot of the un­der-con­struc­tion Apple Advanced Manufacturing Center in Houston.

Apple’s 20,000-square-foot Advanced Manufacturing Center opens later this year, and will pro­vide hands-on train­ing to stu­dents, sup­plier em­ploy­ees, and U. S. busi­nesses of all sizes.

Apple’s 20,000-square-foot Advanced Manufacturing Center opens later this year, and will pro­vide hands-on train­ing to stu­dents, sup­plier em­ploy­ees, and U.S. busi­nesses of all sizes.

Since an­nounc­ing its $600 bil­lion com­mit­ment to the U. S. last year, Apple and its American Manufacturing Program part­ners have al­ready reached sev­eral mile­stones:

Apple ex­ceeded its tar­get and sourced more than 20 bil­lion U.S.-made chips from 24 fac­to­ries across 12 states, in­clud­ing those of part­ners like TSMC, Broadcom, and Texas Instruments.

GlobalWafers has be­gun pro­duc­tion at its new $4 bil­lion bare sil­i­con wafer fa­cil­ity in Sherman, Texas. At Apple’s di­rec­tion, wafers pro­duced in Sherman will be used by Apple’s chip man­u­fac­tur­ing part­ners in the U.S., in­clud­ing TSMC and Texas Instruments.

Supported by Apple’s in­vest­ment, Amkor broke ground on its new $7 bil­lion semi­con­duc­tor ad­vanced pack­ag­ing and test fa­cil­ity in Peoria, Arizona, where Apple will be the first and largest cus­tomer.

Corning’s Harrodsburg, Kentucky, fa­cil­ity is now 100 per­cent ded­i­cated to cover glass for iPhone and Apple Watch shipped glob­ally, and by the end of this year, every new iPhone and Apple Watch will have cover glass made in the state.

In 2026, Apple is on track to pur­chase well over 100 mil­lion ad­vanced chips pro­duced by TSMC at its Arizona fa­cil­ity — a sig­nif­i­cant in­crease from 2025.

Apple opened its Apple Manufacturing Academy in Detroit, which is al­ready sup­port­ing more than 130 small- and medium-sized American man­u­fac­tur­ers with hands-on train­ing in AI, au­toma­tion, and smart man­u­fac­tur­ing. The acad­emy re­cently ex­panded with new vir­tual pro­gram­ming, giv­ing busi­nesses across the coun­try on-de­mand ac­cess to the cur­ricu­lum de­vel­oped by Apple ex­perts and Michigan State University fac­ulty.

Mac mini will be made at a new fa­cil­ity in Houston, and a soon-to-be-launched train­ing cen­ter will sup­port ad­vanced man­u­fac­tur­ing skills de­vel­op­ment

CUPERTINO, CALIFORNIA Apple to­day an­nounced a sig­nif­i­cant ex­pan­sion of fac­tory op­er­a­tions in Houston, bring­ing the fu­ture pro­duc­tion of Mac mini to the U.S. for the first time. The com­pany will also ex­pand ad­vanced AI server man­u­fac­tur­ing at the fac­tory and pro­vide hands-on train­ing at its new Advanced Manufacturing Center be­gin­ning later this year. Altogether, Apple’s Houston op­er­a­tions will cre­ate thou­sands of jobs.

“Apple is deeply com­mit­ted to the fu­ture of American man­u­fac­tur­ing, and we’re proud to sig­nif­i­cantly ex­pand our foot­print in Houston with the pro­duc­tion of Mac mini start­ing later this year,” said Tim Cook, Apple’s CEO. “We be­gan ship­ping ad­vanced AI servers from Houston ahead of sched­ule, and we’re ex­cited to ac­cel­er­ate that work even fur­ther.”

For more than two decades, users around the world have re­lied on the in­cred­i­bly pop­u­lar Mac mini for the tremen­dous power it packs into its ul­tra-com­pact de­sign. With its next-level AI ca­pa­bil­i­ties, it has be­come an es­sen­tial tool for every­one from stu­dents and as­pir­ing cre­atives to small busi­ness own­ers. Beginning later this year, Mac mini will be pro­duced at a new fac­tory on Apple’s Houston man­u­fac­tur­ing site, dou­bling the cam­pus’s foot­print.

Apple be­gan pro­duc­ing ad­vanced AI servers in Houston in 2025 for the first time, and pro­duc­tion is al­ready ahead of sched­ule. Servers as­sem­bled in Houston — in­clud­ing logic boards pro­duced on­site — are used in Apple data cen­ters around the coun­try.

