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$NOW CEO Bill McDermott says AI can identify problems but it cannot fix them. ServiceNow sits on 80B enterprise workflows across legacy systems and acts as the “last-mile” execution layer.

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Shay Boloor

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137,777 Aufrufe • vor 5 Monaten •via X (Twitter)

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🚨 ServiceNow CEO Bill McDermott just dropped this on the AI hype: “Most businesses don’t want to build workflow software for everything internally. They want one responsible AI Control Tower.” ServiceNow is becoming the fabric connecting every hyperscaler, every LLM, systems of record and now full security (cybercrime = $1 Trillion/month problem). True agentic enterprise is here: MoveWorks, VZA identity, Armis OT/security. Integrated major moves in just 20 days. Jensen Huang ( $NVDA CEO) approves, they’re teaming up on the agentic future. 2030 Price Target: $1,200 – $2,000+ per share as they hit $30B+ revenue and own the enterprise AI operating system. While others talk apocalypse, ServiceNow is building it. $NOW to the moon. Who’s loading up?
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🚨 ServiceNow CEO Bill McDermott just dropped this on the AI hype: “Most businesses don’t want to build workflow software for everything internally. They want one responsible AI Control Tower.” ServiceNow is becoming the fabric connecting every hyperscaler, every LLM, systems of record and now full security (cybercrime = $1 Trillion/month problem). True agentic enterprise is here: MoveWorks, VZA identity, Armis OT/security. Integrated major moves in just 20 days. Jensen Huang ( $NVDA CEO) approves, they’re teaming up on the agentic future. 2030 Price Target: $1,200 – $2,000+ per share as they hit $30B+ revenue and own the enterprise AI operating system. While others talk apocalypse, ServiceNow is building it. $NOW to the moon. Who’s loading up?

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Sequoia partner Grady Buchanan says systems of record SAAS like Workday, Salesforce, and ServiceNow are safer from AI. The risk sits with workflow apps in the middle, as AI agents become the new layer that does the work on top of core data.
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Sequoia partner Grady Buchanan says systems of record SAAS like Workday, Salesforce, and ServiceNow are safer from AI. The risk sits with workflow apps in the middle, as AI agents become the new layer that does the work on top of core data.

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$NOW CEO Bill McDermott says ServiceNow can become a $1T company by 2030. He bought $3M worth of shares at $107. $NVDA CEO Jensen Huang says it could 100x. President Trump bought $5M. Anthropic says it’s essential infrastructure. OpenAI is integrating deeply with it. $AMZN, $MSFT & $GOOGL are all expanding partnerships. And vibecoding an alternative would probably cost 10x more than just using ServiceNow. Is ServiceNow the easiest buy in the market?
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$NOW CEO Bill McDermott says ServiceNow can become a $1T company by 2030. He bought $3M worth of shares at $107. $NVDA CEO Jensen Huang says it could 100x. President Trump bought $5M. Anthropic says it’s essential infrastructure. OpenAI is integrating deeply with it. $AMZN, $MSFT & $GOOGL are all expanding partnerships. And vibecoding an alternative would probably cost 10x more than just using ServiceNow. Is ServiceNow the easiest buy in the market?

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$NOW CEO Bill McDermott: “ServiceNow will become a $1T company by 2030.” The current market cap is $99B = he’s calling for a 10x. He bought $3M worth of shares at $107. $NVDA CEO Jensen Huang says ServiceNow can 100x. President Trump bought $5M. $AMZN, $MSFT, $GOOGL OpenAI & Anthropic are all expanding partnerships. And vibecoding an alternative would cost 5-10x more than just using ServiceNow. Is ServiceNow the strongest buy in the market?
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$NOW CEO Bill McDermott: “ServiceNow will become a $1T company by 2030.” The current market cap is $99B = he’s calling for a 10x. He bought $3M worth of shares at $107. $NVDA CEO Jensen Huang says ServiceNow can 100x. President Trump bought $5M. $AMZN, $MSFT, $GOOGL OpenAI & Anthropic are all expanding partnerships. And vibecoding an alternative would cost 5-10x more than just using ServiceNow. Is ServiceNow the strongest buy in the market?

