Um Apple I funcional, de 1977, entrou em leilão pela RR Auction. E o destaque vai para o seu valor estimado, de US$300 mil — os lances começam em US$10 mil.
Ele é um dos 50 modelos do segundo lote produzido pela Apple e está instalado em uma mala adaptada a partir de uma máquina de escrever Smith-Corona, sendo restaurado pelo especialista Corey Cohen, em junho, para funcionamento.
Divulgação/RR Auction
O modelo do leilão, “Neumark”, destaca-se por incluir mais do que a placa de circuito montada, a única coisa que os compradores do Apple I recebiam ao adquirir a máquina.
O item faz parte da segunda parte do “Steve Jobs & the Computer Revolution: The Apple 50th Anniversary Auction”, um leilão comemorativo que inclui objetos históricos da Apple, como um iPhone original lacrado, um protótipo do primeiro iPod — cada um podendo chegar a um valor de US$50 mil —, documentos como um cartão de visitas da Maçã assinado por Steve Jobs, um cheque da Apple assinado por ele (destinado a Elizabeth Holmes, primeira responsável pela contabilidade da empresa) e, ainda, itens pessoais do cofundador e ex-CEO 1Chief executive officer, ou diretor executivo. da Maçã.
Os lances poderão ser feitos até o dia 20 de agosto, às 18h (horário da Costa Leste dos Estados Unidos). Às 19h, entra em vigor a regra de prorrogação automática do leilão, que estende-o em intervalos de 30 minutos a partir do registro de novos lances.
Siri Wolfram Alpha integration helped create one of the defining moments in the early history of consumer artificial intelligence. When Apple introduced Siri with iPhone 4S in October 2011, users were not merely given another form of voice control. They could ask a spoken question and receive a calculated answer rather than a page of search results.
Questions involving mathematics, measurements, dates, nutrition, astronomy and factual comparisons could be routed to Wolfram Alpha, a computational knowledge engine launched in 2009. Siri handled the conversation, while Wolfram Alpha supplied structured information and calculations behind many of the responses.
The experience could feel remarkably advanced for its time. Asking how many days remained before a holiday, comparing the populations of two cities or converting miles into kilometers no longer required opening Safari, entering a query and selecting a website.
That direct path from natural language to a useful answer established an expectation that continues shaping AI products today.
Its technological roots extend to research conducted at SRI International, including work associated with the DARPA-funded CALO project. The objective was to develop systems capable of learning, organizing information and helping people complete everyday tasks.
SRI later spun the technology into Siri Inc., founded by a team including Dag Kittlaus, Adam Cheyer and Tom Gruber. The company released a standalone Siri app for iPhone in early 2010.
The original product was designed around actions rather than ordinary web search. A user could ask for a restaurant reservation, request a taxi, check entertainment listings or search for local services. Siri attempted to understand the intent and connect the request with an appropriate online provider.
This approach was ambitious because the assistant needed to coordinate several different systems. Speech had to be converted into text, the request had to be interpreted, context had to be considered and an external service had to return something useful.
Apple acquired Siri in April 2010. Steve Jobs had personally recognized the potential of moving beyond a collection of apps toward a conversational layer capable of reaching them on behalf of the user.
When the assistant returned as an integrated feature of iPhone 4S, Apple had narrowed some aspects of the original startup vision while making the technology accessible to a much larger audience.
Siri could send messages, create reminders, place calls, manage calendar events, check weather conditions and answer questions. Apple initially labeled the feature as a beta, an unusual decision for a prominent part of a new iPhone launch.
The beta label acknowledged that natural-language interaction remained unpredictable. Accents, ambiguous phrasing, network conditions and external data providers could all influence whether a request succeeded.
Image Source: Google
Siri Wolfram Alpha Made Answers Feel Immediate
Siri Wolfram Alpha became especially memorable because it showed the difference between retrieving information and computing an answer.
A conventional search engine could locate pages containing a formula. Wolfram Alpha could apply that formula to the values supplied by the user. It could interpret units, compare quantities, calculate probabilities and organize factual data into a structured response.
That distinction allowed Siri to appear more knowledgeable than a voice interface simply reading search results aloud.
A request such as “What is 15% of $86?” could return the calculation directly. A question about the distance between planets could produce a value without requiring the user to inspect several websites. Wolfram Alpha could also answer unusually specific requests, including information about aircraft flying overhead when the necessary location and aviation data were available.
The system was not a large language model. It did not generate open-ended prose in the way current AI assistants do. Wolfram Alpha relied on curated data, symbolic computation, algorithms and formal representations of knowledge.
That structure provided an advantage that remains relevant: many answers could be calculated and traced through defined information rather than improvised statistically.
Early Siri combined several specialized capabilities instead of depending on one system to do everything. One provider might supply restaurant information, another could handle maps and Wolfram Alpha could process computational questions.
The assistant acted as the conversational coordinator.
This architecture made Siri seem like one intelligence even though the response could come from a network of separate services. Modern AI platforms have returned to a similar idea through tools, agents and external data connections. A language model may manage the conversation while calling a calculator, calendar, search engine or business system when a task requires reliable external action.
Siri demonstrated that model on a consumer smartphone more than a decade earlier.
A Small Integration Created a Large Expectation
The Wolfram Alpha partnership influenced how people began judging digital assistants.
Before Siri, voice features on phones were commonly associated with rigid commands such as calling a contact or selecting music. Siri invited users to speak more naturally and attempt questions that would previously have been typed into a browser.
The results were inconsistent, but successful interactions changed perceptions immediately. The iPhone appeared capable of understanding intent, reaching into a knowledge system and returning a concise answer through one conversational interface.
That apparent simplicity concealed substantial infrastructure. Speech recognition, language interpretation, location, personal context and external databases all had to work together quickly enough to preserve the feeling of a conversation.
Wolfram Alpha also gave Apple access to expertise that would have taken years to reproduce internally. Stephen Wolfram had spent decades building Mathematica and computational systems before launching the public knowledge engine.
Following the Siri announcement, Wolfram described the integration as a characteristically direct Steve Jobs decision: users wanted access to knowledge and actions without unnecessary intermediate steps.
