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Perplexity CEO told Joe Rogan that Microsoft created office work. The dates say otherwise. To be fair to him, half of it is true. Gates really did want a PC on every desk, and Microsoft did make Word and Excel the default tools that almost every office job trains...

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Alex Prompter

279,043 subscribers

31,371 次观看 • 1 个月前 •via X (Twitter)

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Microsoft invented the knowledge worker to sell more office software. That's not a conspiracy theory. That's what happened. Bill Gates vision was simple: put a PC on every desk. Not to make computing beautiful (that was Steve Jobs). Just to sell more software. Word. Excel. Email. People went to tutorials to learn these tools. Then companies made them the price of admission for employment. The entire concept of an office career was a sales strategy. Now AI is replacing the very work Microsoft created. And maybe that's not a bad thing. Because sitting in a cubicle using Excel was never how humans were supposed to find purpose. The most curious people have the most fulfilling lives. Not the richest. Not the smartest. The whole knowledge economy was built to sell software. What happens when the software sells itself?
2:19

Microsoft invented the knowledge worker to sell more office software. That's not a conspiracy theory. That's what happened. Bill Gates vision was simple: put a PC on every desk. Not to make computing beautiful (that was Steve Jobs). Just to sell more software. Word. Excel. Email. People went to tutorials to learn these tools. Then companies made them the price of admission for employment. The entire concept of an office career was a sales strategy. Now AI is replacing the very work Microsoft created. And maybe that's not a bad thing. Because sitting in a cubicle using Excel was never how humans were supposed to find purpose. The most curious people have the most fulfilling lives. Not the richest. Not the smartest. The whole knowledge economy was built to sell software. What happens when the software sells itself?

Shruti

12,976 次观看 • 1 个月前

Balaji Srinivasan on taking the L to set up for the W: "Before Satya Nadella took over Microsoft, it was losing on mobile to iOS and Android." "He took the L... and he said, 'You know what? Linux is there. Linux is not going to go away.'" "We're going to run Linux on Microsoft hardware." "Mobile is not going away and nobody's installing the Microsoft mobile OS." "So we're going to allow Word and PowerPoint and Excel to run on iOS and Android devices." "And... the browser isn't going away. So we're going to make Office 365 work in the cloud." "Because he took the L, Satya set Microsoft up for the W." Balaji with Peter McCormack 🏴‍☠️🇬🇧🇮🇪
1:10

Balaji Srinivasan on taking the L to set up for the W: "Before Satya Nadella took over Microsoft, it was losing on mobile to iOS and Android." "He took the L... and he said, 'You know what? Linux is there. Linux is not going to go away.'" "We're going to run Linux on Microsoft hardware." "Mobile is not going away and nobody's installing the Microsoft mobile OS." "So we're going to allow Word and PowerPoint and Excel to run on iOS and Android devices." "And... the browser isn't going away. So we're going to make Office 365 work in the cloud." "Because he took the L, Satya set Microsoft up for the W." Balaji with Peter McCormack 🏴‍☠️🇬🇧🇮🇪

a16z

152,169 次观看 • 5 个月前

holy shit! this is INSANE… Microsoft just launched copilot cowork. built with Anthropic. you describe what you want done. it turns your request into a plan and executes it across outlook, teams, excel. 90% of the fortune 500 already use copilot or Microsoft tools. now it does the work for you. the execution era is here and only accelerating.
1:47

holy shit! this is INSANE… Microsoft just launched copilot cowork. built with Anthropic. you describe what you want done. it turns your request into a plan and executes it across outlook, teams, excel. 90% of the fortune 500 already use copilot or Microsoft tools. now it does the work for you. the execution era is here and only accelerating.