Beyond pro­duc­tion, Apple is in­vest­ing in the work­force that will drive American man­u­fac­tur­ing for­ward. Later this year, Apple’s 20,000-square-foot Advanced Manufacturing Center is sched­uled to open its doors in Houston. Currently un­der con­struc­tion, the ded­i­cated fa­cil­ity will pro­vide hands-on train­ing in ad­vanced man­u­fac­tur­ing tech­niques to stu­dents, sup­plier em­ploy­ees, and American busi­nesses of all sizes. Apple ex­perts will teach par­tic­i­pants the same in­no­v­a­tive processes that are used to make Apple prod­ucts, al­low­ing American man­u­fac­tur­ers to take their work to the next level.

Since an­nounc­ing its $600 bil­lion com­mit­ment to the U.S. last year, Apple and its American Manufacturing Program part­ners have al­ready reached sev­eral mile­stones:

Apple ex­ceeded its tar­get and sourced more than 20 bil­lion U.S.-made chips from 24 fac­to­ries across 12 states, in­clud­ing those of part­ners like TSMC, Broadcom, and Texas Instruments.

GlobalWafers has be­gun pro­duc­tion at its new $4 bil­lion bare sil­i­con wafer fa­cil­ity in Sherman, Texas. At Apple’s di­rec­tion, wafers pro­duced in Sherman will be used by Apple’s chip man­u­fac­tur­ing part­ners in the U.S., in­clud­ing TSMC and Texas Instruments.

Supported by Apple’s in­vest­ment, Amkor broke ground on its new $7 bil­lion semi­con­duc­tor ad­vanced pack­ag­ing and test fa­cil­ity in Peoria, Arizona, where Apple will be the first and largest cus­tomer.

Corning’s Harrodsburg, Kentucky, fa­cil­ity is now 100 per­cent ded­i­cated to cover glass for iPhone and Apple Watch shipped glob­ally, and by the end of this year, every new iPhone and Apple Watch will have cover glass made in the state.

In 2026, Apple is on track to pur­chase well over 100 mil­lion ad­vanced chips pro­duced by TSMC at its Arizona fa­cil­ity — a sig­nif­i­cant in­crease from 2025.

Apple opened its Apple Manufacturing Academy in Detroit, which is al­ready sup­port­ing more than 130 small- and medium-sized American man­u­fac­tur­ers with hands-on train­ing in AI, au­toma­tion, and smart man­u­fac­tur­ing. The acad­emy re­cently ex­panded with new vir­tual pro­gram­ming, giv­ing busi­nesses across the coun­try on-de­mand ac­cess to the cur­ricu­lum de­vel­oped by Apple ex­perts and Michigan State University fac­ulty.

About Apple

Apple rev­o­lu­tion­ized per­sonal tech­nol­ogy with the in­tro­duc­tion of the Macintosh in 1984. Today, Apple leads the world in in­no­va­tion with iPhone, iPad, Mac, AirPods, Apple Watch, and Apple Vision Pro. Apple’s six soft­ware plat­forms — iOS, iPa­dOS, ma­cOS, watchOS, vi­sionOS, and tvOS — pro­vide seam­less ex­pe­ri­ences across all Apple de­vices and em­power peo­ple with break­through ser­vices in­clud­ing the App Store, Apple Music, Apple Pay, iCloud, and Apple TV. Apple’s more than 150,000 em­ploy­ees are ded­i­cated to mak­ing the best prod­ucts on earth and to leav­ing the world bet­ter than we found it.

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* Apple ex­ceeded its tar­get and sourced more than 20 bil­lion U.S.-made chips from 24 fac­to­ries across 12 states, in­clud­ing those of part­ners like TSMC, Broadcom, and Texas Instruments.

* GlobalWafers has be­gun pro­duc­tion at its new $4 bil­lion bare sil­i­con wafer fa­cil­ity in Sherman, Texas. At Apple’s di­rec­tion, wafers pro­duced in Sherman will be used by Apple’s chip man­u­fac­tur­ing part­ners in the U.S., in­clud­ing TSMC and Texas Instruments.

* Supported by Apple’s in­vest­ment, Amkor broke ground on its new $7 bil­lion semi­con­duc­tor ad­vanced pack­ag­ing and test fa­cil­ity in Peoria, Arizona, where Apple will be the first and largest cus­tomer.

* Corning’s Harrodsburg, Kentucky, fa­cil­ity is now 100 per­cent ded­i­cated to cover glass for iPhone and Apple Watch shipped glob­ally, and by the end of this year, every new iPhone and Apple Watch will have cover glass made in the state.

* In 2026, Apple is on track to pur­chase well over 100 mil­lion ad­vanced chips pro­duced by TSMC at its Arizona fa­cil­ity — a sig­nif­i­cant in­crease from 2025.