That idea became more influential than any individual answer Siri provided.
The assistant did not need to show how many services had participated. It needed to understand the request and return the result.
Early Siri Also Revealed the Limits of the Model
The first version of Siri could feel futuristic one moment and frustrating the next.
Some questions reached Wolfram Alpha correctly, while similar wording could trigger a web search or an unrelated response. Siri occasionally struggled to determine whether the user wanted a calculation, a local result or an action inside the phone.
Wolfram Alpha responses were also better suited to some subjects than others. Mathematical and scientific questions matched its computational structure, while casual conversation, current events and subjective requests required different sources.
Network dependence created another weakness. Early Siri processing relied heavily on remote servers, so delays or outages could make a basic request fail even when the iPhone itself was functioning normally.
Those limitations foreshadowed the central challenge surrounding modern assistants. A convincing interface encourages people to ask almost anything, but no single technical system performs equally well across every type of request.
Current generative AI can produce more natural language and handle a wider range of topics. It can also create confident errors when factual grounding is weak. The computational approach represented by Wolfram Alpha remains valuable precisely because some questions require verified data and exact calculation rather than fluent speculation.
The story behind the first Siri steps is therefore not only about an old iPhone feature. It shows that a powerful assistant needs more than a conversational personality. It requires access to dependable tools, structured knowledge and the ability to recognize when another system should provide the answer.
Siri Wolfram Alpha offered that lesson in 2011, long before AI assistants became capable of writing essays, interpreting screens and acting across apps.
In our experiment, we deployed A.I. “agents” to act as office workers, and found that they were capable of performing some of the tasks we assigned, but not all of them.
Among a range of factors leading to a wave of tech sector layoffs in 2026 is the rapid rise of artificial intelligence and automation. Companies are reconfiguring their workforces to leverage AI for increased efficiency and reduced operating costs. This realignment and reduction is implemented even by companies reporting strong financial performance.
But it’s not just AI leading to workforce cuts. Complementing this technological shift are ongoing economic uncertainty, inflation, and higher interest rates, compounded by a chip shortage and rising energy costs. This mix is driving companies to cut costs and streamline operations for increased efficiency.
According to data compiled by Layoffs.fyi, an online tracker that keep tabs on job losses in the technology sector, 123,941 tech employees were laid off at 269 companies in 2025. The site also reports that 71,981 government employees were laid off by DOGE alone, with 182,528 total federal workers laid off.
Here is a list — to be updated regularly — of some of the most prominent technology layoffs the industry has experienced recently.
Notable tech layoffs in 2026
Monday.com
Microsoft
Meta
Cisco
Cloudflare
Oracle
Atlassian
Salesforce
Amazon
Ericsson
July 22, 2026: Monday.com cuts 20% of its workforce to restructure for the AI era
The company says the decision to cut 620 jobs isn’t about margins, but about creating a flatter organization built around AI agents, autonomous teams, and deeper customer engagement.
July 6, 2026: Microsoft cuts 4,800 jobs, primarily in sales and Xbox teams
As the company trims thousands of jobs, it’s also investing in embedded engineering teams and AI infrastructure. The layoffs come several weeks after the company offered 8,750 US employees voluntary retirement buyouts.
June 5, 2026: Tech industry cut 38,242 jobs in May, worst since 2024
AI was blamed for 40% of the job cuts in May, up from 7% in January, according to research by employment placement company Challenger, Gray & Christmas.
May 20, 2026: Meta cuts 8,000 jobs, around 10% of workforce
The cuts are expected to expected to hit Meta’s engineering and product teams the hardest, arriving as Meta pivots toward AI to boost efficiency across its organization, according to Yahoo Tech.
May 13, 2026: Cisco to cut nearly 4,000 jobs despite strong growth in AI, enterprise networking
Despite reporting positive financial news — including record third-quarter revenue of $15.8 billion, a 12% year-over-year increase — Cisco said it will eliminate almost 4,000 jobs.
May 7, 2026: Cloudflare to cut 1,100 jobs in AI-focused restructuring
April 1, 2026: Oracle to cut up to 30,000 jobs globally, putting enterprise support and roadmaps at risk
Oracle began laying off employees on March 31 in what could be the largest workforce reduction in the company’s history. Employees received termination emails at 6 a.m. local time with immediate system lockouts and no prior warning. (Note: in June, CNBC put the final layoff tally at 21,000.)
March 12, 2026: Atlassian cuts 1,600 jobs to fund AI and enterprise expansion
Atlassian will reduce its global workforce by approximately 10%, eliminating around 1,600 roles, as the collaboration software maker redirects capital toward artificial intelligence development and enterprise sales.
March 11, 2026: Tech layoffs surpass 45,000 in early 2026
January 15, 2026: Ericsson plans to shed 1,600 jobs in Sweden
Ericsson lans to cut some 1,600 jobs in Sweden, the telecommunications equipment maker said doubling down on recent cost-saving measures that have helped it weather a prolonged downturn in telecoms spending, Reuters reports.
January 13, 2026: Meta plans to cut around 10% of employees in Reality Labs business
Meta plans to cut around 10% of the employees in its Reality Labs division who work on products including the metaverse, according to three people with knowledge of the discussions, according to The New York Times.
Layoffs in 2025
Cisco
Oracle
Windsurf
Intel
Microsoft
Crowdstrike
HPE
Autodesk
HPE
CISA
Workday
Salesforce
Meta
Global tech-sector layoffs surpass 244,000 in 2025
August 18, 2025: Cisco and Oracle to cut hundreds of Bay Area jobs
Tech companies Cisco and Oracle are cutting hundreds of jobs across the Bay Area. Cisco will eliminate 221 positions at its Milpitas and San Francisco offices, effective Oct. 13. Oracle is reducing 101 positions in Santa Clara on the same date
August 5, 2025: 3 weeks after acquiring Windsurf, Cognition offers staff the exit door
Cognition, the AI coding startup that acquired rival company Windsurf three weeks ago, laid off 30 employees last week and is offering buyouts to the roughly 200 remaining employees on the team, reports The Information.
