Did you guys listen when I told you to buy $CRDO? The stock is now up massively from where I first started buying and it’s up another 8% today. You can check out my entire portfolio and see exactly what I’m buying here.

Another SaaS sell off is just inevitable at this point because of the rise of AI agents. Goldman Sachs expects the software profit pool to shift heavily toward AI agents, with the agent market growing to more than $50 billion by 2030 while traditional SaaS falls from roughly $30 billion to around $20 billion. This does not mean software is disappearing but the overall market could actually become larger, but more of the money is expected to move away from traditional SaaS products and toward the agents operating them. Today, businesses pay monthly fees for employees to use Salesforce, ServiceNow, Workday and dozens of other applications but agents can move across those applications and complete the work themselves. Instead of opening several programs, the user simply explains the desired outcome. The agent becomes the main interface, while the software underneath turns into a tool working quietly in the background. This puts pressure on the traditional per seat model because companies may not need as many employees actively using each application. It also weakens customer lock in because users become more loyal to the agent than to the software it operates. Yes, I know many large software companies now offer usage based pricing alongside their legacy seat based models. That should help them adapt as customers move toward paying for completed work rather than software access but the market rarely makes that distinction during a major sell off. If investors begin dumping SaaS stocks because they fear AI agents will weaken seat growth and pricing power, even the strongest software giants will probably get grouped into the same trade and sold alongside the weaker companies. We already saw broad software weakness when new agent products raised similar concerns earlier this year. Muse will be the next catalyst because it is bringing personal agents to a much larger audience. Once regular users become comfortable allowing one agent to work across multiple applications, investors will begin questioning how many separate subscriptions and paid seats businesses truly need. OpenAI and Anthropic will likely respond soon their own version of Muse very soon. And once Muse, OpenAI and Anthropic begin competing to control the user’s entire workflow, SaaS companies will no longer compete only against other software products but also compete against the AI agents deciding which software gets used in the first place. Not every SaaS company will lose because those with proprietary data, deep integrations and strong usage based models should be more defensible but if another broad SaaS sell off begins, the market may not care about those differences at first. The weaker companies will fall and the giants will likely get dragged down with them. If you enjoyed reading this, make sure to follow me @MelvinInvests for more and I’ve already started positioning my portfolio around what I think is coming next as AI agents begin reshaping the software stack. If you want to see exactly what I’m holding, what I’m avoiding, and how I’m positioned for this shift, you can check out my full Milk Road portfolio using the link below.

Meta just found the product that turns its massive AI spending into the next great consumer platform. Muse’s daily US downloads recently surpassed 300,000, putting it above Instagram, WhatsApp, Facebook, Threads and Messenger individually and it also reached No. 1 on the US App Store. The reported Meta Pay integration could make Muse considerably more valuable by allowing users to connect cards already stored in Meta Pay and authorize purchases and Meta is also assembling a powerful commerce network around Muse. Stripe’s Link already lets Muse check out at more than one million businesses and can create single use virtual cards for approved purchases at other merchants. Shopify is bringing Shop Pay checkout to Muse across Shopify stores, connecting Meta’s audience with Shopify’s merchants, product catalogs and payment infrastructure. PayPal is also partnering with Meta to enable shopping and checkout across PayPal’s global merchant network. These partnerships allow Meta to connect every stage of online shopping. Instagram and Facebook provide product discovery, Muse handles research and recommendations, Shopify and PayPal provide merchant access, and Stripe or Meta Pay completes the transaction. This could give Meta visibility across the entire customer journey from advertisement to purchase, making its advertising platform even more valuable. Meta could also monetize Muse through subscriptions, enterprise services, API usage and eventually transaction or referral revenue,. The opportunity is becoming more important as Meta expects to spend between $130 billion and $145 billion on capital expenditures during 2026 and Muse provides early evidence that this investment could create a major consumer business instead of only improving Meta’s existing advertisements. Meta already controls social discovery through Instagram and Facebook, communication through WhatsApp and Messenger, and AI assistance through Muse and if Meta Pay becomes the final payment layer, Meta could control the entire path from product discovery to checkout.