Noah

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$PLTR CEO Alex Karp argued that AI alone is not enough. The real value comes from combining models with domain expertise, workflows, and operational execution. His view is that enterprise AI is ultimately about solving business problems, not maximizing token usage. As models become commoditized, the winners may be the companies that combine taste, data, and execution rather than compute alone.
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$PLTR CEO Alex Karp argued that AI alone is not enough. The real value comes from combining models with domain expertise, workflows, and operational execution. His view is that enterprise AI is ultimately about solving business problems, not maximizing token usage. As models become commoditized, the winners may be the companies that combine taste, data, and execution rather than compute alone.

Sam Badawi

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$SPCX spending $60B on Cursor validates the idea that real AI value accrues to the application layer that owns the workflow, proprietary data loop and enterprise distribution. $NOW is building exactly that as the orchestration layer for enterprise AI agents across business workflows. The Cursor deal is a reminder that the market will pay massive premiums for software that owns where work actually happens.
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$SPCX spending $60B on Cursor validates the idea that real AI value accrues to the application layer that owns the workflow, proprietary data loop and enterprise distribution. $NOW is building exactly that as the orchestration layer for enterprise AI agents across business workflows. The Cursor deal is a reminder that the market will pay massive premiums for software that owns where work actually happens.

Shay Boloor

82,503 Aufrufe • vor 2 Monaten

WHERE THE ENTERPRISE AI STACK IS BEING BUILT 1. $PLTR building the orchestration layer of the AI economy through the control systems enterprises need before models can take real-world actions backed by a Rule of 40 score of 127 2. $CRWD, $PANW, $ZS & $RBRK building the security layer of the AI economy across endpoint, identity, Zero Trust & cyber recovery as every new agent, machine identity & AI-generated workflow expands the attack surface 3. $NET building the connectivity layer of the AI economy through the internet control plane that agents, APIs & inference traffic must move across in real time, with Cloudflare sitting behind over 20% of the web 4. $SNOW & $MDB building the data layer of the AI economy through the clean, structured, production-grade enterprise data systems that make AI usable inside real applications and workflows
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WHERE THE ENTERPRISE AI STACK IS BEING BUILT 1. $PLTR building the orchestration layer of the AI economy through the control systems enterprises need before models can take real-world actions backed by a Rule of 40 score of 127 2. $CRWD, $PANW, $ZS & $RBRK building the security layer of the AI economy across endpoint, identity, Zero Trust & cyber recovery as every new agent, machine identity & AI-generated workflow expands the attack surface 3. $NET building the connectivity layer of the AI economy through the internet control plane that agents, APIs & inference traffic must move across in real time, with Cloudflare sitting behind over 20% of the web 4. $SNOW & $MDB building the data layer of the AI economy through the clean, structured, production-grade enterprise data systems that make AI usable inside real applications and workflows

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General AI is already a dated concept. ThinkingAI connects an entire business ecosystem through MCP, pulling data, tools, and workflows into a single execution layer. Not isolated AI tools working separately. Coordinated agent systems triggering real actions across the whole operation. The shift is from using AI to running on it. Every company becomes an AI-powered system built on custom agent teams through the ThinkingAI Agentic Engine.
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General AI is already a dated concept. ThinkingAI connects an entire business ecosystem through MCP, pulling data, tools, and workflows into a single execution layer. Not isolated AI tools working separately. Coordinated agent systems triggering real actions across the whole operation. The shift is from using AI to running on it. Every company becomes an AI-powered system built on custom agent teams through the ThinkingAI Agentic Engine.

Future Stacked

52,003 Aufrufe • vor 3 Monaten

Ali Ghodsi, the cofounder and CEO of Databricks, says Zoom has a massive chance to build an AI-first product, that could seriously disrupt the traditional enterprise SAAS. Because it sits on the largest datasets of meeting videos and transcripts. The big pain in enterprise software is data entry and coordination. Zoom already sits on the raw input: every customer call and internal meeting, plus the video, audio, and transcript. If Zoom can reliably pull out decisions, context, and action items, then write them back into the right system of record automatically, as an AI-first workflow layer, it becomes the front door for work. That would replace lots of separate SAAS tools that exist mainly to collect notes and updates. --- Video from 'Bg2 Pod' YT channel (link in comment)
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Ali Ghodsi, the cofounder and CEO of Databricks, says Zoom has a massive chance to build an AI-first product, that could seriously disrupt the traditional enterprise SAAS. Because it sits on the largest datasets of meeting videos and transcripts. The big pain in enterprise software is data entry and coordination. Zoom already sits on the raw input: every customer call and internal meeting, plus the video, audio, and transcript. If Zoom can reliably pull out decisions, context, and action items, then write them back into the right system of record automatically, as an AI-first workflow layer, it becomes the front door for work. That would replace lots of separate SAAS tools that exist mainly to collect notes and updates. --- Video from 'Bg2 Pod' YT channel (link in comment)