Damian Player

166,920 次观看 • 5 个月前

MICROSOFT JUST OPEN SOURCED THE ENTIRE AGENT RUNTIME, SO YOU NEVER HAVE TO BUILD ONE AGAIN a raw model only writes text. to make it a real agent it needs a loop, tools, memory, planning, approvals, and a way to know when it is done. Microsoft's Agent Harness is that whole layer, and it ships with everything on by default. you bring the model and the tools, it wires up the rest: > an automatic tool calling loop with iteration limits > history saved after every call, so a crash resumes instead of starting over > context compaction that summarizes when the window fills > a persistent todo list plus plan and execute modes > file memory that survives across turns > tool approval with standing rules and auto approval > OpenTelemetry tracing and web search built in > Agent Skills that load domain expertise on demand the mental model is simple: the model is the brain, the harness is the body around it. and it works with whatever you already run: > Azure OpenAI, OpenAI, Anthropic, and GitHub Copilot, and it hosts on Microsoft Foundry you spin one up in a single line: agent = create_harness_agent(client, name, instructions) open source, Python, .NET, and Go, stable since mid 2026. bookmark this. Microsoft already built the hard part of every AI agent, you just plug in the model.
0:23

MICROSOFT JUST OPEN SOURCED THE ENTIRE AGENT RUNTIME, SO YOU NEVER HAVE TO BUILD ONE AGAIN a raw model only writes text. to make it a real agent it needs a loop, tools, memory, planning, approvals, and a way to know when it is done. Microsoft's Agent Harness is that whole layer, and it ships with everything on by default. you bring the model and the tools, it wires up the rest: > an automatic tool calling loop with iteration limits > history saved after every call, so a crash resumes instead of starting over > context compaction that summarizes when the window fills > a persistent todo list plus plan and execute modes > file memory that survives across turns > tool approval with standing rules and auto approval > OpenTelemetry tracing and web search built in > Agent Skills that load domain expertise on demand the mental model is simple: the model is the brain, the harness is the body around it. and it works with whatever you already run: > Azure OpenAI, OpenAI, Anthropic, and GitHub Copilot, and it hosts on Microsoft Foundry you spin one up in a single line: agent = create_harness_agent(client, name, instructions) open source, Python, .NET, and Go, stable since mid 2026. bookmark this. Microsoft already built the hard part of every AI agent, you just plug in the model.

NO1ennn

68,276 次观看 • 17 天前

Matt Mullenweg told us the best acquisition his company ever made. He'd been studying Microsoft. For every $1 Microsoft made on Windows, the ecosystem around it made about $20. He wanted the app that sat on top of WordPress the way Office sat on top of Windows. He found it in a 40-person company in South Africa with 4 engineers. It was called woocommerce. They beat out a private equity firm to buy it. Last year over $30b in goods and services sold through it.
1:45

Matt Mullenweg told us the best acquisition his company ever made. He'd been studying Microsoft. For every $1 Microsoft made on Windows, the ecosystem around it made about $20. He wanted the app that sat on top of WordPress the way Office sat on top of Windows. He found it in a 40-person company in South Africa with 4 engineers. It was called woocommerce. They beat out a private equity firm to buy it. Last year over $30b in goods and services sold through it.

Sam Parr

31,113 次观看 • 1 个月前

MICROSOFT QUIETLY SHIPPED THE RAG PIPELINE EVERYONE KEEPS TRYING TO BUILD FROM SCRATCH it is called Kernel Memory, and it turns any pile of files into an AI memory that answers with citations. drop your data in and Microsoft's pipeline does the rest: > ingest PDFs, Word, PPT, Excel, web pages, even images > extract the text, chunk it, embed it into vectors > store the vectors with metadata and keep the originals in blob storage > ask a question and it pulls the right chunks with semantic plus hybrid search then it hands the answer back grounded, with links to the exact source and full token usage. and it plugs into whatever you already run: > Azure OpenAI, OpenAI, Ollama, or Anthropic for the models > Qdrant, pgvector, Redis, or Azure AI Search for the vectors > every step is a swappable handler, so you can replace any part with your own one heads up: Microsoft archived the repo in June 2026 and ships it as a reference blueprint, not production. but as a map for how memory and RAG are actually built, nothing is cleaner. run it in one command: docker run kernelmemory/service bookmark this. Microsoft already drew the blueprint, you just build on it.
0:25