Another SaaS sell off is just inevitable at this point because of the rise of AI agents. Goldman Sachs expects the software profit pool to shift heavily toward AI agents, with the agent market growing to more than $50 billion by 2030 while traditional SaaS falls from roughly $30 billion to around $20 billion. This does not mean software is disappearing but the overall market could actually become larger, but more of the money is expected to move away from traditional SaaS products and toward the agents operating them. Today, businesses pay monthly fees for employees to use Salesforce, ServiceNow, Workday and dozens of other applications but agents can move across those applications and complete the work themselves. Instead of opening several programs, the user simply explains the desired outcome. The agent becomes the main interface, while the software underneath turns into a tool working quietly in the background. This puts pressure on the traditional per seat model because companies may not need as many employees actively using each application. It also weakens customer lock in because users become more loyal to the agent than to the software it operates. Yes, I know many large software companies now offer usage based pricing alongside their legacy seat based models. That should help them adapt as customers move toward paying for completed work rather than software access but the market rarely makes that distinction during a major sell off. If investors begin dumping SaaS stocks because they fear AI agents will weaken seat growth and pricing power, even the strongest software giants will probably get grouped into the same trade and sold alongside the weaker companies. We already saw broad software weakness when new agent products raised similar concerns earlier this year. Muse will be the next catalyst because it is bringing personal agents to a much larger audience. Once regular users become comfortable allowing one agent to work across multiple applications, investors will begin questioning how many separate subscriptions and paid seats businesses truly need. OpenAI and Anthropic will likely respond soon their own version of Muse very soon. And once Muse, OpenAI and Anthropic begin competing to control the user’s entire workflow, SaaS companies will no longer compete only against other software products but also compete against the AI agents deciding which software gets used in the first place. Not every SaaS company will lose because those with proprietary data, deep integrations and strong usage based models should be more defensible but if another broad SaaS sell off begins, the market may not care about those differences at first. The weaker companies will fall and the giants will likely get dragged down with them. If you enjoyed reading this, make sure to follow me @MelvinInvests for more and I’ve already started positioning my portfolio around what I think is coming next as AI agents begin reshaping the software stack. If you want to see exactly what I’m holding, what I’m avoiding, and how I’m positioned for this shift, you can check out my full Milk Road portfolio using the link below.

Another SaaS sell off is coming soon and I think the rise of AI agents will be the reason why. Agents like Muse and Grok are bringing AI agents to the consumer market in masses. What was recently experimental technology is becoming something regular people can use to complete real work across their applications. Grok Bot, for example, can operate software through its own cloud computer and continue working after the user steps away. This is a much bigger threat to software companies than a chatbot that only answers questions. Instead of opening Salesforce, ServiceNow and Workday separately, an employee can tell an agent what needs to be done. The agent can then move between those applications and complete the entire workflow. This means the agent becomes the main interface, while the software underneath becomes a tool working quietly in the background. That puts pressure on the traditional SaaS business model. If agents perform more of the work, companies may not need as many paid software seats across CRM, project management and customer support. Agents could also make switching between software providers easier. Once users interact with Muse or Grok instead of the actual application, they become less attached to that software. The agent could choose whichever service offers the best price or performance. That weakens customer lock in. The agent controls the user experience and decides which software gets used, while SaaS companies risk losing pricing power and their direct relationship with customers. We have already seen how quickly investors react to this threat. New agent capabilities from Anthropic contributed to weakness in software stocks earlier this year as the market questioned whether AI would help SaaS companies or replace parts of them. Muse and Grok could cause another sell off because they are making agents available to regular people. I also think this will force OpenAI and Anthropic to respond very soon. OpenAI has already shown where it is heading. Earlier this year, it hired Peter Steinberger, the creator of OpenClaw, to help build its next generation of personal agents. I am sure they are going to release something soon and then Claude will respond with their own version. If Meta, Grok, OpenAI and Anthropic all begin releasing more capable agents, SaaS companies will no longer compete only against other software products. They will also compete against the agents controlling how customers use those products. The most exposed companies will be those selling basic productivity tools, simple workflows and large numbers of employee seats. Businesses with proprietary data, deep integrations and strict compliance requirements should be safer but they too will be affected by this sell off. If you enjoyed reading this, make sure to follow @MelvinInvests for more.

