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Ackman views $MSFT as having an "impossible to disrupt" position in enterprise software. The base Microsoft 365 package has 450M users at a very low cost per seat, roughly $200 per customer. It would be nearly impossible for an enterprise to replace these various components with 3P vendors, even... show more

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The market is underappreciating that $MSFT already owns the enterprise workflow layer where AI adoption is likely to happen. Workers already live inside Outlook, Excel, PowerPoint, Teams, GitHub and Azure which gives Microsoft a built-in distribution advantage as AI gets embedded across the enterprise. Copilot is still early but the numbers are getting more meaningful with over 20M paid seats, paid seat additions up 250% YoY and customers with more than 50K seats quadrupling YoY Every 10M Copilot seats at ~$30 per user per month represents ~$3.6B of annualized revenue so if Copilot scales to 100M seats over the next several years then it becomes a major software revenue layer on top of Microsoft 365.

The market is underappreciating that $MSFT already owns the enterprise workflow layer where AI adoption is likely to happen. Workers already live inside Outlook, Excel, PowerPoint, Teams, GitHub and Azure which gives Microsoft a built-in distribution advantage as AI gets embedded across the enterprise. Copilot is still early but the numbers are getting more meaningful with over 20M paid seats, paid seat additions up 250% YoY and customers with more than 50K seats quadrupling YoY Every 10M Copilot seats at ~$30 per user per month represents ~$3.6B of annualized revenue so if Copilot scales to 100M seats over the next several years then it becomes a major software revenue layer on top of Microsoft 365.

Shay Boloor

117,810 Aufrufe • vor 1 Monat

$MSFT is trading at a decade-low valuation because the market is focused on the near-term cost of AI while underpricing Microsoft’s role as one of the most important enterprise AI platforms in the world. The bigger shift is that Microsoft may move from only monetizing users to monetizing work where companies eventually pay not just for employee licenses but for the AI work being performed around each employee. That creates a ton of upside if Microsoft can monetize agents, tokens, workflows, security, governance and productivity across the enterprise stack in the new AI economy.

$MSFT is trading at a decade-low valuation because the market is focused on the near-term cost of AI while underpricing Microsoft’s role as one of the most important enterprise AI platforms in the world. The bigger shift is that Microsoft may move from only monetizing users to monetizing work where companies eventually pay not just for employee licenses but for the AI work being performed around each employee. That creates a ton of upside if Microsoft can monetize agents, tokens, workflows, security, governance and productivity across the enterprise stack in the new AI economy.

Shay Boloor

606,243 Aufrufe • vor 1 Monat

"Every software company in the world, needs to have an OpenClaw🦞 strategy" - Jensen at NVIDIA AI GTC Framing OpenClaw as one of the most important open source releases ever, they have announced NemoClaw - a reference platform for enterprise grade secure Openclaw, with OpenShell, Network boundaries, security baked in.

"Every software company in the world, needs to have an OpenClaw🦞 strategy" - Jensen at NVIDIA AI GTC Framing OpenClaw as one of the most important open source releases ever, they have announced NemoClaw - a reference platform for enterprise grade secure Openclaw, with OpenShell, Network boundaries, security baked in.