* Apple opened its Apple Manufacturing Academy in Detroit, which is al­ready sup­port­ing more than 130 small- and medium-sized American man­u­fac­tur­ers with hands-on train­ing in AI, au­toma­tion, and smart man­u­fac­tur­ing. The acad­emy re­cently ex­panded with new vir­tual pro­gram­ming, giv­ing busi­nesses across the coun­try on-de­mand ac­cess to the cur­ricu­lum de­vel­oped by Apple ex­perts and Michigan State University fac­ulty.

In 1978, for my 10th birth­day, I went to Disneyland and got to ride a new roller coaster called Space Mountain. It fig­u­ra­tively and lit­er­ally took my breath away. I loved every sec­ond of it and that night, I could­n’t fall asleep; I just kept think­ing about how ex­hil­a­rat­ing it was. Then, a wild thought sud­denly hit me: Why is­n’t there a roller coaster that goes up­side down?

At first, I was like that’s crazy, it can’t work. But then I re­mem­bered Spin Out, the ride with a round room that spun so fast I stuck to the wall. If that worked, why not a loop on a roller coaster? I thought that would feel and be like the same thing. I was con­vinced!

I fi­nally fell asleep dream­ing of my roller coaster, full of twists, turns, and loops.

A few days later, I told my best friend Daschle. He was older, knew every­thing, and lived next door. “Buddy,” he said, “I’ve got ex­cit­ing but crush­ing news. Your idea works.”

“Yep. I saw it. They’re build­ing one at Magic Mountain. It’s called the Revolution. Sorry, Buddy.”

But I was­n’t crushed, I was thrilled! What I knew could work was re­ally hap­pen­ing.

“How many loops does it have?” I asked.

“Ha! Mine has four. It’s called the Quadrupuler! It’s gonna be way bet­ter!”

That night I taped six sheets of pa­per to­gether and drew my blue­prints in col­ored mark­ers. As you can see from the photo it was glo­ri­ous!

Look closely, I did­n’t la­bel those coaster hills in feet or me­ters, no sir, I used build­ing “story’s” for height, and the speed at each sec­tion in miles per hour. I’m 10. I’m se­ri­ous here.

With guid­ing blue­prints, it was time to build the model.

I got a Styrofoam board and balsa wood. Cutting and glu­ing each tiny cross tie was slow, and with all my home­work, I could only work on week­ends. So I cal­cu­lated how many inches I could fin­ish in a week. The an­swer turned out to be some­thing like 5 months! After that I con­sid­ered just giv­ing up be­cause I re­al­ized that I was only 120 months old and this was go­ing to take 5% of my life! Plus, I still had­n’t fig­ured out how to make the loops, balsa wood does­n’t bend like that. But I told my­self: one piece at a time. That be­came my motto.

When I got to the first loop, I had to stop and think. What in the world could I make the loop out of? A lot of 10-year-old brain power went into imag­in­ing what sim­ple ma­te­r­ial I could use. Then one morn­ing, I had it: heat plas­tic strips over the stove­top flame and bend them as they cooled. The key? Don’t burn the house down.

I’d learned that the hard way a year ear­lier, when Daschle con­vinced me we should recre­ate the movie The Towering Inferno, with a card­board box un­der his house… and real fire. It got out of con­trol so fast, the flames started hit­ting the wood floor joists! Thankfully, we were able to smother it with the damp dirt down there. So yeah, wild card Daschle was not in­vited over for my plas­tic fire bend­ing ex­per­i­ment.

I don’t re­mem­ber where the plas­tic came from, but I do re­mem­ber hold­ing the strip with pli­ers over the flame. The first piece melted so fast and started burn­ing with thick black smoke that it scared me. I yanked it back and coughed. That’s when I made an amend­ment to the safety plan: don’t kill your­self with what­ever these hor­ri­ble smelly fumes were! I got a fan, opened the back door, and all the kitchen win­dows be­fore try­ing again. Eventually, I fig­ured out the per­fect dis­tance and tim­ing with the heat.

When I laid that fi­nal track piece, I was so ex­cited, so proud! I took the model out­side for bet­ter light­ing and snapped Polaroids. I needed it cap­tured in­stantly. Here’s a photo of the Polaroid with my 10-year-old pen­man­ship.

What was the next thought that im­me­di­ately popped into my head?

This mas­ter­piece is ready to be sold to Disneyland! And I wrote my let­ter. I don’t have the orig­i­nal of that. But I re­mem­ber it went some­thing like this:

To whom it may con­cern:

My name is Kevin Glikmann. I am 10 years old. Enclosed are Polaroids of a roller coaster model I made called the Quadrupuler. It has four loops! I think you should make it!

And I sent it off!