MICROSOFT QUIETLY SHIPPED THE RAG PIPELINE EVERYONE KEEPS TRYING TO BUILD FROM SCRATCH it is called Kernel Memory, and it turns any pile of files into an AI memory that answers with citations. drop your data in and Microsoft's pipeline does the rest: > ingest PDFs, Word, PPT, Excel, web pages, even images > extract the text, chunk it, embed it into vectors > store the vectors with metadata and keep the originals in blob storage > ask a question and it pulls the right chunks with semantic plus hybrid search then it hands the answer back grounded, with links to the exact source and full token usage. and it plugs into whatever you already run: > Azure OpenAI, OpenAI, Ollama, or Anthropic for the models > Qdrant, pgvector, Redis, or Azure AI Search for the vectors > every step is a swappable handler, so you can replace any part with your own one heads up: Microsoft archived the repo in June 2026 and ships it as a reference blueprint, not production. but as a map for how memory and RAG are actually built, nothing is cleaner. run it in one command: docker run kernelmemory/service bookmark this. Microsoft already drew the blueprint, you just build on it.

NO1ennn

85,010 次观看 • 15 天前

Microsoft is deceiving you by inflating its AI empire with money it handed its OWN customer first. They sold Wall Street a $37 billion AI business, then went silent the moment its own filing showed where that money came from. The line sits in the annual report for fiscal 2026: Microsoft recorded $24.1 billion of revenue from commercial arrangements with OpenAI, including revenue sharing payments. If you run that figure against Microsoft's own AI disclosures you'll find that OpenAI made up more than half, and likely around 70%, of everything the company counts as AI sales. ONE customer. A Microsoft spokesperson confirmed the figure covers all sales and revenue share from OpenAI. The 70% comes by assuming Microsoft's AI run rate kept growing at the 123% pace the company itself reported in March, which is the company's own optimistic math turned around on it. Now follow where that money starts: Microsoft has put around $12 billion into OpenAI since 2019. OpenAI spends its cash on computing power, and Microsoft is the cloud provider selling it. So the money leaves as an investment and comes back as an Azure bill. Microsoft then books that bill as AI revenue and shows it to investors as proof the AI business is "working." Microsoft invests in OpenAI -> OpenAI buys Microsoft compute -> Microsoft records the payment as AI revenue -> the AI growth story goes to Wall Street And a chunk of it never actually arrived. The same filing shows $6 billion of accounts receivable from OpenAI as of June 30. That is $6 billion of AI revenue Microsoft booked and had not been paid when the year closed. Now here's where it gets really concerning for anyone holding the stock... Microsoft has told the public how big its total AI business is exactly twice. Once for the quarter ending December 2024, when it said the unit was on pace for more than $13 billion a year. And once for the quarter ending March 2026, when Satya Nadella put it on pace for $37 billion. That $37 billion number went everywhere. It was the headline proof that Microsoft had won the AI race. Then fourth quarter earnings arrived, and Microsoft did NOT update it. The company that had been announcing the figure as its own scoreboard stopped announcing the figure. In the same stretch, the filing landed showing where most of it came from. So what is actually left underneath? The full year AI business ran near $34 billion. Take OpenAI out and roughly $10 billion remains. Microsoft has spent about $261 billion on capital expenditure since the start of 2022. That is the scale of the bet against what the rest of the AI business currently brings in. And the one customer holding it up is walking further away every quarter. In October, Microsoft's stake in OpenAI dropped to 27% from 32.5%. In April the partnership was rewritten so OpenAI can sell its products across any cloud it likes, which is how Amazon got a seat at the table. The exclusivity that made this arrangement valuable is gone. The compute bill and the unpaid $6 billion are still on Microsoft's books. Nadella spent two years telling the market Microsoft built the largest AI business in software. The filing shows one client bought most of it, on credit, using money Microsoft partly supplied. So watch the next earnings call: If Microsoft puts a fresh total AI number back on the board, the business found customers beyond OpenAI. If you hear a lot about AI momentum and never hear what it adds up to, you already know why the number went missing. But nonetheless, how is something like this even legal?
0:56