Alex Volkov

562,028 Aufrufe • vor 5 Monaten

WorkOS: The Enterprise Stack for the AI Era AI companies are just B2B SaaS with a new engine. They monetize like SaaS, sell like SaaS, and scale into the enterprise like SaaS. The difference is velocity. These new products grow so fast that the old playbook of “PLG for years, enterprise later” simply does not work anymore. PMF is no longer enough. Winning your market requires crossing the Enterprise Chasm almost immediately. Enterprise auth, provisioning, RBAC, compliance, billing, IT integrations. If you wait, someone else takes your market while you are still wiring SCIM. This is why WorkOS exists. We give developers the infrastructure they need to scale up-market on day one. Even if you have never touched WorkOS, you have already used it through products like ChatGPT, Perplexity, Cursor and many others. Today we operate 81M+ enterprise user accounts, 67M API calls per day, and 38K+ connected enterprise environments. Modern AI tools already run through WorkOS. At ERC, we unveiled six major launches expanding that foundation for the AI era: • AuthKit for ChatGPT Apps: secure OAuth + MCP so developers can connect real enterprise data to 700M+ weekly ChatGPT users. • AuthKit for Platforms: embed full enterprise identity into frameworks like Supabase and Convex for zero-friction onboarding. • Stripe Usage Sync: actual per-seat billing with no glue code. Data stays consistent and invoices are always correct. • WorkOS Pipes: the fastest and most secure way to ship integrations (Salesforce, Slack, Intercom and more). • Agent-Ready API Keys: scoped, revocable keys designed for both developers and autonomous agents. • WorkOS Studio: vibe coding for the enterprise. A collaborative AI app builder with SSO, SCIM, RBAC, audit logs, workflows and third-party connectors built-in. Internal software at the speed of a prompt. AI has already changed how software gets created. The next shift is changing what software becomes. We are still “filming the play” like early cinema: using new technology to recreate old patterns. The opportunity ahead is to invent entirely new applications that only AI-native development makes possible. WorkOS is building the enterprise infrastructure that lets teams design the next era of software itself. Enterprise-ready AI is where the real acceleration happens. Let’s build that future together.

WorkOS: The Enterprise Stack for the AI Era AI companies are just B2B SaaS with a new engine. They monetize like SaaS, sell like SaaS, and scale into the enterprise like SaaS. The difference is velocity. These new products grow so fast that the old playbook of “PLG for years, enterprise later” simply does not work anymore. PMF is no longer enough. Winning your market requires crossing the Enterprise Chasm almost immediately. Enterprise auth, provisioning, RBAC, compliance, billing, IT integrations. If you wait, someone else takes your market while you are still wiring SCIM. This is why WorkOS exists. We give developers the infrastructure they need to scale up-market on day one. Even if you have never touched WorkOS, you have already used it through products like ChatGPT, Perplexity, Cursor and many others. Today we operate 81M+ enterprise user accounts, 67M API calls per day, and 38K+ connected enterprise environments. Modern AI tools already run through WorkOS. At ERC, we unveiled six major launches expanding that foundation for the AI era: • AuthKit for ChatGPT Apps: secure OAuth + MCP so developers can connect real enterprise data to 700M+ weekly ChatGPT users. • AuthKit for Platforms: embed full enterprise identity into frameworks like Supabase and Convex for zero-friction onboarding. • Stripe Usage Sync: actual per-seat billing with no glue code. Data stays consistent and invoices are always correct. • WorkOS Pipes: the fastest and most secure way to ship integrations (Salesforce, Slack, Intercom and more). • Agent-Ready API Keys: scoped, revocable keys designed for both developers and autonomous agents. • WorkOS Studio: vibe coding for the enterprise. A collaborative AI app builder with SSO, SCIM, RBAC, audit logs, workflows and third-party connectors built-in. Internal software at the speed of a prompt. AI has already changed how software gets created. The next shift is changing what software becomes. We are still “filming the play” like early cinema: using new technology to recreate old patterns. The opportunity ahead is to invent entirely new applications that only AI-native development makes possible. WorkOS is building the enterprise infrastructure that lets teams design the next era of software itself. Enterprise-ready AI is where the real acceleration happens. Let’s build that future together.

Michael Grinich

37,894 Aufrufe • vor 9 Monaten

In Ackman's latest interview he divides the AI market, stating that it is not a bubble at the foundational layer, but highly risky at the software/model layer. He sees "near infinite demand" for compute. He believes infrastructure providers such as Microsoft, Amazon, Meta, and even SpaceX will earn massive returns on their data center investments. He is highly skeptical of pure model layer businesses like OpenAI and Anthropic. He notes they face massive capital burn rates and an existential threat from open-source models such as Chinese model and SpaceX that are driving the cost of AI access effectively to zero. A business model reliant on charging for proprietary models will collapse if open-source alternatives are essentially free. $AMZN $META $MSFT $SPCX