July 25, 2025, Intel to lay off 22% of workforce, CEO Tan signals ‘no more blank checks’
July 8, 2025, Intel layoffs begin: Chipmaker is cutting many thousands of jobs
Intel has begun laying off employees across the company. CEO Lip-Bu Tan told workers back in April to expect major layoffs at Intel in the coming months as the chipmaker slashes costs and overhauls its organization after years of technical setbacks and falling sales.
July 2, 2025: Microsoft will cut 9,000 workers
Microsoft will lay off about 9,000 employees, a source familiar with the workforce cut told CNBC. The cuts will reportedly affect less than 4% of Microsoft’s global workforce and will impact different teams, geographies and levels of experience. This is the latest in a string of cuts the tech giant has made this year.
June 17, 2025: Intel looks to factory layoffs to return to profitability
Intel will lay off up to 20% of its manufacturing sector employees starting in July, according to media reports, as the company looks for options as it seeks a return to profitability. The cuts reportedly will be made around the world, but some of the layoffs will be closer to home, according to a report in The Oregonian citing an internal company memo from Intel manufacturing Vice President Naga Chandrasekaran.
May 7, 2025: CrowdStrike to lay off 5% of staff
CrowdStrike announced a plan to cut about 500 roles, roughly 5% of its workforce, to streamline operations and reduce costs. The cybersecurity company will incur about $36 million to $53 million in charges related to the layoffs
March 6, 2025: HPE cuts 2,500 jobs, remains committed to Juniper buy
Feb. 27, 2025: Autodesk to lay off 9% of workforce
Software maker Autodesk is laying off 1,350 staff. With the rise of subscription and multi-year contracts billed annually, and self-service enablement, it finds it needs fewer sales staff, CEO Andrew Anagnost said in a message to employees. And with its cloud, platform, and AI products proving most profitable, it’s concentrating its staff and investments there.
Feb. 27, 2025: HP to lay off 2,000 more
As part of an ongoing restructuring, HP plans to lay off up to another 2,000 workers. In recent weeks, the company has tried — unsuccessfully — to do away with telephone support staff by forcing callers to wait for at least 15 minutes if they refuse to use self-service support resources online. The company swiftly backtracked, but wider job cuts are still on.
Government employees get laid off too: In this case, 130 workers at the US Cybersecurity and Infrastructure Security Agency are being shown the door as a result of a DOGE decision. Cybersecurity experts are concerned that the cuts will harm the international collaborations that CISA has fostered, quite apart from their concerns about the security of the DOGE layoff process itself.
As it moves to invest more in AI and international growth, Workday is laying off 8.5% of its workforce and disposing of unused office space. Some analysts fear the cutbacks will affect the company’s customer service — unless AI can pick up the slack.
Feb. 4, 2025: Salesforce lays off over 1,000
At the same time as it’s hiring sales staff for its new artificial intelligence products, Salesforce is laying off over 1,000 workers across the company, according to Bloomberg. As of June, 2024, the company had over 72,000 employees, according to its website. Salesforce did not comment on the report. In 2024 the company reportedly laid off around 1,000 staff too, in two waves: January and July.
Jan. 14, 2025: Meta will lay off 5% of workforce
Mark Zuckerberg told Meta employees he intended to “move out the low performers faster” in an internal memo reported by Bloomberg. The memo announced that the company will lay off 5% of its staff, or around 3,600 staff, beginning Feb. 10. The company had already reduced its headcount by 5% in 2024 through natural attrition, the memo said. Among those leaving the company will be staff previously responsible for fact checking of posts on its social media platforms in the US, as the company begins relying on its users to police content.
Despite intense demand for its data center capacity, Equinix is planning to lay off 3% of its workforce, or around 400 employees. The announcement followed the appointment of Adaire Fox-Martin to replace Charles Meyers as CEO and the departures of two other senior executives, CIO Milind Wagle and CISO Michael Montoya.
AMD will lay off around 1,000 employees as it pivots towards developing AI-focused chips, it said. The move came as a surprise to staff, as the company also reported strong quarterly earnings.
Enterprise software vendor Freshworks laid off around 660 staff, or around 13% of its headcount, despite reporting increased revenue and profits in its fourth fiscal quarter. The company described the layoffs as a realignment of its global workforce.
After laying off around 4,200 staff in February, Cisco is at it again, laying off another 6,000 or around 7% of its workforce. Among the divisions affected were its threat intelligence unit, Talos Security.
More than 1,000 software and services staff are on the way out at General Motors, signalling that it could be rethinking its digital transformation strategy. In an internal memo, the company said that it was moving resources to its highest-priority work and flattening hierarchies.
Intel plans to cut its workforce by around 15% to reduce costs after a disastrous second quarter. Revenue for the three months to June 29 stagnated at around $12.8 billion, but net income fell 85% to $83 million, prompting CEO Pat Gelsinger to bring forward a company-wide meeting in order to announce that 15,000 staff would lose their jobs. “This is an incredibly hard day for Intel as we are making some of the most consequential changes in our company’s history,” Gelsinger wrote in an email to staff, continuing: “Our revenues have not grown as expected — and we’ve yet to fully benefit from powerful trends, like AI. Our costs are too high, our margins are too low. We need bolder actions to address both — particularly given our financial results and outlook for the second half of 2024, which is tougher than previously expected.”
OpenText said it will lay off 1,200 staff, or about 1.7% of its workforce, in a bid to save around $100 million annually. It plans to hire new sales and engineering staff in other areas in 2025, it said.
Microsoft laid off staff in several teams supporting its cloud services, including Azure for Operations and Mission Engineering. The company didn’t say exactly how many staff were leaving.
Amazon announced hundreds of layoffs in the sales and marketing teams of its AWS cloud services division — and also in the technology development teams for its physical retail stores, as it stepped back from efforts to generalize the “Just Walk Out” technology built for its Amazon Fresh grocery stores.