Microsoft is deceiving you by inflating its AI empire with money it handed its OWN customer first. They sold Wall Street a $37 billion AI business, then went silent the moment its own filing showed where that money came from. The line sits in the annual report for fiscal 2026: Microsoft recorded $24.1 billion of revenue from commercial arrangements with OpenAI, including revenue sharing payments. If you run that figure against Microsoft's own AI disclosures you'll find that OpenAI made up more than half, and likely around 70%, of everything the company counts as AI sales. ONE customer. A Microsoft spokesperson confirmed the figure covers all sales and revenue share from OpenAI. The 70% comes by assuming Microsoft's AI run rate kept growing at the 123% pace the company itself reported in March, which is the company's own optimistic math turned around on it. Now follow where that money starts: Microsoft has put around $12 billion into OpenAI since 2019. OpenAI spends its cash on computing power, and Microsoft is the cloud provider selling it. So the money leaves as an investment and comes back as an Azure bill. Microsoft then books that bill as AI revenue and shows it to investors as proof the AI business is "working." Microsoft invests in OpenAI -> OpenAI buys Microsoft compute -> Microsoft records the payment as AI revenue -> the AI growth story goes to Wall Street And a chunk of it never actually arrived. The same filing shows $6 billion of accounts receivable from OpenAI as of June 30. That is $6 billion of AI revenue Microsoft booked and had not been paid when the year closed. Now here's where it gets really concerning for anyone holding the stock... Microsoft has told the public how big its total AI business is exactly twice. Once for the quarter ending December 2024, when it said the unit was on pace for more than $13 billion a year. And once for the quarter ending March 2026, when Satya Nadella put it on pace for $37 billion. That $37 billion number went everywhere. It was the headline proof that Microsoft had won the AI race. Then fourth quarter earnings arrived, and Microsoft did NOT update it. The company that had been announcing the figure as its own scoreboard stopped announcing the figure. In the same stretch, the filing landed showing where most of it came from. So what is actually left underneath? The full year AI business ran near $34 billion. Take OpenAI out and roughly $10 billion remains. Microsoft has spent about $261 billion on capital expenditure since the start of 2022. That is the scale of the bet against what the rest of the AI business currently brings in. And the one customer holding it up is walking further away every quarter. In October, Microsoft's stake in OpenAI dropped to 27% from 32.5%. In April the partnership was rewritten so OpenAI can sell its products across any cloud it likes, which is how Amazon got a seat at the table. The exclusivity that made this arrangement valuable is gone. The compute bill and the unpaid $6 billion are still on Microsoft's books. Nadella spent two years telling the market Microsoft built the largest AI business in software. The filing shows one client bought most of it, on credit, using money Microsoft partly supplied. So watch the next earnings call: If Microsoft puts a fresh total AI number back on the board, the business found customers beyond OpenAI. If you hear a lot about AI momentum and never hear what it adds up to, you already know why the number went missing. But nonetheless, how is something like this even legal?

Ricardo

24,389 次观看 • 22 天前

"I don't think we ever go back to where we were," says $BLCO CEO Brent Saunders on remote vs. in person work. "I used to be a real stickler that work is in the office. Everyone needed to be in the office. The pandemic opened my eyes to some of the benefits of remote work."
4:27

"I don't think we ever go back to where we were," says $BLCO CEO Brent Saunders on remote vs. in person work. "I used to be a real stickler that work is in the office. Everyone needed to be in the office. The pandemic opened my eyes to some of the benefits of remote work."

Squawk Box

89,003 次观看 • 3 年前

man anthropic is absolutely cooking microsoft. claude now works natively in word, powerpoint and excel. thats 450M users but how the fuck did anthropic beat microsoft co-pilot? it gets worse - microsoft blew $13B creating co-pilot and owns 27% of openai yet no sign on chatgpt. - claude has access to SHARED context across excel, word and powerpoint. they know the footprint of microsoft's users - very valuable AI data. - only 15M microsoft users pay for copilot, so its clear they need to go model-agnostic - this is the 3rd major microsoft product to leverage claude (cowork and deep research are the other 2) very impressive execution from anthropic tbh, they are trying to be everywhere and anywhere - its working
0:57

man anthropic is absolutely cooking microsoft. claude now works natively in word, powerpoint and excel. thats 450M users but how the fuck did anthropic beat microsoft co-pilot? it gets worse - microsoft blew $13B creating co-pilot and owns 27% of openai yet no sign on chatgpt. - claude has access to SHARED context across excel, word and powerpoint. they know the footprint of microsoft's users - very valuable AI data. - only 15M microsoft users pay for copilot, so its clear they need to go model-agnostic - this is the 3rd major microsoft product to leverage claude (cowork and deep research are the other 2) very impressive execution from anthropic tbh, they are trying to be everywhere and anywhere - its working