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$PLTR $NOW Palantir is coming for ServiceNow. I've gotten plenty of pushback on this, but after watching the Hertz presentation at AIPCon 10, I think it’s happening. Hertz demonstrated a workflow that looks something like this: • A vehicle is returned. • The system already knows its location, mileage, maintenance history, damage history, and rental schedule. • An issue is identified and entered into the system. • A maintenance workflow is generated. • The task is assigned to the appropriate team. • The vehicle is routed to the correct queue. • The relevant employees are notified. Historically, this is where ServiceNow creates value. A problem is reported. A ticket is created. The workflow is managed. What Palantir demonstrated is different. Once an issue enters the system, AIP can help determine the appropriate response, generate tasks, assign work, route resources, and track execution all autonomously. In other words: ServiceNow manages the workflow. Palantir is increasingly orchestrating it. Now before the $NOW crowd comes after me, ServiceNow is much broader than ticketing alone. It powers IT service management, employee onboarding, HR workflows, finance operations, security operations, and enterprise service management across some of the largest organizations in the world. But Palantir's AIP is increasingly capable of: • Monitoring systems • Detecting anomalies • Recommending actions • Generating tasks • Assigning work • Tracking execution • Measuring outcomes I'm not saying Palantir replaces ServiceNow tomorrow, but Palantir is starting to make the ticketing system unecessary.
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$PLTR $NOW Palantir is coming for ServiceNow. I've gotten plenty of pushback on this, but after watching the Hertz presentation at AIPCon 10, I think it’s happening. Hertz demonstrated a workflow that looks something like this: • A vehicle is returned. • The system already knows its location, mileage, maintenance history, damage history, and rental schedule. • An issue is identified and entered into the system. • A maintenance workflow is generated. • The task is assigned to the appropriate team. • The vehicle is routed to the correct queue. • The relevant employees are notified. Historically, this is where ServiceNow creates value. A problem is reported. A ticket is created. The workflow is managed. What Palantir demonstrated is different. Once an issue enters the system, AIP can help determine the appropriate response, generate tasks, assign work, route resources, and track execution all autonomously. In other words: ServiceNow manages the workflow. Palantir is increasingly orchestrating it. Now before the $NOW crowd comes after me, ServiceNow is much broader than ticketing alone. It powers IT service management, employee onboarding, HR workflows, finance operations, security operations, and enterprise service management across some of the largest organizations in the world. But Palantir's AIP is increasingly capable of: • Monitoring systems • Detecting anomalies • Recommending actions • Generating tasks • Assigning work • Tracking execution • Measuring outcomes I'm not saying Palantir replaces ServiceNow tomorrow, but Palantir is starting to make the ticketing system unecessary.

Davis.

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Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.
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Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.

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🆕 Claude Cowork, Skills, and the Future of AI Coworkers Felix Rieseberg has spent years working at the interface layer, from Electron and the Slack desktop app to now helping build Claude Cowork. In this episode, Felix explains why execution is getting so cheap that teams can “build all the candidates,” why Anthropic is betting on local-first agent workflows, and why the future of AI products may belong less to chatbots and more to systems that can actually do knowledge work.
0:34

🆕 Claude Cowork, Skills, and the Future of AI Coworkers Felix Rieseberg has spent years working at the interface layer, from Electron and the Slack desktop app to now helping build Claude Cowork. In this episode, Felix explains why execution is getting so cheap that teams can “build all the candidates,” why Anthropic is betting on local-first agent workflows, and why the future of AI products may belong less to chatbots and more to systems that can actually do knowledge work.