Dell Technologies’ latest 10K filing with the US Securities and Exchange Commission disclosed that the company had laid off 13,000 employees over the course of the 2023 fiscal year; it characterized the layoffs and other reorganizational moves as cost-cutting measures. “These actions resulted in a reduction in our overall headcount,” the company said. A comparison to the previous year’s 10K filing, performed by The Register, found that Dell employed 133,000 people at that point, compared to 120,000 as of February 2024. Dell announced layoffs of 6,650 staffers on Feb. 6, but it is unclear whether those cuts were reflected in the numbers from this year’s 10K statement.
Jobs involving physical labor are at high risk of disruption from automation, with new technologies such as AI robots becoming more prevalent, according to a recent study by the Organization for Economic Co-operation and Development (OECD). That means workers in construction and extraction, farming, fishing, forestry, production and material transportation could be affected by fast-moving technology changes.
“Routine and low-skilled jobs are at higher risk,” the Paris-based public policy group said, adding that “overall, jobs requiring non-routine cognitive, social and creative skills are less susceptible to automation.”
The kinds of creative and cognitive jobs still thought to be less exposed to automation include social work and community service roles.
OECD also said management jobs — which often require workers to devise creative answers to solve problems — fall within the creative and cognitive category. “While AI has made some high-skill job requirements more susceptible to automation, many critical skills in these roles remain difficult to automate,” OECD said.
The same still holds true for some physical and manual labor jobs – including cleaners, agricultural workers, food-prep assistants, and laborers — which are less exposed to the affects of AI, OECD said.
But people who work in programming, translating and interpretation positions could find their work affected by the quick rise of AI tools and services. According to the organization, global AI uptake rose from 7% in 2021 to 20% in 2025.
“In these occupations, GenAI could perform a significant share of tasks at least twice as fast today or in the near future,” OECD said.
The effects of the AI boom are not always uniform across industries or regions. In a separate 2026 Employment Outlook study released by the group, exposure to disruption from generative AI (genAI) ranges from about 16% in some areas to more than 70% elsewhere, depending on industries and occupations.
AI technology has become so ubiquitous that it’s been compared to electricity — virtually all companies will need it or at least know how to use it. But it’s adoption has been hindered at times as companies struggle to find ROI from its use, and by regulatory and ethical hurdles.
In the US, AI blamed for June job losses
According to a Challenger, Gray & Christmas study released earlier this month, AI was cited as the top reason for job cuts in June. The outplacement firm said employers cut 45,849 job cuts in June, of which 14,029 were attributed to AI, with the tech industry leading the cuts.
“Tech remains the epicenter of this year’s cuts,” Challenger said. “AI is the dominant force as companies are restructuring around it, automating roles, and reallocating budgets toward new capabilities. The sector is being reshaped in real time.”
Overall, AI has been responsible for 173,568 job cuts since 2021, the company said.
AI is hurting jobs in customer service, internal reporting, telecommunications, and hosting automation, said Victor Janulaitis, a staffing consultant who was formerly CEO at Janco Associates Inc.
“C-level executives continue to be focused on eliminating ‘non-essential’ managers, staff, and services,” he said. “Coders and developers have limited opportunities with legacy applications.”
While jobs in the IT sector overall are declining, current hiring tends to skew in the direction of people with AI skills. A report this month by CompTIA put job listings with AI skills at around 500,000, which is close to double the number in January.
“Employers in other industries are accelerating digital transformation initiatives and moving from AI experimentation to implementation,” said Seth Robinson, CompTIA’s vice president for industry research.
That view dovetails with what ManpowerGroup, the recruitment firm, is seeing; demand for AI-related skills has nearly doubled over the past year, said Ger Doyle, regional president of North America at ManpowerGroup.
That growth extends well beyond traditional technology roles as companies move from experimenting to AI deployments at scale, Doyle said. “We’re seeing it influence hiring across occupations ranging from data science and engineering to project management and operational roles,” he said.
The open-plan floors make it hard to concentrate. The building is so large that getting from one meeting to the next eats real time out of the day. It’s common for people to run meetings with colleagues over Webex — colleagues on the same campus, sometimes no more than two hundred yards away.
Ironically, Apple Park replaced a campus that did far better on the same measure without ever trying to. Infinite Loop produced far more of the accidental, cross-team contact Apple Park was explicitly built to create. Working out why starts with what Infinite Loop got right by accident. It continues with what the research on office proximity says about why that kind of thing happens at all. And it ends with what Apple Park could become instead — including a version of the fix Apple already trusts enough to run for a hundred people a year.
[…]
There’s no obvious focal point for the whole site — most sections have their own sitting area and their own coffee bar, but nothing plays the role Caffè Macs and the IL1 coffee bar played together at Infinite Loop. Caffè Macs at Apple Park seats a thousand people and feels built for throughput, not conversation. Everything is organised per-segment rather than around a shared centre, which is convenient for the people in that segment and useless for the discovery-by-accident that made the old campus work.
[…]
By multiple accounts from people who were there during design and construction, the site was flagged as under-provisioned for meetings and conferences before it even opened.
Apple Park is a beautiful structure, but is not terribly conducive to focused or collaborative work. Even as an occasional visitor I found it overwhelming. Employees sit shoulder to shoulder, voices bounce off and bleed through glass walls, and privacy is a virtual impossibility. My friends and colleagues who worked there regularly found it difficult to be productive.
I worked in Infinite Loop (Building 3, 2nd floor) for thirteen years (right below Developer Publications, where Malcolm spent a good portion of his Apple career). I loved IL because its design made serendipitous encounters easy. Whether it was sitting outside Caffè Macs or in the IL 1 Atrium, I would inevitably bump into someone and have a conversation that furthered an in-flight project, sparked something new, or simply reinforced the social ties that bind colleagues.
It helped that at that time, Apple had perhaps 10,000 employees, most of whom were in or near IL. After iPhone came about and IL started getting locked down, much of the natural collaboration dissipated, disappearing behind badged doors and disclosures.
IL provided a place to focus on your work[1], as well as seating spaces that are out of the flow of traffic where you can have an informal meeting[2]. At AP, every collaborative space is effectively in the middle of a hallway. That turns out to be enormously distracting, both to you and to those people trying to work in the glass bullpen right next to it.