The ad business as we know it is under serious threat and Amazon blocking Meta’s Muse is the perfect example of why. If AI agents become the main interface people use to shop, search and make decisions, the entire advertising funnel starts to break. Instead of going to Amazon, searching for a product, scrolling through sponsored listings and clicking ads, you could simply tell an AI agent what you want and let it compare products, prices and reviews for you. At that point, Amazon risks becoming just another supplier while the AI agent owns the relationship with the customer. Google could face the same problem on an even larger scale. Google makes money because people search for things and businesses pay to appear in front of those searches. But if people stop searching and start telling AI agents to find the best hotel, product, restaurant, flight or service for them, there are fewer searches, fewer clicks and fewer opportunities to show ads. The value starts shifting away from whoever owns the website or search engine and toward whoever owns the AI agent making the decision. That is the bigger reason companies like Amazon have every incentive to fight this. AI agents do not just threaten traffic but rather threaten the entire business model built around controlling what users see before they make a purchase. If agents become the new front door to the internet, advertising as we know it could look completely different.

Another SaaS sell off is coming soon and I think the rise of AI agents will be the reason why. Agents like Muse and Grok are bringing AI agents to the consumer market in masses. What was recently experimental technology is becoming something regular people can use to complete real work across their applications. Grok Bot, for example, can operate software through its own cloud computer and continue working after the user steps away. This is a much bigger threat to software companies than a chatbot that only answers questions. Instead of opening Salesforce, ServiceNow and Workday separately, an employee can tell an agent what needs to be done. The agent can then move between those applications and complete the entire workflow. This means the agent becomes the main interface, while the software underneath becomes a tool working quietly in the background. That puts pressure on the traditional SaaS business model. If agents perform more of the work, companies may not need as many paid software seats across CRM, project management and customer support. Agents could also make switching between software providers easier. Once users interact with Muse or Grok instead of the actual application, they become less attached to that software. The agent could choose whichever service offers the best price or performance. That weakens customer lock in. The agent controls the user experience and decides which software gets used, while SaaS companies risk losing pricing power and their direct relationship with customers. We have already seen how quickly investors react to this threat. New agent capabilities from Anthropic contributed to weakness in software stocks earlier this year as the market questioned whether AI would help SaaS companies or replace parts of them. Muse and Grok could cause another sell off because they are making agents available to regular people. I also think this will force OpenAI and Anthropic to respond very soon. OpenAI has already shown where it is heading. Earlier this year, it hired Peter Steinberger, the creator of OpenClaw, to help build its next generation of personal agents. I am sure they are going to release something soon and then Claude will respond with their own version. If Meta, Grok, OpenAI and Anthropic all begin releasing more capable agents, SaaS companies will no longer compete only against other software products. They will also compete against the agents controlling how customers use those products. The most exposed companies will be those selling basic productivity tools, simple workflows and large numbers of employee seats. Businesses with proprietary data, deep integrations and strict compliance requirements should be safer but they too will be affected by this sell off. If you enjoyed reading this, make sure to follow @MelvinInvests for more.