Ejaaz

473,836 次观看 • 4 个月前

Tucker is Charles Lindbergh pilled: "They tried to discredit the term America First and they did it by tying it to Charles Lindbergh. Lindbergh was the greatest hero in the first half of the 20th century in the United States. A true hero and a pioneer in aviation."👀
2:23

Tucker is Charles Lindbergh pilled: "They tried to discredit the term America First and they did it by tying it to Charles Lindbergh. Lindbergh was the greatest hero in the first half of the 20th century in the United States. A true hero and a pioneer in aviation."👀

Logan Hall

236,244 次观看 • 9 个月前

Trump: Remember that I was the one that did it, OK? Somebody's going to walk into office and they're going to have the most successful country in history, and they're going to be bragging what a great job they did. We did it.
0:54

Trump: Remember that I was the one that did it, OK? Somebody's going to walk into office and they're going to have the most successful country in history, and they're going to be bragging what a great job they did. We did it.

Acyn

29,773 次观看 • 2 个月前

The CEO of Microsoft AI just said on camera that most white collar work will be fully automated within 12 to 18 months. This isn't some random guy on a podcast. This is the person in charge of building the tools that will do it. And he's telling you the timeline out loud.
1:25

The CEO of Microsoft AI just said on camera that most white collar work will be fully automated within 12 to 18 months. This isn't some random guy on a podcast. This is the person in charge of building the tools that will do it. And he's telling you the timeline out loud.

LayoffHedge

208,540 次观看 • 5 个月前

The owner of a real estate company thought it would be fun to build everyone their own tiny home as an office instead of the typical boring cubicles. He felt that it would be more private for them and it would be fun for the to customize and make it their own. When the workers get to work they seem to be at a home away from home. They are happier and more productive. Would you want to work in your own home office like this or should he just let them have cubicles like everyone else?
0:34

The owner of a real estate company thought it would be fun to build everyone their own tiny home as an office instead of the typical boring cubicles. He felt that it would be more private for them and it would be fun for the to customize and make it their own. When the workers get to work they seem to be at a home away from home. They are happier and more productive. Would you want to work in your own home office like this or should he just let them have cubicles like everyone else?

SonnyBoy🇺🇸

3,501,336 次观看 • 6 个月前

Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?
1:05

Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?

Ricardo

93,582 次观看 • 1 个月前

Bill Gates told Satya Nadella that Microsoft's 2019 $1B investment in OpenAI was the equivalent of lighting the money on fire. What did it mean for Microsoft to invest in the unproven nonprofit? "I didn't put in that billion dollars saying 'Oh yeah, this is going to be a hundred bagger.' That's not what was going through our heads." "We had a high risk tolerance and we said we want to go and give this a shot."
1:48

Bill Gates told Satya Nadella that Microsoft's 2019 $1B investment in OpenAI was the equivalent of lighting the money on fire. What did it mean for Microsoft to invest in the unproven nonprofit? "I didn't put in that billion dollars saying 'Oh yeah, this is going to be a hundred bagger.' That's not what was going through our heads." "We had a high risk tolerance and we said we want to go and give this a shot."

TBPN

538,322 次观看 • 10 个月前

Jill Biden: "I was the last First Lady who worked in that office. I loved the East Wing. It was so beautiful. When we moved in there, the previous inhabitant hadn't used the office to work in. It was kind of dingy and dull. Had I known that this was gonna happen, I would have purchased everything in that office and taken it with me. But who knew?"
1:51

Jill Biden: "I was the last First Lady who worked in that office. I loved the East Wing. It was so beautiful. When we moved in there, the previous inhabitant hadn't used the office to work in. It was kind of dingy and dull. Had I known that this was gonna happen, I would have purchased everything in that office and taken it with me. But who knew?"

Reggie B.