[1] before all cubicles and offices became multi-person shared spaces
[2] before all those spaces were filled in with more offices
“The IL1 atrium really was the crossroads of the company in those days” I really don’t think that this is true literally by any means. Assuming “those days” overlap with the time I’ve been there (pre Park). The XFs in IL have been extremely scarce.
IL was way too small and overloaded, I’d actually say it was very similar to Apple Park. No one really wanted to work there in those tiny offices with multiple people 🤷♀️
I loved the IL1 atrium. I’d sit there and hope that someone like MMalc would wander by, and they often did. It was a real destination for field people who didn’t get to visit the mothership very often. I miss that. AP had nothing like it.
I think of my days in college—most dorms residence halls were not air conditioned, so at the end of August, you had to open your window (often to place a box fan) and door to create some airflow. People walking through the building would meet by chance. Newer buildings tended to be less lively and more like a hotel—all the doors closed and rarely much activity. Through renovations, most of the buildings have had air conditioning added, dropping those interactions over the years.
As you may know, the Lumon Industries building that Mark, Helly, Irving, and Dylan work in is a former Bell Labs facility in Holmdel, New Jersey. I first learned about the building several years ago, when I read Jon Gertner’s excellent history of The Labs, The Idea Factory. It’s a distinctive place designed by Eero Saarinen in the early 60s.
Bell Labs was known for the fruitful collaboration of its researchers, often started through chance meetings in the hallways of other Bell Labs facilities. The new Holmdel building was supposed to further that sort of teamwork, but things didn’t work out as planned.
I worked in IL1 for over a decade. The day I saw the open-plan spaceship, I knew I would never set foot inside. There are more rewarding ways to work in a barn.
Desde que a Apple levou a OpenAI aos tribunais por uma suposta violação de segredos industriais e propriedade intelectual, a ausência do nome de Jony Ive no processo tem sido motivo de especulações, considerando que o ex-executivo da Maçã e braço direito de Steve Jobs é uma peça relevante para o desenvolvimento de hardwares da dona do ChatGPT.
No ano passado, a startup de Ive, a io Products, foi adquirida pela OpenAI por US$6,5 bilhões. Desde então, o estúdio de design independente LoveFrom (também comandado pelo ex-Apple) passou a ser o espaço da gigante de inteligência artificial (IA) para a supervisão do design da sua linha de hardware. Nesse processo, mais de 400 funcionários trocaram a Maçã pela empresa de Sam Altman — entre eles, Tang Tan e Chang Liu, acusados de instruírem a revelação de protótipos da Maçã para quem estivesse em entrevista com a empresa de IA.
Para Mark Gurman, jornalista da Bloomberg, existem duas explicações lógicas para Ive ter ficado de fora das acusações: a ausência de provas que comprovem seu vínculo com o esquema e a sua relação de proximidade com a viúva de Jobs, Laurene Powell Jobs.
Próxima de Tim Cook e de outros executivos da empresa — além de manter uma relação de longa data com Ive —, ela continua circulando com naturalidade entre ambos os lados, tendo inclusive participado da última WWDC como convidada.
Laurene também é uma das principais investidoras dos projetos de Ive e esteve ao lado dele e de Altman quando os dois revelaram que o primeiro dispositivo de IA da OpenAI já estava em desenvolvimento. Para Gurman, esse conjunto de relações pode ter contribuído para evitar que o nome do ex-chefe de design da Apple fosse envolvido diretamente na disputa judicial, especialmente na ausência de evidências que o ligassem ao suposto vazamento de informações.
If you're a skilled writer with outsize technology chops who gets excited by the idea of taking the Ars audience with you as you go hands-on with hardware—all kinds of hardware!—then this position has your name all over it. Plus, you get to have me as your boss, and how could that be anything other than awesome?!
The job
The formal job description and application is right here and has all the specifics and HR stuff, including salary range. The short summary is that we're looking for an experienced writer (where "experience" means "several years of professional work"), who is a technologist first and foremost. We want people who tinker around with tech because they can't not tinker around with tech; that kind of joy tends to leak out into the work, and it's impossible to fake.
Some specifics on the subject matter the job will cover, copied from the job description:
Enterprises that use AI in hiring and firing decisions continue to be under scrutiny, and this time it’s Meta under the microscope.
A legal complaint filed on July 13 in a US District Court in California alleges that Meta used AI systems that unfairly and illegally selected workers for termination while they were out on protected leave.
More than two dozen anonymous plaintiffs are seeking a preliminary injunction that would prevent the company from finalizing their separations or altering their compensation, benefits, or protected leave status.
Meta has countered that the claims lack merit and that its workforce decisions were, and continue to be, made by people, not AI.
An important lesson
These allegations should serve as an important lesson to other businesses using AI in their HR decision-making, analysts note.
“Enterprises must begin by rejecting the convenient assumption that AI improves workforce decisions simply by touching them,” said Sanchit Vir Gogia, chief analyst at Greyhound Research.
There is “scant independent proof” that AI makes layoff choices more accurate or more lawful, he said. “It makes them faster, and faster has never been shown to be fairer.”
The claims against Meta
The complaint states that, on May 20, 2026, Meta began notifying roughly 10% of its workforce (around 8,000 employees) that they had been selected for termination. The company also announced that several thousand more would be reassigned to new AI initiatives. But this came even as Meta reported record revenues in Q1 2026 ($56.31 billion, a 33% year-over-year increase), and pledged to spend upwards of $100 billion on AI this year.
In addition to questioning the need for staff cuts, the filing alleges that Meta used a “constellation” of internal AI systems to score, rank, and select employees for termination. These tools included Meta’s internal AI coworker, “Metamate,” employee-trained “second-brain” agents that replicated their output, algorithms tracking keystrokes and other digital activity, and AI token usage dashboards.
“Meta did not assemble the termination list through the considered judgment of managers who knew the work,” the complaint claims.
The 26 plaintiffs, all current or former employees, requested, took, or were approved for “statutorily protected” leave within 24 months of the workforce reduction, and claim they were “disproportionately selected” for layoff based on scoring that essentially penalized them for exercising their legal right to take leave.