Nebius just raised GPU prices AGAIN and it is the clearest sign yet that AI compute demand is still outpacing supply. The company is increasing pay as you go prices for Token Factory’s dedicated inference endpoints by 16% to 20% starting October 1. H100 pricing will rise from $4.05 to $4.70 per GPU-hour, H200 from $4.70 to $5.60, B200 from $7.40 to $8.70 and B300 from $8.10 to $9.70. This is separate from the cloud GPU price increase Nebius announced earlier. That earlier change raised standard on demand cloud prices by roughly 17% to 21%, taking the H100 to $4.50 per hour, H200 to $5.40, B200 to $8.50 and B300 to $9.50. Nebius is now charging an additional $0.20 per GPU hour for every comparable GPU inside a Token Factory dedicated endpoint. The difference exists because customers are not merely renting a raw GPU. Token Factory’s dedicated endpoints provide isolated model deployments, reserved capacity, predictable latency, a 99.9% uptime commitment and customer controlled autoscaling. Nebius handles much of the infrastructure required to deploy and operate the model, while customers access it through an OpenAI compatible API. That makes Token Factory a higher value managed service layered on top of Nebius’ underlying GPU cloud. Customers pay more, but they avoid managing clusters, orchestration, scaling, model serving and availability themselves. The new rates therefore show Nebius trying to monetize both layers of its platform. It is raising the price of the underlying GPU infrastructure while also raising the price of the managed inference product built on top of it. That matters because Token Factory can potentially generate more revenue per GPU than simply renting the same hardware as raw compute. A B300 running continuously at the new dedicated endpoint rate would generate approximately $6,984 per month, compared with $5,832 at the old rate, before discounts and assuming full utilization. That is roughly $1,152 of additional monthly revenue per fully utilized B300, or nearly $13.8 million annually across 1,000 continuously running GPUs. The economics are similar across the lineup. At full utilization, the new pricing adds approximately $468 per month for each H100, $648 for each H200 and $936 for each B200. Not all GPUs will run constantly at list price, and large customers can negotiate discounts but the increases demonstrate the potential operating leverage. Most of Nebius’ data center, server and GPU costs are fixed or committed in advance. If Nebius can charge 16% to 20% more for the same installed hardware without suffering a comparable increase in operating costs, much of the additional revenue can flow into gross profit. The fact that Nebius is protecting contracted prices also matters .Existing reservations and previously negotiated contracts will not be affected, meaning the immediate revenue benefit will primarily come from new customers, renewed contracts and flexible pay as you go usage. That limits the near term impact but reduces the risk of angering major customers that already committed to the platform. The company also introduced dynamic spot pricing for preemptible virtual machines earlier today and those prices will automatically move according to available capacity and real time demand for each GPU type and region. Customers can set a maximum price and allow their workload to stop when the spot rate exceeds it, or follow the market price to improve their chances of maintaining access. This gives Nebius three distinct ways to monetize the same GPU fleet. Long-term customers receive reserved capacity and discounted pricing, on demand customers pay more for flexibility, and interruption-tolerant customers bid for spare capacity through the spot market. Token Factory then adds another premium layer for customers who want Nebius to manage model deployment and inference. To me, this is one of the clearest signs yet that demand is still running ahead of supply. If Nebius can continue raising pricing, improve utilization and move more customers up the stack into managed services, the economics of every new megawatt and every new GPU they bring online become significantly more attractive. Bullish on Nebius!

Elon Musk warned that electricity will become the next major AI shortage. He expects today’s silicon shortage to shift toward transformers and eventually electricity as AI, transportation and heating electrify. Here are five under the radar stocks positioned to benefit (Save this).

Both OpenAI and Anthropic say the AI race needs to slow down yet both companies released newer models on the exact same day. Anthropic released Claude Opus 5.5, while OpenAI released GPT-6 Sol and GPT-6 Luna on September 22. Anthropic says Opus 5.5 delivers performance close to its more powerful Claude Fable 5.1 model while costing about 40% less to run than Opus 5. The model is designed for coding, computer use and long professional tasks that require the AI to work independently. OpenAI expanded the GPT-6 family with two cheaper models. GPT-6 Sol is built for difficult coding, research and computer-use tasks, while GPT-6 Luna is designed for faster and cheaper work at scale. OpenAI priced both models 50% below their GPT-5.6 equivalents, making GPT-6 more practical for businesses running millions of AI tasks.9to5mac The same day releases show how intense the competition has become. Both companies may genuinely want more time for safety testing, but neither company wants to give the other one a major advantage. If Anthropic slows down while OpenAI continues releasing models, OpenAI can win more developers and enterprise customers. If OpenAI slows down while Anthropic keeps moving, Anthropic can do the same. This creates a race in which both companies want everyone to slow down but neither company wants to slow down first.

The ad business as we know it is under serious threat and Amazon blocking Meta’s Muse is the perfect example of why. If AI agents become the main interface people use to shop, search and make decisions, the entire advertising funnel starts to break. Instead of going to Amazon, searching for a product, scrolling through sponsored listings and clicking ads, you could simply tell an AI agent what you want and let it compare products, prices and reviews for you. At that point, Amazon risks becoming just another supplier while the AI agent owns the relationship with the customer. Google could face the same problem on an even larger scale. Google makes money because people search for things and businesses pay to appear in front of those searches. But if people stop searching and start telling AI agents to find the best hotel, product, restaurant, flight or service for them, there are fewer searches, fewer clicks and fewer opportunities to show ads. The value starts shifting away from whoever owns the website or search engine and toward whoever owns the AI agent making the decision. That is the bigger reason companies like Amazon have every incentive to fight this. AI agents do not just threaten traffic but rather threaten the entire business model built around controlling what users see before they make a purchase. If agents become the new front door to the internet, advertising as we know it could look completely different.