Suddenly, my chore of check­ing the mail af­ter school be­came a heart-pound­ing rit­ual. I was ner­vous, hope­ful, ex­cited. Sometimes I opened the mail­box slowly, peek­ing in. Sometimes I pre­tended it was just a nor­mal day. Other times, I yanked it open and grabbed the mail fast, try­ing any­thing to calm my nerves.

Daschle said, “No way they’ll re­spond. It’s Disneyland, Buddy, they get a mil­lion let­ters a day.”

Weeks turned into months, and I started to think he was right. Then one day, I opened the mail­box.

My name on it. My head was scream­ing, “This is it! I never get mail!”

HOLY SMOKES! What’s WED Enterprises? I started bounc­ing up and down. I started shak­ing. I ran into the house, ran straight to my room, tore open the en­ve­lope, and read:

Your re­cent let­ter was di­rected to my of­fice here at WED Enterprises. WED (Walter Elias Disney) is the de­sign and “Imagineering” branch of Walt Disney Productions. As such, we are re­spon­si­ble for the cre­ation of all shows, at­trac­tions and out­door en­ter­tain­ment for both Disneyland and Walt Disney World.

Thank you for show­ing us your “Quadrupuler” roller coaster - it looks like quite an ad­ven­ture! As you may know Kevin, we are cre­at­ing a new roller­coaster type at­trac­tion for Disneyland’s Frontierland. Known as Big Thunder Mountain Railroad, this thrilling ad­ven­ture will carry pas­sen­gers on a high speed jour­ney through the gold rush days of the old west. Big Thunder is sched­uled to open later this year.

Thank you Kevin, for your in­ter­est in Walt Disney Productions.

Here is a photo of the orig­i­nal let­ter:

You would think that this let­ter would have ended my in­vent­ing spirit. That I would have got­ten bit­ter and de­clared to the world, “No more will I in­vent for that mouse or any­one else!”

But no! Instead I was elated. I read it over and over. It said, “It looks like quite an ad­ven­ture!” Disneyland liked it! I could­n’t be­lieve it.

Looking back, those words from Tom Fitzgerald did­n’t just val­i­date my idea, they launched my 10-year-old self-es­teem into or­bit! (Tom Fitzgerald went on to be­come one of the most in­flu­en­tial Imagineers in Disney his­tory. According to his bio, he started in 1979. I got this let­ter in April 1979 which means this must have been one of his first tasks as a new Imagineer em­ployee. lol! I won­der if he would re­mem­ber?)

A cou­ple years later, the Rubik’s Cube came out. I was ob­sessed. It took me weeks to solve, and once I did, my first thought was: What if it could turn on the an­gle? So I in­tro­duced Mr. Rubik’s Cube to my band­saw, re­designed the core, and built a very rough pro­to­type.

Here are some pic­tures.

I sent it to Ideal Toy Company, but they re­jected it straight away, they don’t ac­cept un­so­licited ideas. But that did­n’t mat­ter. They did­n’t un­der­stand that I had a let­ter from Disney Imagineering telling me my ideas are good!

That ten-year-old in­ven­tor is still alive in me, and still does­n’t un­der­stand re­jec­tion. Over the decades, I’ve in­vented sev­eral patented board games that were shopped around but never sold.

But I’m con­vinced the early val­i­da­tion from the Disney let­ter gave me a kind of bul­let­proof re­silience.

Today, I work in one of the most re­jec­tion-heavy in­dus­tries there is, act­ing. To me, in­vent­ing and act­ing are deeply con­nected: both are about dis­cov­ery, and both feed my in­vent­ing spirit. Successes are rare, but when they come, the joy lasts for­ever.

So I keep au­di­tion­ing, and I keep in­vent­ing.

And some­times, when frus­tra­tion creeps in, won­der­ing why I’m not fur­ther along, or why things aren’t work­ing out, that 10-year-old boy ap­pears. He re­minds me of what we be­lieved back then, and what still guides me now- just keep go­ing, one piece at a time.

*This post was up­dated at 12:35 pm PT to fix a typo in the build time bench­marks.

Last week, one en­gi­neer and an AI model re­built the most pop­u­lar front-end frame­work from scratch. The re­sult, vinext (pronounced “vee-next”), is a drop-in re­place­ment for Next.js, built on Vite, that de­ploys to Cloudflare Workers with a sin­gle com­mand. In early bench­marks, it builds pro­duc­tion apps up to 4x faster and pro­duces client bun­dles up to 57% smaller. And we al­ready have cus­tomers run­ning it in pro­duc­tion.

The whole thing cost about $1,100 in to­kens.

Next.js is the most pop­u­lar React frame­work. Millions of de­vel­op­ers use it. It pow­ers a huge chunk of the pro­duc­tion web, and for good rea­son. The de­vel­oper ex­pe­ri­ence is top-notch.