These practices are prohibited by federal and state law; The US Family and Medical Leave Act, for one, prohibits the use of protected leave as a “negative factor” in employment decisions. Further, the plaintiffs allege that Meta violated the US Worker Adjustment and Retraining Notification (WARN) Act that requires employers with 100 or more employees to provide written notice 60 calendar days in advance of mass layoffs.
This notice gives employees reasonable time to seek alternate employment; however, the complaint argues, an employee undergoing “significant medical treatment” or providing “around the clock care” for a “weeks old newborn” or other loved ones “cannot also be told that during this exact same time period they must look for new work.”
In one scenario, according to the filing, a scientist was identified for termination just two days before she gave birth while on pregnancy leave. In another, an engineer’s manager tied his performance rating to “broken time” when an injury prevented him from working. In a third, a researcher was called out after requesting time off following a medical diagnosis.
The plaintiffs are seeking a preliminary injunction pending an independent audit of the “algorithmically assisted selection process” and “resolution of the merits of their claims” in arbitration.
Once terminations are finalized, the harm to plaintiffs “cannot be undone by money damages alone,” the complaint states. For employees out on leave, “every day that goes by constitutes additional harm, in that Meta is taking away the entire purpose of a protected leave.”
Considerations for enterprises
Any system that materially influences who keeps a job is not an HR tool, Gogia noted. “It is high-risk enterprise infrastructure.”
An “AI-determined” process delegates the outcome to the system, while an “AI-assisted” one gives the system the ability to rank, recommend, and summarize, with a human formally making the final decision. Exposure arises in either model, Gogia pointed out, because the output has often been compressed and eliminates detail by the time of executive approval.
There must be one non-negotiable role in the process, Gogia said: A single executive with the authority to halt the process, suspend the model, and delay decisions when evidence does not hold. This person should be “a meaningful reviewer [who] understands the model’s limits, knows the actual work, and holds the authority to challenge the recommendation, with every override visible and reviewable,” he said. At the same time, the objective is to “govern the machine and the manager together,” since human judgement brings its own “risks, favoritism, and proximity” bias.
Gogia advised enterprises to retain fixed memory for auditing, determine who chose the auditor, what was excluded, and whether the result can be reproduced. They should also inventory every source feeding the model and its origins, and run adverse-impact analysis before making any firing decisions.
Leave details must never be identified as inactivity or weak adoption; a protected absence is not ordinary missing data, and the system has to be informed of this. Rather, these circumstances belong in an “independent review lane,” where human reviewers get enough context to “neutralize” the period without receiving specific leave details, Gogia said.
He pointed to another important question: What should the “second brain” AI agent that ingested the employee’s communications and documents to replicate the employee’s output be allowed to do when humans are away, and who owns that output?
Ultimately, said Gogia, “the safest position is not to ban AI from workforce planning. Used with discipline, it can expose duplicated work and inconsistent assessment, and it can challenge human bias rather than automate it.”
How employees can protect their rights
Employees, for their part, need a genuine window in which to challenge inaccurate data before separation becomes “irreversible,” and they should “fight the record, not the algorithm,” Gogia advised.
That means that, while the model cannot explain itself, documented evidence can. Employees should lawfully retain their own reviews, leave approvals, and severance documents, and build a chronology of events: When leave was requested, when performance language changed, when new metrics appeared, Gogia said.
Impacted workers should ask in writing which criteria were used in the decision, whether automated systems materially influenced it, how protected leave was treated, and what information about them influenced the result and how that information was verified.
Further, it’s important to take note of deadlines; the federal discrimination window is typically six months, although that is extended to 10 in many places, and internal processes are “not obliged to respect it,” said Gogia.
His ultimate advice for workers: “Preserve the lawful record, and protect the deadline.”
The best time for tech workers to unionize was 20 years ago, when they had plenty of leverage. The second-best time is now, when they don’t.
Mass layoffs, AI-driven displacement, corporate surveillance, workplace disillusionment have created conditions that have made organizing compelling for tech professionals. But the federal labor board that has historically protected workers’ right to organize has been weakened, and the companies that once feared it are openly defying it.
Here’s how organizers and labor experts describe the pros and cons to organizing — and how you can get started.
The single biggest benefit of a union contract for most tech workers isn’t pay — it’s protection against arbitrary termination, especially in the wake of recent mass layoffs in tech. In the United States, nonunion “at-will” workers can be fired at any time without a stated reason, while unionized workers negotiate protections written into their contracts.
“That fear of the company letting you go for anything at any time…with a union they just can’t do that,” says Zak Thompson, a senior software engineer at Kickstarter and union steward at Kickstarter United. Now that Kickstarter employees are unionized, people are less worried that saying something negative will result in termination.
“I’ve been shocked at the willingness of my co-workers to speak up against what they see as poor or controversial business decisions,” Thompson says.
Beyond job security, unions can deliver concrete material gains.Kickstarter United was formed in 2020, although getting there wasn’t easy: two employees were fired during the organizing campaign — which itself became a galvanizing event. And while the union hasn’t been able to prevent layoffs, it did negotiate better terms: four months of severance pay and four to six months of continued health insurance, versus the two to three weeks per year of work that management had initially proposed.
Other benefits include a four-day work week; AI protections; a minimum pay floor; and standards for raises, promotions, and time off for the company’s 59 employees.
Unions can give tech workers a voice in decisions that affect their daily work — including how AI tools are deployed. “Nobody I’ve spoken to is against new technology or getting trained in it,” says Max Belasco, a business systems analyst at the University of California Los Angeles School of Law and co-chair of the UCLA chapter of the University Professional and Technical Employees/Communications Workers of America (UPTE-CWA) Local 9119.
“But when new technology is being implemented, we want to know: what’s the five-year vision, the 10-year vision? Are we implementing this in a way that betters staffing, increases efficiency, or eases the lives of people already working? Or are we trying to take away jobs, automate people out of their pension or paycheck?” Belasco says.
The challenges are real. Tech professionals are less inclined to leave their jobs in the current market because wages haven’t been increasing as fast as they once were, and it can take longer to land another job.