In Ackman's latest interview he divides the AI market, stating that it is not a bubble at the foundational layer, but highly risky at the software/model layer. He sees "near infinite demand" for compute. He believes infrastructure providers such as Microsoft, Amazon, Meta, and even SpaceX will earn massive returns on their data center investments. He is highly skeptical of pure model layer businesses like OpenAI and Anthropic. He notes they face massive capital burn rates and an existential threat from open-source models such as Chinese model and SpaceX that are driving the cost of AI access effectively to zero. A business model reliant on charging for proprietary models will collapse if open-source alternatives are essentially free. $AMZN $META $MSFT $SPCX

CapexAndChill

137,755 Aufrufe • vor 1 Monat

ELON MUSK: "We see a path to putting 100 gigawatts per year of solar-powered AI satellite into orbit. And having this be actually the lowest cost way to power and operate AI at a very large scale For reference, the United States consumes roughly 460 gigawatts on average per year. Because the average power load in the US is 460 gigawatts"

ELON MUSK: "We see a path to putting 100 gigawatts per year of solar-powered AI satellite into orbit. And having this be actually the lowest cost way to power and operate AI at a very large scale For reference, the United States consumes roughly 460 gigawatts on average per year. Because the average power load in the US is 460 gigawatts"

X Freeze

9,044,720 Aufrufe • vor 9 Monaten

The reason $PLTR has pulled back this year is that it has gone from being viewed as THE AI application winner to AN AI application winner which is a one-letter shift that has completely changed how the market values the stock. At its peak, investors paid nearly 200x earnings because Palantir appeared to be the only public software company clearly converting AI demand into accelerating fundamentals. That multiple has since compressed toward 80x as $SNOW, $DDOG, $MSFT and Databricks prove enterprise AI will have multiple winners.

The reason $PLTR has pulled back this year is that it has gone from being viewed as THE AI application winner to AN AI application winner which is a one-letter shift that has completely changed how the market values the stock. At its peak, investors paid nearly 200x earnings because Palantir appeared to be the only public software company clearly converting AI demand into accelerating fundamentals. That multiple has since compressed toward 80x as $SNOW, $DDOG, $MSFT and Databricks prove enterprise AI will have multiple winners.

Shay Boloor

75,400 Aufrufe • vor 15 Tagen

A client accidentally spent $500M in one month on Claude. $16.6M per day. No usage controls. Chamath Palihapitiya on The All-In Podcast EP275: a Fortune-level company failed to set token limits. The bill arrived at end of month. A separate Fortune 20 company is 6 months into a $1B AI-driven OPEX reduction program. $200M in tokens spent. Minimal results. Microsoft is already canceling Claude enterprise licenses. David Sacks calls it a "meme" forming - that token spend is wasteful and the market is overcorrecting. For enterprise AI buyers: the companies building spend-control and measurable-ROI infrastructure now are positioned to capture budget as the backlash unfolds. Full enterprise spend breakdown and what it means for AI vendor pricing power on The All-In Podcast: Source: All-In Podcast -

A client accidentally spent $500M in one month on Claude. $16.6M per day. No usage controls. Chamath Palihapitiya on The All-In Podcast EP275: a Fortune-level company failed to set token limits. The bill arrived at end of month. A separate Fortune 20 company is 6 months into a $1B AI-driven OPEX reduction program. $200M in tokens spent. Minimal results. Microsoft is already canceling Claude enterprise licenses. David Sacks calls it a "meme" forming - that token spend is wasteful and the market is overcorrecting. For enterprise AI buyers: the companies building spend-control and measurable-ROI infrastructure now are positioned to capture budget as the backlash unfolds. Full enterprise spend breakdown and what it means for AI vendor pricing power on The All-In Podcast: Source: All-In Podcast -

Podcast Alpha

31,016 Aufrufe • vor 2 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)

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)