69,174 次观看 • 2 天前

The entire AI industry is racing to build the smartest model. Satya Nadella just admitted that is not where the money is. The model is not the product. The harness is. That is the exact line. And it changes what Microsoft is actually competing on. OpenAI, Anthropic, Google, xAI, Meta every frontier lab is pouring hundreds of billions into training compute, chasing the next capability jump. Each betting that raw model intelligence is the moat. Microsoft is doing the opposite. It is building the harness the orchestration layer that sits above the model, connecting it to tools, data, permissions, sub-agents, and enterprise workflows. And it is letting OpenAI, Anthropic, and MAI compete to plug into it. "You need the model. But the model is not the product. The harness is." So do the math on what a harness actually does. A raw model dropped into an enterprise answers questions. That is a chatbot. A harness turns that same model into an agent that reads the SharePoint, edits the ERP entry, pulls the GitHub PR, updates Salesforce, and files the Excel report with the right permissions, the right audit trail, and the right sub-agent for each sub-task. The model provides the intelligence. The harness converts intelligence into work. Now here's where it gets interesting. "Even the best model in the world will feel broken without a great harness. And an okay model with a great harness can feel like magic." If that is true, the enterprise buyer is not buying model quality. The enterprise buyer is buying the harness. Which means model quality becomes a commodity input over time, and harness quality becomes the sustainable moat. Compare that to the strategy the entire frontier lab industry is executing. Everyone else is chasing the numerator raw intelligence. Almost nobody at scale is racing to build the denominator the orchestration layer that determines whether that intelligence can actually be deployed profitably inside a real company. The frontier model race has a 10 to 20 percent chance of producing a single dominant winner. Nadella just told the industry he does not need to be that winner. If OpenAI wins, Microsoft wins. If Anthropic wins, Microsoft wins. If MAI wins, Microsoft wins. If someone Microsoft has never heard of trains a better model in 2027, Microsoft still wins. Because the compute they train on, the harness they get plugged into, the enterprise contracts they get delivered through, and the products they sit inside are all Microsoft. He is not building the best AI model. He is building the layer that the best AI model has to run on to make anyone money. I wonder which position looks more valuable in ten years.
3:19

The entire AI industry is racing to build the smartest model. Satya Nadella just admitted that is not where the money is. The model is not the product. The harness is. That is the exact line. And it changes what Microsoft is actually competing on. OpenAI, Anthropic, Google, xAI, Meta every frontier lab is pouring hundreds of billions into training compute, chasing the next capability jump. Each betting that raw model intelligence is the moat. Microsoft is doing the opposite. It is building the harness the orchestration layer that sits above the model, connecting it to tools, data, permissions, sub-agents, and enterprise workflows. And it is letting OpenAI, Anthropic, and MAI compete to plug into it. "You need the model. But the model is not the product. The harness is." So do the math on what a harness actually does. A raw model dropped into an enterprise answers questions. That is a chatbot. A harness turns that same model into an agent that reads the SharePoint, edits the ERP entry, pulls the GitHub PR, updates Salesforce, and files the Excel report with the right permissions, the right audit trail, and the right sub-agent for each sub-task. The model provides the intelligence. The harness converts intelligence into work. Now here's where it gets interesting. "Even the best model in the world will feel broken without a great harness. And an okay model with a great harness can feel like magic." If that is true, the enterprise buyer is not buying model quality. The enterprise buyer is buying the harness. Which means model quality becomes a commodity input over time, and harness quality becomes the sustainable moat. Compare that to the strategy the entire frontier lab industry is executing. Everyone else is chasing the numerator raw intelligence. Almost nobody at scale is racing to build the denominator the orchestration layer that determines whether that intelligence can actually be deployed profitably inside a real company. The frontier model race has a 10 to 20 percent chance of producing a single dominant winner. Nadella just told the industry he does not need to be that winner. If OpenAI wins, Microsoft wins. If Anthropic wins, Microsoft wins. If MAI wins, Microsoft wins. If someone Microsoft has never heard of trains a better model in 2027, Microsoft still wins. Because the compute they train on, the harness they get plugged into, the enterprise contracts they get delivered through, and the products they sit inside are all Microsoft. He is not building the best AI model. He is building the layer that the best AI model has to run on to make anyone money. I wonder which position looks more valuable in ten years.