But Next.js has a de­ploy­ment prob­lem when used in the broader server­less ecosys­tem. The tool­ing is en­tirely be­spoke: Next.js has in­vested heav­ily in Turbopack but if you want to de­ploy it to Cloudflare, Netlify, or AWS Lambda, you have to take that build out­put and re­shape it into some­thing the tar­get plat­form can ac­tu­ally run.

If you’re think­ing: “Isn’t that what OpenNext does?”, you are cor­rect.

That is in­deed the prob­lem OpenNext was built to solve. And a lot of en­gi­neer­ing ef­fort has gone into OpenNext from mul­ti­ple providers, in­clud­ing us at Cloudflare. It works, but quickly runs into lim­i­ta­tions and be­comes a game of whack-a-mole.

Building on top of Next.js out­put as a foun­da­tion has proven to be a dif­fi­cult and frag­ile ap­proach. Because OpenNext has to re­verse-en­gi­neer Next.js’s build out­put, this re­sults in un­pre­dictable changes be­tween ver­sions that take a lot of work to cor­rect.

Next.js has been work­ing on a first-class adapters API, and we’ve been col­lab­o­rat­ing with them on it. It’s still an early ef­fort but even with adapters, you’re still build­ing on the be­spoke Turbopack tool­chain. And adapters only cover build and de­ploy. During de­vel­op­ment, next dev runs ex­clu­sively in Node.js with no way to plug in a dif­fer­ent run­time. If your ap­pli­ca­tion uses plat­form-spe­cific APIs like Durable Objects, KV, or AI bind­ings, you can’t test that code in dev with­out workarounds.

What if in­stead of adapt­ing Next.js out­put, we reim­ple­mented the Next.js API sur­face on Vite di­rectly? Vite is the build tool used by most of the front-end ecosys­tem out­side of Next.js, pow­er­ing frame­works like Astro, SvelteKit, Nuxt, and Remix. A clean reim­ple­men­ta­tion, not merely a wrap­per or adapter. We hon­estly did­n’t think it would work. But it’s 2026, and the cost of build­ing soft­ware has com­pletely changed.

We got a lot fur­ther than we ex­pected.

Replace next with vinext in your scripts and every­thing else stays the same. Your ex­ist­ing app/, pages/, and next.con­fig.js work as-is.

vinext dev # Development server with HMR

vinext build # Production build

vinext de­ploy # Build and de­ploy to Cloudflare Workers

This is not a wrap­per around Next.js and Turbopack out­put. It’s an al­ter­na­tive im­ple­men­ta­tion of the API sur­face: rout­ing, server ren­der­ing, React Server Components, server ac­tions, caching, mid­dle­ware. All of it built on top of Vite as a plu­gin. Most im­por­tantly Vite out­put runs on any plat­form thanks to the Vite Environment API.

Early bench­marks are promis­ing. We com­pared vinext against Next.js 16 us­ing a shared 33-route App Router ap­pli­ca­tion.

Both frame­works are do­ing the same work: com­pil­ing, bundling, and prepar­ing server-ren­dered routes. We dis­abled TypeScript type check­ing and ESLint in Next.js’s build (Vite does­n’t run these dur­ing builds), and used force-dy­namic so Next.js does­n’t spend ex­tra time pre-ren­der­ing sta­tic routes, which would un­fairly slow down its num­bers. The goal was to mea­sure only bundler and com­pi­la­tion speed, noth­ing else. Benchmarks run on GitHub CI on every merge to main.

These bench­marks mea­sure com­pi­la­tion and bundling speed, not pro­duc­tion serv­ing per­for­mance. The test fix­ture is a sin­gle 33-route app, not a rep­re­sen­ta­tive sam­ple of all pro­duc­tion ap­pli­ca­tions. We ex­pect these num­bers to evolve as three pro­jects con­tinue to de­velop. The full method­ol­ogy and his­tor­i­cal re­sults are pub­lic. Take them as di­rec­tional, not de­fin­i­tive.

The di­rec­tion is en­cour­ag­ing, though. Vite’s ar­chi­tec­ture, and es­pe­cially Rolldown (the Rust-based bundler com­ing in Vite 8), has struc­tural ad­van­tages for build per­for­mance that show up clearly here.

vinext is built with Cloudflare Workers as the first de­ploy­ment tar­get. A sin­gle com­mand takes you from source code to a run­ning Worker:

This han­dles every­thing: builds the ap­pli­ca­tion, auto-gen­er­ates the Worker con­fig­u­ra­tion, and de­ploys. Both the App Router and Pages Router work on Workers, with full client-side hy­dra­tion, in­ter­ac­tive com­po­nents, client-side nav­i­ga­tion, React state.