Rohan Paul

84,823 Aufrufe • vor 5 Monaten

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Milk Road AI

280,929 Aufrufe • vor 1 Monat

prediction from Chamath Palihapitiya : 95% of enterprise software running in production today will be rewritten in the next 3 years. AI made rewriting cheaper than maintaining. for 30 years the ROI on rebuilding software was brutal. a 7-figure build. a 2-year timeline. 60% chance of failure. executives chose maintenance every time, even as costs compounded. AI just flipped that equation. the moats that mattered for 30 years in enterprise software are about to collapse. first movers will own the new infrastructure. laggards will be the ones still paying maintenance fees to vendors that can't explain their own code. take a look at your own maintenance line item and ask what an AI-native rewrite would cost instead. reach out to us to learn about what use cases we've solved across healthcare/life science, government, manufacturing, & energy: sales@8090.ai

prediction from Chamath Palihapitiya : 95% of enterprise software running in production today will be rewritten in the next 3 years. AI made rewriting cheaper than maintaining. for 30 years the ROI on rebuilding software was brutal. a 7-figure build. a 2-year timeline. 60% chance of failure. executives chose maintenance every time, even as costs compounded. AI just flipped that equation. the moats that mattered for 30 years in enterprise software are about to collapse. first movers will own the new infrastructure. laggards will be the ones still paying maintenance fees to vendors that can't explain their own code. take a look at your own maintenance line item and ask what an AI-native rewrite would cost instead. reach out to us to learn about what use cases we've solved across healthcare/life science, government, manufacturing, & energy: [email protected]

8090

273,913 Aufrufe • vor 4 Monaten

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 Aufrufe • vor 11 Monaten

Today we’re partnering with AWS to launch Superblocks 3.0: the secure way for employees to vibe code production enterprise software. In a single prompt, Superblocks can replace million dollar SaaS, while IT & Security stay in control. OpenAI and Anthropic are releasing new models with advanced cyber attack capability and vibe coding is every company's achilles heel: > Personal Replit accounts store untracked customer data. > Lovable prototypes with your data open to the public internet. > Claude on the desktop pulls malicious packages. How Superblocks 3.0 works: 1. Superblocks Builds: Import vibe coded prototypes. Model routing picks the best frontier or open source model per task. Saves up to 30% on token costs. 2. Superblocks Secures: A swarm of security agents work like a real human team to find and fix vulnerabilities. 3. Superblocks Deploys: Unlike consumer vibe coding tools that send your data to their cloud, Superblocks deploys the application, database, and AI inference securely inside your private AWS environment. Superblocks 3.0 is trusted across enterprises like Instacart, Benchling, and even banks and social networks with the most stringent security requirements. Book a demo here: Everyone says, “AI is replacing SaaS”, yet find me a Fortune 500 company that has vibe coded its own CRM instead of using Salesforce. That changes today. To celebrate our launch, we're building 1,000 enterprise apps for free. Comment a SaaS tool you hate and why, and we'll reply with an enterprise-grade replacement.

Today we’re partnering with AWS to launch Superblocks 3.0: the secure way for employees to vibe code production enterprise software. In a single prompt, Superblocks can replace million dollar SaaS, while IT & Security stay in control. OpenAI and Anthropic are releasing new models with advanced cyber attack capability and vibe coding is every company's achilles heel: > Personal Replit accounts store untracked customer data. > Lovable prototypes with your data open to the public internet. > Claude on the desktop pulls malicious packages. How Superblocks 3.0 works: 1. Superblocks Builds: Import vibe coded prototypes. Model routing picks the best frontier or open source model per task. Saves up to 30% on token costs. 2. Superblocks Secures: A swarm of security agents work like a real human team to find and fix vulnerabilities. 3. Superblocks Deploys: Unlike consumer vibe coding tools that send your data to their cloud, Superblocks deploys the application, database, and AI inference securely inside your private AWS environment. Superblocks 3.0 is trusted across enterprises like Instacart, Benchling, and even banks and social networks with the most stringent security requirements. Book a demo here: Everyone says, “AI is replacing SaaS”, yet find me a Fortune 500 company that has vibe coded its own CRM instead of using Salesforce. That changes today. To celebrate our launch, we're building 1,000 enterprise apps for free. Comment a SaaS tool you hate and why, and we'll reply with an enterprise-grade replacement.

Brad Menezes

19,455,263 Aufrufe • vor 15 Tagen

Elon Musk says he has mapped out a plan to put a 100 gigawatts per year of solar-powered AI satellites into orbit. “We see a path to putting a hundred gigawatts per year of solar powered Al satellite into orbit, and having this be actually the lowest cost way to power and operate Al at a very large scale. For reference, the United States consumes roughly 460 gigawatts on average per year. We have a plan mapped out to do so. It gets crazy.”