Latent.Space

66,874 Aufrufe • vor 5 Monaten

Palantir CEO Alex Karp on why the model is not the moat. The application layer is: "To make them valuable in an enterprise, like a battlefield, regulated, or manufacturing context, you have to have what's called an application layer." "We have this thing called ontology that now everyone's copying. It takes a large language model and makes it safe and useful and precise." "Safe because it doesn't touch your underlying data." "Safe because it prevents the large language model from caching your data and replicating your business." The tell for any enterprise AI pitch: ask what sits between the model and your data. If the answer is nothing, you are not buying leverage. You are renting a fast way to hand your business to whoever owns the weights. Alex Karp, CEO of Palantir, on CNBC.
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Palantir CEO Alex Karp on why the model is not the moat. The application layer is: "To make them valuable in an enterprise, like a battlefield, regulated, or manufacturing context, you have to have what's called an application layer." "We have this thing called ontology that now everyone's copying. It takes a large language model and makes it safe and useful and precise." "Safe because it doesn't touch your underlying data." "Safe because it prevents the large language model from caching your data and replicating your business." The tell for any enterprise AI pitch: ask what sits between the model and your data. If the answer is nothing, you are not buying leverage. You are renting a fast way to hand your business to whoever owns the weights. Alex Karp, CEO of Palantir, on CNBC.

Karl Mehta

31,891 Aufrufe • vor 1 Monat

JUST IN: 🌐 "Every major institution, every major bank, every capital markets firms, payments companies, enterprise... can all now build on this infrastructure," says Circle CEO Jeremy Allaire. 🗨️ "Treat it as digital cash in the economic system. And that's a huge opening up."
1:19

JUST IN: 🌐 "Every major institution, every major bank, every capital markets firms, payments companies, enterprise... can all now build on this infrastructure," says Circle CEO Jeremy Allaire. 🗨️ "Treat it as digital cash in the economic system. And that's a huge opening up."

Bitcoin.com News

78,704 Aufrufe • vor 28 Tagen

Just last week $NOW CEO Bill McDermott had an hour-long interview on the No Priors podcast. He gave away several operational metrics that were missing. This gives a clearer look at their real competitive advantage right now. First, he shut down the analyst narrative about integration risk. On the earnings call, Wall Street worried that merging Moveworks, Veza, and Armis all at once would break the core platform. McDermott revealed they can fully integrated all of these businesses into the core system in just 20 days. That kind of engineering speed is impressive for major enterprise software mergers. It proves their internal architecture is incredibly agile. Enterprise deployment times have collapsed. Historically, big software installations take months or even years. McDermott stated that massive customers are now going live on their autonomous platform in under 30 days. This completely changes the return on investment math for buyers. If a CIO can show value in one month instead of one year, budget approvals happen much faster. He specifically noted that "the dance has gotten brief" and customers are making highly decisive, rapid purchasing choices. He finally explained the math behind his claim that building AI workflows from scratch costs ten times more than buying ServiceNow. It is not just a marketing number. They factored in three specific costs. They added up the massive cost of human capital required to write new code to mimic existing workflows. Then they added the capital expenditure of the necessary GPU compute. And finally, they added the ongoing variable cost of language model tokens. When you stack those three expenses, trying to replace their platform with raw AI becomes an incredibly difficult financial decision. He also dropped a massive usage statistic to prove their scale. They currently process 7 TRILLION transactions across 85B active workflows. McDermott gave a rare look at his daily sales management. He personally sat down for one-on-one calls with 17 different quota-carrying sales reps just yesterday. He has 72 of these calls scheduled for this month alone. A CEO of a company this size directly interviewing ground-level salespeople shows intense, micromanaged execution. It also means management has a flawless, real-time read on exactly what enterprise buyers are doing. It is easier to trust their forward guidance because the CEO is literally talking to the people closing the deals every single day. Wow!
3:12