For pro­duc­tion caching, vinext in­cludes a Cloudflare KV cache han­dler that gives you ISR (Incremental Static Regeneration) out of the box:

KV is a good de­fault for most ap­pli­ca­tions, but the caching layer is de­signed to be plug­gable. That set­CacheHan­dler call means you can swap in what­ever back­end makes sense. R2 might be a bet­ter fit for apps with large cached pay­loads or dif­fer­ent ac­cess pat­terns. We’re also work­ing on im­prove­ments to our Cache API that should pro­vide a strong caching layer with less con­fig­u­ra­tion. The goal is flex­i­bil­ity: pick the caching strat­egy that fits your app.

We also have a live ex­am­ple of Cloudflare Agents run­ning in a Next.js app, with­out the need for workarounds like get­Plat­form­Proxy, since the en­tire app now runs in work­erd, dur­ing both dev and de­ploy phases. This means be­ing able to use Durable Objects, AI bind­ings, and every other Cloudflare-specific ser­vice with­out com­pro­mise. Have a look here.

The cur­rent de­ploy­ment tar­get is Cloudflare Workers, but that’s a small part of the pic­ture. Something like 95% of vinext is pure Vite. The rout­ing, the mod­ule shims, the SSR pipeline, the RSC in­te­gra­tion: none of it is Cloudflare-specific.

Cloudflare is look­ing to work with other host­ing providers about adopt­ing this tool­chain for their cus­tomers (the lift is min­i­mal — we got a proof-of-con­cept work­ing on Vercel in less than 30 min­utes!). This is an open-source pro­ject, and for its long term suc­cess, we be­lieve it’s im­por­tant we work with part­ners across the ecosys­tem to en­sure on­go­ing in­vest­ment. PRs from other plat­forms are wel­come. If you’re in­ter­ested in adding a de­ploy­ment tar­get, open an is­sue or reach out.

We want to be clear: vinext is ex­per­i­men­tal. It’s not even one week old, and it has not yet been bat­tle-tested with any mean­ing­ful traf­fic at scale. If you’re eval­u­at­ing it for a pro­duc­tion ap­pli­ca­tion, pro­ceed with ap­pro­pri­ate cau­tion.

That said, the test suite is ex­ten­sive: over 1,700 Vitest tests and 380 Playwright E2E tests, in­clud­ing tests ported di­rectly from the Next.js test suite and OpenNext’s Cloudflare con­for­mance suite. We’ve ver­i­fied it against the Next.js App Router Playground. Coverage sits at 94% of the Next.js 16 API sur­face.

Early re­sults from real-world cus­tomers are en­cour­ag­ing. We’ve been work­ing with National Design Studio, a team that’s aim­ing to mod­ern­ize every gov­ern­ment in­ter­face, on one of their beta sites, CIO.gov. They’re al­ready run­ning vinext in pro­duc­tion, with mean­ing­ful im­prove­ments in build times and bun­dle sizes.

The README is hon­est about what’s not sup­ported and won’t be, and about known lim­i­ta­tions. We want to be up­front rather than over­promise.

vinext al­ready sup­ports Incremental Static Regeneration (ISR) out of the box. After the first re­quest to any page, it’s cached and reval­i­dated in the back­ground, just like Next.js. That part works to­day.

vinext does not yet sup­port sta­tic pre-ren­der­ing at build time. In Next.js, pages with­out dy­namic data get ren­dered dur­ing next build and served as sta­tic HTML. If you have dy­namic routes, you use gen­er­at­eSta­t­ic­Params() to enu­mer­ate which pages to build ahead of time. vinext does­n’t do that… yet.

This was an in­ten­tional de­sign de­ci­sion for launch. It’s on the roadmap, but if your site is 100% pre­built HTML with sta­tic con­tent, you prob­a­bly won’t see much ben­e­fit from vinext to­day. That said, if one en­gi­neer can spend $1,100 in to­kens and re­build Next.js, you can prob­a­bly spend $10 and mi­grate to a Vite-based frame­work de­signed specif­i­cally for sta­tic con­tent, like Astro (which also de­ploys to Cloudflare Workers).

For sites that aren’t purely sta­tic, though, we think we can do some­thing bet­ter than pre-ren­der­ing every­thing at build time.

Next.js pre-ren­ders every page listed in gen­er­at­eSta­t­ic­Params() dur­ing the build. A site with 10,000 prod­uct pages means 10,000 ren­ders at build time, even though 99% of those pages may never re­ceive a re­quest. Builds scale lin­early with page count. This is why large Next.js sites end up with 30-minute builds.

So we built Traffic-aware Pre-Rendering (TPR). It’s ex­per­i­men­tal to­day, and we plan to make it the de­fault once we have more real-world test­ing be­hind it.