Elon Musk says he has mapped out a plan to put a 100 gigawatts per year of solar-powered AI satellites into orbit. “We see a path to putting a hundred gigawatts per year of solar powered Al satellite into orbit, and having this be actually the lowest cost way to power and operate Al at a very large scale. For reference, the United States consumes roughly 460 gigawatts on average per year. We have a plan mapped out to do so. It gets crazy.”

Nic Cruz Patane

267,484 Aufrufe • vor 9 Monaten

Gavin Newsom’s new software tax goes way beyond corporate softwares, California Democrats are going to tax everything They expect to make over $2 billion per year from this new tax, “They now define pre-written software as everything from Microsoft Office, Gmail accounts, Android operating systems — it has a computer, it has pre-written software. California is now going to tax that. Wow” I put together a list to give you an idea of how far this goes • Microsoft Office / 365 subscriptions • Gmail / Google Workspace • Slack • Workday • QuickBooks / Intuit products • Adobe Creative Cloud / Acrobat • Android operating system licenses (in applicable contexts) • Cloud-based CRM/ERP systems • Accounting/financial software (SaaS versions) • Project management tools (e.g., Asana, Monday. com) • Antivirus/security software (digital downloads/subscriptions) • Productivity suites (e.g., Zoom, Teams) • Database software (pre-written) • Graphic design/photo editing tools (cloud) • Operating system access/subscriptions (where pre-written) • Enterprise software platforms • HR/payroll SaaS tools • Marketing automation software • Collaboration/communication apps • Many mobile/desktop apps sold digitally So basically everything

Gavin Newsom’s new software tax goes way beyond corporate softwares, California Democrats are going to tax everything They expect to make over $2 billion per year from this new tax, “They now define pre-written software as everything from Microsoft Office, Gmail accounts, Android operating systems — it has a computer, it has pre-written software. California is now going to tax that. Wow” I put together a list to give you an idea of how far this goes • Microsoft Office / 365 subscriptions • Gmail / Google Workspace • Slack • Workday • QuickBooks / Intuit products • Adobe Creative Cloud / Acrobat • Android operating system licenses (in applicable contexts) • Cloud-based CRM/ERP systems • Accounting/financial software (SaaS versions) • Project management tools (e.g., Asana, Monday. com) • Antivirus/security software (digital downloads/subscriptions) • Productivity suites (e.g., Zoom, Teams) • Database software (pre-written) • Graphic design/photo editing tools (cloud) • Operating system access/subscriptions (where pre-written) • Enterprise software platforms • HR/payroll SaaS tools • Marketing automation software • Collaboration/communication apps • Many mobile/desktop apps sold digitally So basically everything

Wall Street Apes

320,987 Aufrufe • vor 1 Monat

I was joined by co-host Jesse Kobernick today. We had the pleasure of speaking with Ethan Peck and Scott Shepard of the Free Enterprise Project at the National Center for Public Policy. We discussed Ethan's introduction of the Microsoft $MSFT #Bitcoin Shareholder Proposal, considerations around the specific terms of the proposal, the technical process of getting the proposal in front of $MSFT shareholders, SAB 121, and what viewers can do to make our voices heard both at $MSFT and beyond. We have an incoming red wave. Now is our opportunity to create an Orange Wave and move forward corporate #Bitcoin adoption as a Treasury Reserve Asset. Share this video and Vote Your Shares YES on the Microsoft $MSFT Shareholder Proposal! Here's our conversation with Ethan and Scott. @TheJesseMK

I was joined by co-host Jesse Kobernick today. We had the pleasure of speaking with Ethan Peck and Scott Shepard of the Free Enterprise Project at the National Center for Public Policy. We discussed Ethan's introduction of the Microsoft $MSFT #Bitcoin Shareholder Proposal, considerations around the specific terms of the proposal, the technical process of getting the proposal in front of $MSFT shareholders, SAB 121, and what viewers can do to make our voices heard both at $MSFT and beyond. We have an incoming red wave. Now is our opportunity to create an Orange Wave and move forward corporate #Bitcoin adoption as a Treasury Reserve Asset. Share this video and Vote Your Shares YES on the Microsoft $MSFT Shareholder Proposal! Here's our conversation with Ethan and Scott. @TheJesseMK