Just last week $NOW CEO Bill McDermott had an hour-long interview on the No Priors podcast. He gave away several operational metrics that were missing. This gives a clearer look at their real competitive advantage right now. First, he shut down the analyst narrative about integration risk. On the earnings call, Wall Street worried that merging Moveworks, Veza, and Armis all at once would break the core platform. McDermott revealed they can fully integrated all of these businesses into the core system in just 20 days. That kind of engineering speed is impressive for major enterprise software mergers. It proves their internal architecture is incredibly agile. Enterprise deployment times have collapsed. Historically, big software installations take months or even years. McDermott stated that massive customers are now going live on their autonomous platform in under 30 days. This completely changes the return on investment math for buyers. If a CIO can show value in one month instead of one year, budget approvals happen much faster. He specifically noted that "the dance has gotten brief" and customers are making highly decisive, rapid purchasing choices. He finally explained the math behind his claim that building AI workflows from scratch costs ten times more than buying ServiceNow. It is not just a marketing number. They factored in three specific costs. They added up the massive cost of human capital required to write new code to mimic existing workflows. Then they added the capital expenditure of the necessary GPU compute. And finally, they added the ongoing variable cost of language model tokens. When you stack those three expenses, trying to replace their platform with raw AI becomes an incredibly difficult financial decision. He also dropped a massive usage statistic to prove their scale. They currently process 7 TRILLION transactions across 85B active workflows. McDermott gave a rare look at his daily sales management. He personally sat down for one-on-one calls with 17 different quota-carrying sales reps just yesterday. He has 72 of these calls scheduled for this month alone. A CEO of a company this size directly interviewing ground-level salespeople shows intense, micromanaged execution. It also means management has a flawless, real-time read on exactly what enterprise buyers are doing. It is easier to trust their forward guidance because the CEO is literally talking to the people closing the deals every single day. Wow!

CapexAndChill

120,541 Aufrufe • vor 3 Monaten

I came across this ad that seems as if an AI took all the typical manhwa power systems and tropes and blended them into something painfully generic. It's so bad but I can't stop watching it.
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I came across this ad that seems as if an AI took all the typical manhwa power systems and tropes and blended them into something painfully generic. It's so bad but I can't stop watching it.

blyoof

423,729 Aufrufe • vor 2 Jahren

Demis Hassabis says AGI is only a few years away, and society needs to take it seriously now AlphaGo, ten years ago, marked the beginning of the modern AI era "we had five or six years, but didn't use them wisely, and dismissed it as an anomaly, but now these systems are getting really good"
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Demis Hassabis says AGI is only a few years away, and society needs to take it seriously now AlphaGo, ten years ago, marked the beginning of the modern AI era "we had five or six years, but didn't use them wisely, and dismissed it as an anomaly, but now these systems are getting really good"

Haider.

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Day 2 with the Intuition 👁️ ecosystem step by step video guide Today I explored TRUST Naming Service (TNS) it acts as an identity layer helping connect records and knowledge across the network. I left some questions in the video answer them and you can get 3 ttrust faucet Stay focused stay bullish on $TRUST

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27,296 Aufrufe • vor 11 Monaten

Your AI is only as smart as the context it runs on. Have you built your shared enterprise brain yet? At Databricks Data+AI Summit, I spoke with Prukalpa ✨, co-founder and co-CEO of Atlan, to go deeper on the AI Context Layer in practice. The concept of a shared enterprise brain resonated with me. It is a foundation that every AI agent draws from, learns from, and contributes back to. "The future of organizations are going to be the fastest learning organizations." - Prukalpa ✨ Sankar, co-founder and co-CEO of Atlan Watch the full interview on YouTube: Check out the live demo by Atlan on Building Context for Your AI Agents - #EnterpriseAI #ContextLayer #Data #AI #AtlanPartner Matthias Heidrich
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Your AI is only as smart as the context it runs on. Have you built your shared enterprise brain yet? At Databricks Data+AI Summit, I spoke with Prukalpa ✨, co-founder and co-CEO of Atlan, to go deeper on the AI Context Layer in practice. The concept of a shared enterprise brain resonated with me. It is a foundation that every AI agent draws from, learns from, and contributes back to. "The future of organizations are going to be the fastest learning organizations." - Prukalpa ✨ Sankar, co-founder and co-CEO of Atlan Watch the full interview on YouTube: Check out the live demo by Atlan on Building Context for Your AI Agents - #EnterpriseAI #ContextLayer #Data #AI #AtlanPartner Matthias Heidrich

Helen Yu

10,982 Aufrufe • vor 1 Monat