“Tech moved from a very tight labor market in 2022 (1.85% unemployment rate) to a noticeably weaker one in 2024–2026 (3.49%),” although that’s still better than the national unemployment rate of 4.36% through May of this year, says Liya Palagashvili, senior research fellow and director of the Labor Policy Project at the Mercatus Center at George Mason University.
Liya Palagashvili of the Mercatus Center at George Mason University
Mercatus Center at George Mason University
Flexibility is a concern. The more substantive challenge, raised by economists including Palagashvili, is that traditional union contracts impose uniform terms across an entire bargaining unit, limiting the flexibility that many tech workers — and their employers —currently enjoy. Tech firms need to move fast, adjusting teams, products, and roles on the fly.
“Collective bargaining agreements can make those adjustments much more difficult, whether by making them slower, costlier, or inconsistent with the contract,” she says.
Workers skeptical of unions in a survey of 1,900 tech professionals conducted by the career site Blind cited specific concerns: that unions are “not meritocratic,” “prevent innovation,” and “hold back earnings of top performers.”
Thompson from Kickstarter United pushes back: “We have nothing in our contract about ‘you can’t bend down and pick up a piece of trash because that’s someone else’s job.’ The company is free to give bonuses and individual raises as much as they like. This is all just up to the people who are bargaining the contract from the union side.”
Organizing carries potentially serious personal risks. During negotiations for a second three-year contract in 2025, Kickstarter United went on strike for 42 days. A few months later, the company announced layoffs.
“They let go strong union leaders, including a person who had bargained our last contract,” Thompson says. The union appealed, and the issue is now going to arbitration.
If you form a union, don’t expect much support from the National Labor Relations Board, the agency that certifies US labor unions and protects workers’ right to organize, in terms of prosecuting complaints of unfair labor practices, Thompson warns. “We’re in a political moment in this country with a pretty weakened NLRB. You have to be ready to organize and withhold worker power without any guarantee of safety.”
Organizers are up against an enormous union avoidance industry. Organizers can expect fierce pushback as soon as the business discovers that organizing is underway.
“There’s a multi-billion-dollar industry in union avoidance,” says Alan McAvinney, a Google software engineer and organizing chair, Alphabet Workers Union-CWA, a 1,400-member minority union of Alphabet employees. (Google is a subsidiary of Alphabet.)
US employers spend roughly $1.7 billion a year on union avoidance consultants and law firms, according to a May 2026 report by the Economic Policy Institute and LaborLab.
Expect hardball tactics. Management may play hardball during the time between when organizers announce their intention to unionize and the actual vote. For example, management can threaten to fire foreign-born workers in the US on H-1B visas if they support the union. Those workers would then have just 60 days to find a new sponsoring employer or lose their H-1B status, according to a recent Tech Workers Coalition blog post.
And at venture capital-backed startups, investment agreements sometimes require management to attest there is no union activity — meaning a public organizing drive can trigger funding withdrawal. Or, if a unionized company is acquired, the new management can dissolve the union overnight by reclassifying unionized workers as new hires.
With these sobering facts in mind, here is how organizers who have done it describe the process of creating a union.
Step 1: Start a conversation with your co-workers
At the University of California, a two-tier system had evolved where some tech workers were unionized and some weren’t, Belasco says. Management created new titles that fell outside the union even though they had similar job descriptions and responsibilities to those in the union. Those nonunion employees received lower pay and benefits than their unionized peers, which created resentment and instability.
Belasco and other organizers wanted to eliminate that division by bringing everyone under the same contract. But when they began their unionization drive, “the biggest barrier we faced wasn’t management opposition — it was that people felt this was just the best-case scenario realistically available: ‘We have this job at the university, we have concerns about automation and layoffs, but what can we really do about it?'” he says.
The antidote to that fatalism, organizers say, is simple: “Just start talking to your immediate co-workers. Are they experiencing the same challenges you are experiencing?” says McAvinney. “There’s no need to start talking about a union at this point.”
Just get a consensus and start building a group of like-minded individuals, Thompson advises. “Always start with one-on-one conversations, and that’s what you should do the whole time. That’s the key to organizing,” he says.
Tech workers often think they’re a special case, says Thompson, and therefore that unionization isn’t a good fit. “You’re not special. You are a company of workers, you are organizing, and there is a playbook for that. Trust the process, because it tends to work pretty well,” he says.
Step 2: Who’s on board, and who’s not? Map your workplace, but keep it quiet
Once there’s a consensus, continue to grow your network. Keep a list of everyone you’ve spoken with and note their disposition: “Is this person union-friendly or anti-union? Would they be a strong organizer?” Thompson says.
Maintaining secrecy early on is essential, because anti-union tactics will start immediately, and that can stop union organizing before it can gain momentum.
“Generally, employers do not want to share power with their workforce,” McAvinney says. Employers will deploy every means at their disposal to stop organizing efforts and peel away potential yes votes.
“If you look at historical examples, having 70% approval before the employer finds out about you results in a high percentage of wins when you actually cast the vote. Historically, that’s an effective buffer,” he says.
There’s a real threat of firing and layoffs. The traditional tech worker belief that job mobility makes collective action unnecessary is now being tested by a tighter job market, McAvinney says, noting that workers who many believe were fired for speaking out back in 2019 were a galvanizing factor in his union’s formation.
“You generally don’t want to be in a situation where the employer feels comfortable firing everyone. Part of that is thinking from a cynical standpoint about what the consequences would be to the employer if they did fire everyone,” he says.
One-on-one conversations that include personally asking co-workers to keep conversations confidential are key to keeping things quiet, Belasco says. When 2,100 UC tech workers voted to unionize in May, 96% voted in favor. To stay out of earshot of managers, avoid employee surveillance tools, and sidestep conference calls that could be recorded, organizers met with workers in their homes.
“That tactic is probably what made the difference between winning the election and getting the majority we got,” he says.