Nebius just turned its spare GPU capacity into a live auction. Starting October 8, the price of its preemptible virtual machines will change based on real time demand, available capacity, GPU type and region. Previously, Nebius set a fixed discount for these machines but under the new system, prices can fall when Nebius has extra GPUs available and rise when demand becomes stronger. Customers can either follow the changing market price or set the maximum price they are willing to pay. If the spot price rises above a customer’s limit, Nebius can stop that virtual machine and give the capacity to someone willing to pay more. Nebius is making this change because dynamic pricing allows Nebius to lower prices when demand is weak, attract extra workloads and keep more of its expensive infrastructure running. When demand becomes stronger like right now, Nebius can raise the spot price instead of continuing to sell scarce capacity at a fixed price. This could improve both utilization and revenue because Nebius can fill otherwise idle GPUs while charging more whenever customers begin competing for limited capacity. Bullish on Nebius and if GPU demand stays this strong, dynamic pricing gives $NBIS another lever to squeeze more revenue and higher margins out of every GPU it already owns.

Elon Musk warned that electricity will become the next major AI shortage. He expects today’s silicon shortage to shift toward transformers and eventually electricity as AI, transportation and heating electrify. Here are five under the radar stocks positioned to benefit (Save this).

The bull run is just getting started and SAVE this post so you can come yell at me if I am wrong. In midterm election years, October has historically been the S&P 500’s best month, averaging a 3.0% gain and finishing higher 73.7% of the time. November has been the second best month, averaging 2.7% with a positive return nearly 79% of the time. Seasonality is never guaranteed but the market is about to enter its strongest historical window. The bigger reason for my optimism is that overall AI demand continues to move higher. AI is expanding beyond basic chatbots into coding, video, search, business software, and agents capable of completing entire tasks. Muse is great recent example of that transition and the early usage numbers are honestly pretty crazy. Wells Fargo noted today that Muse’s US downloads and daily active users have been accelerating over the last few days and are already tracking above other major AI apps at the same point after launch. Muse set a new US download record on September 19 with 264,000 downloads, marking its third straight day above 200,000, while daily active users reached roughly 448,000 just 10 days after launch. For comparison, ChatGPT did not surpass 200,000 U.S. downloads until roughly a year after launch and took 49 days to reach around 450,000 US daily active users. Muse is also seeing strong early user feedback, with a 4.66-star average rating over the last 30 days and 87% of reviews coming in at five stars. This all just means that AI usage is accelerating and that demand eventually moves through the entire infrastructure supply chain. More AI usage requires more GPUs, advanced memory, networking equipment, storage, cooling, electricity and data center capacity. Anthropic’s expected IPO could add another major catalyst. Reuters reports that the company could begin marketing its offering in mid October, with a possible listing before the November midterm elections, although the schedule remains subject to change. A successful offering could bring even more attention and capital into AI while creating a new public valuation benchmark for the industry. This could be very similar to what we saw during SpaceX IPO and with all of the Space stocks running up leading to their IPO. The macro picture is not perfect but greater clarity could be coming. Fed Chair Kevin Warsh has remained focused on restoring price stability, and a credible Fed can help reduce long term uncertainty even if that requires some short term discipline. The market does not need every problem to disappear but rather needs confidence that inflation is moving in the right direction and that policymakers have a clear plan. Buckle up, we are going higher. If you enjoyed reading this make sure to follow me @MelvinInvests for more.

Meta’s Muse agents are about to ignite the next CPU boom (Save this). The more tasks these agents complete, the more CPU power Meta will need to run them. Here are the five stocks positioned to win from this.

Meta’s Muse agents are about to ignite the next CPU boom (Save this). The more tasks these agents complete, the more CPU power Meta will need to run them. Here are the five stocks positioned to win from this.