The idea is sim­ple. Cloudflare is al­ready the re­verse proxy for your site. We have your traf­fic data. We know which pages ac­tu­ally get vis­ited. So in­stead of pre-ren­der­ing every­thing or pre-ren­der­ing noth­ing, vinext queries Cloudflare’s zone an­a­lyt­ics at de­ploy time and pre-ren­ders only the pages that mat­ter.

vinext de­ploy –experimental-tpr

Building…

Build com­plete (4.2s)

TPR (experimental): Analyzing traf­fic for my-store.com (last 24h)

TPR: 12,847 unique paths — 184 pages cover 90% of traf­fic

TPR: Pre-rendering 184 pages…

TPR: Pre-rendered 184 pages in 8.3s → KV cache

Deploying to Cloudflare Workers…

For a site with 100,000 prod­uct pages, the power law means 90% of traf­fic usu­ally goes to 50 to 200 pages. Those get pre-ren­dered in sec­onds. Everything else falls back to on-de­mand SSR and gets cached via ISR af­ter the first re­quest. Every new de­ploy re­freshes the set based on cur­rent traf­fic pat­terns. Pages that go vi­ral get picked up au­to­mat­i­cally. All of this works with­out gen­er­at­eSta­t­ic­Params() and with­out cou­pling your build to your pro­duc­tion data­base.

A pro­ject like this would nor­mally take a team of en­gi­neers months, if not years. Several teams at var­i­ous com­pa­nies have at­tempted it, and the scope is just enor­mous. We tried once at Cloudflare! Two routers, 33+ mod­ule shims, server ren­der­ing pipelines, RSC stream­ing, file-sys­tem rout­ing, mid­dle­ware, caching, sta­tic ex­port. There’s a rea­son no­body has pulled it off.

This time we did it in un­der a week. One en­gi­neer (technically en­gi­neer­ing man­ager) di­rect­ing AI.

The first com­mit landed on February 13. By the end of that same evening, both the Pages Router and App Router had ba­sic SSR work­ing, along with mid­dle­ware, server ac­tions, and stream­ing. By the next af­ter­noon, App Router Playground was ren­der­ing 10 of 11 routes. By day three, vinext de­ploy was ship­ping apps to Cloudflare Workers with full client hy­dra­tion. The rest of the week was hard­en­ing: fix­ing edge cases, ex­pand­ing the test suite, bring­ing API cov­er­age to 94%.

What changed from those ear­lier at­tempts? AI got bet­ter. Way bet­ter.

Not every pro­ject would go this way. This one did be­cause a few things hap­pened to line up at the right time.

Next.js is well-spec­i­fied. It has ex­ten­sive doc­u­men­ta­tion, a mas­sive user base, and years of Stack Overflow an­swers and tu­to­ri­als. The API sur­face is all over the train­ing data. When you ask Claude to im­ple­ment get­Server­Side­Props or ex­plain how useRouter works, it does­n’t hal­lu­ci­nate. It knows how Next works.

Next.js has an elab­o­rate test suite. The Next.js repo con­tains thou­sands of E2E tests cov­er­ing every fea­ture and edge case. We ported tests di­rectly from their suite (you can see the at­tri­bu­tion in the code). This gave us a spec­i­fi­ca­tion we could ver­ify against me­chan­i­cally.

Vite is an ex­cel­lent foun­da­tion. Vite han­dles the hard parts of front-end tool­ing: fast HMR, na­tive ESM, a clean plu­gin API, pro­duc­tion bundling. We did­n’t have to build a bundler. We just had to teach it to speak Next.js. @vitejs/plugin-rsc is still early, but it gave us React Server Components sup­port with­out hav­ing to build an RSC im­ple­men­ta­tion from scratch.

The mod­els caught up. We don’t think this would have been pos­si­ble even a few months ago. Earlier mod­els could­n’t sus­tain co­her­ence across a code­base this size. New mod­els can hold the full ar­chi­tec­ture in con­text, rea­son about how mod­ules in­ter­act, and pro­duce cor­rect code of­ten enough to keep mo­men­tum go­ing. At times, I saw it go into Next, Vite, and React in­ter­nals to fig­ure out a bug. The state-of-the-art mod­els are im­pres­sive, and they seem to keep get­ting bet­ter.

All of those things had to be true at the same time. Well-documented tar­get API, com­pre­hen­sive test suite, solid build tool un­der­neath, and a model that could ac­tu­ally han­dle the com­plex­ity. Take any one of them away and this does­n’t work nearly as well.