Step 3: Find the right union affiliation or go it alone
“Running a campaign against major employers requires the resources and expertise of the larger labor movement, even if workers publicly present as independent,” says Kate Bronfenbrenner, director of labor education research and senior lecturer emeritus at Cornell University’s School of Industrial and Labor Relations.
The Alphabet Workers Union decided early on to affiliate with CWA. “They gave us a bunch of support early on in our campaign with no strings attached,” McAvinney says.
Kickstarter is organized through OPEIU, Thompson says. “They’ll usually have resources and staff that can help you through the next steps: collecting signatures in support of a union, bringing that to management, holding a vote — the more formalized things that interact with US labor law. They’ll also help with organizing along the way,” he says.
For workers at institutions where a union already exists, there may be a faster path. Organizers at UCLA did what’s called a “unit modification,” aligning with UPTE. By organizing under UPTE, the workers didn’t have to negotiate a new contract from scratch — they joined an already-negotiated contract covering existing UPTE tech members, which put them in “a much stronger position” than starting fresh, Belasco says.
Step 4: Choose your union model: majority vs. pre-majority or minority
Assess what’s practical for your organizing effort. In a majority union, more than 50% of all workers in a defined bargaining unit must vote to join the union through an NLRB-supervised election in the private sector, or a Public Employment Relations Board (PERB)-supervised election for public sector workers.
The NLRB must certify the union, which then operates under its legal protections. This means, for example, that the employer must bargain, negotiated contracts are enforceable, violations must go to the NLRB or arbitration, and workers can’t be dismissed without just cause.
A pre-majority or minority union is a minority labor organization operating without NLRB protections or collective bargaining agreements. “Pre-majority means that workers are able to demonstrate majority support — through signed cards, petitions, a walkout, or everyone wearing solidarity T-shirts — without going through a formal election,” Bronfenbrenner says.
Kate Bronfenbrenner from the School of Industrial and Labor Relations, Cornell University
ILR School/Cornell University
The Alphabet Workers Union-CWA (AWU-CWA) formed as a pre-majority union because achieving majority status across a globally distributed workforce of over 100,000 was not a realistic near-term goal. “An underground model where you try to reach 70% support across a workforce of over 100,000 people isn’t realistic,” McAvinney says.
A pre-majority union can still make a difference, he says. For example, the Alphabet Workers Union-CWA convinced management to offer voluntary exit packages — buyouts — prior to announcing layoffs.
For smaller organizations, a majority union may be the more practical option — it’s more attainable, McAvinney says. “I don’t think [the pre-majority union model] is the correct thing to do in all situations. I certainly would not recommend it to a 200-person shop.”
Kickstarter, which had fewer than 100 employees, was able to form a majority union, with 55% voting to organize.
Ultimately, says McAvinney, “there’s no inflection point where you go from being able to win nothing to winning everything, even with a contract and a supermajority. But the more people you have who are willing and able to fight for what they want, the more you’ll be able to get.”
Step 5: Who should — and should not — be in your union?
Belasco’s situation at UCLA illustrates a broader strategic choice that every organizing campaign must make. He had been in a union position in educational technology when he was told his role would be reclassified as a non-union position.
“I was given a choice: apply to the new non-union position to continue doing the work I’d trained for, or stay in my union position doing service desk work I wasn’t used to,” he says. “Essentially, it was a choice between job security and career progression.”
Belasco joined a “wall-to-wall” union, which represents a broad range of university professional and technical employees across the UC system rather than a single job category, such as engineers or tech professionals.
Kickstarter United is another example of a wall-to-wall union. “It’s not just the engineers who are unionized, but also customer support, designers — everyone,” Thompson says.
Wall-to-wall unions are more powerful, but they’re also more difficult to achieve. Under US labor law, “professionals have to vote separately on whether they want to be combined with other workers,” says Bronfenbrenner. “You can never have a wall-to-wall unit without giving professionals the chance to decide whether they want to be separate.”
The law’s “professional employees” category includes roles like software engineers and developers but not necessarily others. For example, customer support specialists and QA analysts would fall into the “non-professional workers” category.
“For decades, the pattern was either to organize everybody except the engineers, or manage to organize the engineers and fail to bring in everybody else — neither of which builds real worker power,” says Simone Robutti, an organizer with Tech Workers Coalition Global, an international branch of TWC based in Berlin.
Step 6: You won the vote. Get ready for what comes next
Winning a union vote means having a seat at the table, says Thompson. “Once the workers have come together and agreed they want that seat, you bring that to management, and they have a chance to voluntarily recognize a union,” he says.
But in most cases employers contest the results, which must be certified by the NLRB or PERB. That process, in which the employer uses various tactics to challenge the legitimacy of the outcome, can take weeks or months.
In the meantime, some companies may disregard negotiated contracts, which can lead to lengthy legal appeals or extended arbitration.
“The NLRB can still force an election, but it can’t force a contract, and companies are saying they simply won’t comply,” Bronfenbrenner says. This is where the expertise and resources of affiliation with a major union can help, she adds.
As a result, contract negotiations can take far longer than workers might expect. At Kickstarter, for example, two years and four months elapsed from the time of the union vote to the first contract, and that was at a 59-person company with a relatively cooperative employer. At larger companies with more aggressive legal teams, the timeline will be longer.
Forming a union is hard work, Robutti says. “It’s not a service you pay for and they protect you. It doesn’t happen spontaneously, and it doesn’t happen magically. It’s the choice to take responsibility for improving your workplace.”
The net zero economy is booming, so claims that prosperity depends on oil and gas are bunkum – unless you’re a Reform backer with fossil fuel interests, of course
Really? You want to destroy a million jobs? Vote Reform UK for mass unemployment: is that your pitch? Hammer these questions home whenever you meet a supporter of the party. Or, for that matter, a Conservative, as their party now takes an almost identical line.
The figures are stark. They were compiled not by Just Stop Oil or the Green party, but by that bastion of conservatism, the Confederation of British Industry. They show that the net zero economy now directly employs more than 300,000 full-time workers, while supporting the jobs of 1.1 million. The net zero sector is worth £100bn to the UK already, and is likely to grow by hundreds of billions more. The rest of the green economy directly employs a further 600,000.
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