Vikram M

21,463 次观看 • 2 个月前

The cold is British. They just never told you. ❄️🇬🇧 Every air conditioner, every fridge, every freezer on earth, the cold inside all of it was first made by a Scotsman. In 1756. ❄️🏴󠁧󠁢󠁳󠁣󠁴󠁿 His name was William Cullen, a doctor in Edinburgh. In a warm room, with no ice and no winter, he drew the air from a glass of ether until it boiled cold and drank the heat from the water around it, until the water froze. No one had ever done it before. Then he wrote it down and walked away. No machine, no patent, no fortune. Just the proof, on a bench. It sat there the better part of a century. A British bench built the first machine that worked, and a Scot carried it across the world to Australia, where it froze meat and cooled beer. But cold was only half the story. ❄️📖 To master the air itself took another Scot. When the Houses of Parliament burned down in 1834, David Boswell Reid made the new building breathe, its gothic spires its lungs. At St George's Hall in Liverpool in 1851 he built what is often called the first air-conditioned building on earth. It should have made him. He died forgotten in America instead. 40 years on, Willis Carrier built the machine and earned his name as the father of modern air conditioning. He earned every bit of it. But he did not make the cold. The cold was British. America took that inheritance and cooled the world with it, and that is no theft. That is what an inheritance is for. We are the home of British heroes. Not built by ads, not by the government, built by us. There's a place for you with us. Be part of us. ☝️🇬🇧 Be Proud Of Us. 🙏🇬🇧
4:44

The cold is British. They just never told you. ❄️🇬🇧 Every air conditioner, every fridge, every freezer on earth, the cold inside all of it was first made by a Scotsman. In 1756. ❄️🏴󠁧󠁢󠁳󠁣󠁴󠁿 His name was William Cullen, a doctor in Edinburgh. In a warm room, with no ice and no winter, he drew the air from a glass of ether until it boiled cold and drank the heat from the water around it, until the water froze. No one had ever done it before. Then he wrote it down and walked away. No machine, no patent, no fortune. Just the proof, on a bench. It sat there the better part of a century. A British bench built the first machine that worked, and a Scot carried it across the world to Australia, where it froze meat and cooled beer. But cold was only half the story. ❄️📖 To master the air itself took another Scot. When the Houses of Parliament burned down in 1834, David Boswell Reid made the new building breathe, its gothic spires its lungs. At St George's Hall in Liverpool in 1851 he built what is often called the first air-conditioned building on earth. It should have made him. He died forgotten in America instead. 40 years on, Willis Carrier built the machine and earned his name as the father of modern air conditioning. He earned every bit of it. But he did not make the cold. The cold was British. America took that inheritance and cooled the world with it, and that is no theft. That is what an inheritance is for. We are the home of British heroes. Not built by ads, not by the government, built by us. There's a place for you with us. Be part of us. ☝️🇬🇧 Be Proud Of Us. 🙏🇬🇧

Proudofus.uk

56,349 次观看 • 2 个月前

In Ancient Rome, an "office" wasn't a building, it was a person's staff. The word comes from “officium”, referring to a magistrate's retinue of aides and administrators, each one called an officialis. If you held real authority, your "office" was the group of people around you handling correspondence, records, and logistics on your behalf. This wasn't a small operation. Surviving records like the Notitia Dignitatum, a late Roman administrative document, list out the staffing structures for provincial governors and military commanders in detail: ranks, roles, and reporting lines not far off from a modern org chart. Coordination happened the only way it could: in person, in the same building, one conversation at a time. It wasn't until the word crossed into English in the 1200s that "office" started to mean a place instead of a role, and even later before it came to mean the literal room or building we picture today. For most of its history, the word wasn't about where you worked. It was about who was working with you.
5:37

In Ancient Rome, an "office" wasn't a building, it was a person's staff. The word comes from “officium”, referring to a magistrate's retinue of aides and administrators, each one called an officialis. If you held real authority, your "office" was the group of people around you handling correspondence, records, and logistics on your behalf. This wasn't a small operation. Surviving records like the Notitia Dignitatum, a late Roman administrative document, list out the staffing structures for provincial governors and military commanders in detail: ranks, roles, and reporting lines not far off from a modern org chart. Coordination happened the only way it could: in person, in the same building, one conversation at a time. It wasn't until the word crossed into English in the 1200s that "office" started to mean a place instead of a role, and even later before it came to mean the literal room or building we picture today. For most of its history, the word wasn't about where you worked. It was about who was working with you.

Historic Vids

180,301 次观看 • 1 个月前