Tim Kotzman

44,208 Aufrufe • vor 1 Jahr

MIT's new State of AI in Business report went viral for claiming that 95% of enterprise AI projects fail. But the real story isn't that AI doesn't work — it's just big companies can't build it. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down what the study really says, why in-house enterprise AI efforts keep stalling, and how startups are filling the gap with products that learn, integrate, and actually deliver value. 2:08 - The enterprise AI adoption gap and why the failure rate is high 3:32 - Even Apple can be bad at software 4:30 - Why getting enterprise software to actually work is so hard 11:08 - The Reducto case study 13:39 - The type of enterprise employee you should find as a founder 14:39 - Meet founders who’ve been acquired by enterprises 15:25 - Enterprise/startup tension and symbiosis

MIT's new State of AI in Business report went viral for claiming that 95% of enterprise AI projects fail. But the real story isn't that AI doesn't work — it's just big companies can't build it. On the Lightcone Podcast, Garry Tan, Harj Taggar, Diana, and Jared Friedman break down what the study really says, why in-house enterprise AI efforts keep stalling, and how startups are filling the gap with products that learn, integrate, and actually deliver value. 2:08 - The enterprise AI adoption gap and why the failure rate is high 3:32 - Even Apple can be bad at software 4:30 - Why getting enterprise software to actually work is so hard 11:08 - The Reducto case study 13:39 - The type of enterprise employee you should find as a founder 14:39 - Meet founders who’ve been acquired by enterprises 15:25 - Enterprise/startup tension and symbiosis

Y Combinator

118,795 Aufrufe • vor 9 Monaten

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!

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

CFO/COO Brittany Bagley shared some insights on $AXON a few months ago. Taser now makes up less than 40% of their revenue. They have morphed into a massive software and AI powerhouse. Their software revenue has been growing near 40% YoY into 2026. Almost 95% of their total revenue is tied to sticky subscription plans. They use AI to solve massive police understaffing. They rolled out a product called Draft One. It uses bodycam audio to automatically write first drafts of police reports. This saves understaffed departments up to 12 hours a week per officer. They also added instant push-button language translation right on the cameras. But Axon is not stopping at just software. They are going all in on drone technology. Drones are now acting as first responders to keep officers out of dangerous situations like high-speed car chases. Their acquisitions of Fusus and Dedrone have been allowed them to build a single pane of glass for real-time crime centers. They are aggressively expanding into the enterprise space. Retail workers are now wearing Axon bodycams to de-escalate store conflicts. Their largest single booking ever recently came from an enterprise customer. Bagley is both the CFO and the COO. She actively runs the business. That dual role is a unique edge for capital allocation. Axon recently upsized a massive $1.75B debt raise because investor demand was so high. They are going to use that cash to hunt for more acquisitions. The enterprise upside definitely seems interesting.

CFO/COO Brittany Bagley shared some insights on $AXON a few months ago. Taser now makes up less than 40% of their revenue. They have morphed into a massive software and AI powerhouse. Their software revenue has been growing near 40% YoY into 2026. Almost 95% of their total revenue is tied to sticky subscription plans. They use AI to solve massive police understaffing. They rolled out a product called Draft One. It uses bodycam audio to automatically write first drafts of police reports. This saves understaffed departments up to 12 hours a week per officer. They also added instant push-button language translation right on the cameras. But Axon is not stopping at just software. They are going all in on drone technology. Drones are now acting as first responders to keep officers out of dangerous situations like high-speed car chases. Their acquisitions of Fusus and Dedrone have been allowed them to build a single pane of glass for real-time crime centers. They are aggressively expanding into the enterprise space. Retail workers are now wearing Axon bodycams to de-escalate store conflicts. Their largest single booking ever recently came from an enterprise customer. Bagley is both the CFO and the COO. She actively runs the business. That dual role is a unique edge for capital allocation. Axon recently upsized a massive $1.75B debt raise because investor demand was so high. They are going to use that cash to hunt for more acquisitions. The enterprise upside definitely seems interesting.

CapexAndChill

21,170 Aufrufe • vor 4 Monaten