Almost every line of code in vinext was writ­ten by AI. But here’s the thing that mat­ters more: every line passes the same qual­ity gates you’d ex­pect from hu­man-writ­ten code. The pro­ject has 1,700+ Vitest tests, 380 Playwright E2E tests, full TypeScript type check­ing via tsgo, and lint­ing via oxlint. Continuous in­te­gra­tion runs all of it on every pull re­quest. Establishing a set of good guardrails is crit­i­cal to mak­ing AI pro­duc­tive in a code­base.

The process started with a plan. I spent a cou­ple of hours go­ing back and forth with Claude in OpenCode to de­fine the ar­chi­tec­ture: what to build, in what or­der, which ab­strac­tions to use. That plan be­came the north star. From there, the work­flow was straight­for­ward:

Let the AI write the im­ple­men­ta­tion and tests. If tests pass, merge. If not, give the AI the er­ror out­put and let it it­er­ate.

We wired up AI agents for code re­view too. When a PR was opened, an agent re­viewed it. When re­view com­ments came back, an­other agent ad­dressed them. The feed­back loop was mostly au­to­mated.

It did­n’t work per­fectly every time. There were PRs that were just wrong. The AI would con­fi­dently im­ple­ment some­thing that seemed right but did­n’t match ac­tual Next.js be­hav­ior. I had to course-cor­rect reg­u­larly. Architecture de­ci­sions, pri­or­i­ti­za­tion, know­ing when the AI was headed down a dead end: that was all me. When you give AI good di­rec­tion, good con­text, and good guardrails, it can be very pro­duc­tive. But the hu­man still has to steer.

For browser-level test­ing, I used agent-browser to ver­ify ac­tual ren­dered out­put, client-side nav­i­ga­tion, and hy­dra­tion be­hav­ior. Unit tests miss a lot of sub­tle browser is­sues. This caught them.

Over the course of the pro­ject, we ran over 800 ses­sions in OpenCode. Total cost: roughly $1,100 in Claude API to­kens.

Why do we have so many lay­ers in the stack? This pro­ject forced me to think deeply about this ques­tion. And to con­sider how AI im­pacts the an­swer.

Most ab­strac­tions in soft­ware ex­ist be­cause hu­mans need help. We could­n’t hold the whole sys­tem in our heads, so we built lay­ers to man­age the com­plex­ity for us. Each layer made the next per­son’s job eas­ier. That’s how you end up with frame­works on top of frame­works, wrap­per li­braries, thou­sands of lines of glue code.

AI does­n’t have the same lim­i­ta­tion. It can hold the whole sys­tem in con­text and just write the code. It does­n’t need an in­ter­me­di­ate frame­work to stay or­ga­nized. It just needs a spec and a foun­da­tion to build on.

It’s not clear yet which ab­strac­tions are truly foun­da­tional and which ones were just crutches for hu­man cog­ni­tion. That line is go­ing to shift a lot over the next few years. But vinext is a data point. We took an API con­tract, a build tool, and an AI model, and the AI wrote every­thing in be­tween. No in­ter­me­di­ate frame­work needed. We think this pat­tern will re­peat across a lot of soft­ware. The lay­ers we’ve built up over the years aren’t all go­ing to make it.

Thanks to the Vite team. Vite is the foun­da­tion this whole thing stands on. @vitejs/plugin-rsc is still early days, but it gave me RSC sup­port with­out hav­ing to build that from scratch, which would have been a deal­breaker. The Vite main­tain­ers were re­spon­sive and help­ful as I pushed the plu­gin into ter­ri­tory it had­n’t been tested in be­fore.

We also want to ac­knowl­edge the Next.js team. They’ve spent years build­ing a frame­work that raised the bar for what React de­vel­op­ment could look like. The fact that their API sur­face is so well-doc­u­mented and their test suite so com­pre­hen­sive is a big part of what made this pro­ject pos­si­ble. vinext would­n’t ex­ist with­out the stan­dard they set.

vinext in­cludes an Agent Skill that han­dles mi­gra­tion for you. It works with Claude Code, OpenCode, Cursor, Codex, and dozens of other AI cod­ing tools. Install it, open your Next.js pro­ject, and tell the AI to mi­grate:

Then open your Next.js pro­ject in any sup­ported tool and say:

The skill han­dles com­pat­i­bil­ity check­ing, de­pen­dency in­stal­la­tion, con­fig gen­er­a­tion, and dev server startup. It knows what vinext sup­ports and will flag any­thing that needs man­ual at­ten­tion.

Or if you pre­fer do­ing it by hand:

npx vinext init # Migrate an ex­ist­ing Next.js pro­ject

npx vinext dev # Start the dev server

npx vinext de­ploy # Ship to Cloudflare Workers

The source is at github.com/​cloud­flare/​vinext. Issues, PRs, and feed­back are wel­come.