Wall Street’s earnings forecasts are exploding higher and the market is nowhere near finished (Save this). Analysts usually begin with optimistic forecasts and gradually lower them as reality catches up but this time, the exact opposite is happening. Goldman Sachs chart shows that global earnings estimates for 2026 have risen from roughly $52 per share to more than $61 per share. The 2027 estimate has increased even faster, rising from approximately $56 per share to more than $71 per share.. These increases are unusual because earnings estimates for most previous years moved sideways or lower as the year approached and the increases for 2026 and 2027 suggest that companies are earning considerably more money than analysts expected. So why this all happening? it's because of AI is one of the biggest reasons for this earnings growth. Goldman Sachs estimates that global AI investment will exceed $1 trillion in 2026, with approximately $581 billion of that spending occurring in the United States. This money is flowing into semiconductors, memory, networking equipment, cloud infrastructure, data centers, cooling systems and power equipment. The spending cycle also appears to have more room to run because Goldman Sachs expects global AI investment to increase from 0.9% of global GDP in 2026 to 1.3% in 2027 and 1.4% in 2028. The bank also estimates that hyperscaler capital spending could reach approximately $1.1 trillion in 2027, compared with Wall Street’s forecast of roughly $920 billion. This continued investment helps explain why the 2027 earnings line is rising so quickly. The growth is also beginning to spread beyond the largest American technology companies. Companies that provide chips, memory, electricity, construction, networking and cooling equipment are earning more money as the AI infrastructure buildout expands. This is important because a bull market becomes stronger when earnings growth spreads across more sectors, countries and companies. This is why I’m still comfortable staying heavily exposed to AI and infrastructure names. Earnings expectations are not rolling over, they’re still moving higher. If you want to see the positions I’m holding and the trades I’m making around this trend, check out my Milk Road Pro portfolio below.

Everyone was clowning Mark Zuckerberg and Alexandr Wang but now they are back on top. Meta spent more than $14 billion to bring @alexandr_wang and several Scale AI researchers into the company after the disappointing release of Llama 4. Many people questioned whether Wang had enough experience to lead one of the world’s largest AI teams and nvestors also worried that @finkd was spending too much money without having a clear plan to earn it back. But now that narrative is completely dead after Meta’s new Muse AI agent reached No. 1 on Apple’s US App Store shortly after its launch and moved ahead of ChatGPT. Meta offers Muse for free but users who need more access can pay $20 or $100 per month which means that Meta finally has a consumer AI product that could turn its massive infrastructure spending into direct revenue. Oppenheimer estimates that Muse could eventually reach 1.91 billion users across Meta’s applications and If only 6% of those people become paying subscribers, Meta would have approximately 115 million paying Muse customers. Those customers could generate approximately $27.5 billion in annual revenue at a monthly price of $20 and Oppenheimer estimates that this revenue could produce approximately $22 billion in operating income. This scenario would increase Meta’s total 2027 revenue to approximately $332 billion and its operating income to more than $122 billion. Meta’s earnings could reach $38.83 per share, which would be 15% above the Wall Street estimate used in Oppenheimer’s model. Meta has an advantage that most other AI companies do not have. Meta already owns Facebook, Instagram, WhatsApp and Messenger, which gives the company a direct path to billions of potential Muse users. Meta does not need to build a new audience because it can place Muse inside the applications people already use every day. The company could eventually connect Muse to its AI glasses, which would allow users to access the agent without opening a phone or computer. Meta could also make money from consumer subscriptions, business agents, developer access and commissions from purchases completed through Muse. Meta is an asset I hold in my portfolio, and if you want to see the rest of my positions, how I’m sizing them, and the trades I’m making across AI, check out my Milk Road Pro portfolio using the link below.

Everyone was clowning Mark Zuckerberg and Alexandr Wang but now they are back on top. Meta spent more than $14 billion to bring @alexandr_wang and several Scale AI researchers into the company after the disappointing release of Llama 4. Many people questioned whether Wang had enough experience to lead one of the world’s largest AI teams and nvestors also worried that @finkd was spending too much money without having a clear plan to earn it back. But now that narrative is completely dead after Meta’s new Muse AI agent reached No. 1 on Apple’s US App Store shortly after its launch and moved ahead of ChatGPT. Meta offers Muse for free but users who need more access can pay $20 or $100 per month which means that Meta finally has a consumer AI product that could turn its massive infrastructure spending into direct revenue. Oppenheimer estimates that Muse could eventually reach 1.91 billion users across Meta’s applications and If only 6% of those people become paying subscribers, Meta would have approximately 115 million paying Muse customers. Those customers could generate approximately $27.5 billion in annual revenue at a monthly price of $20 and Oppenheimer estimates that this revenue could produce approximately $22 billion in operating income. This scenario would increase Meta’s total 2027 revenue to approximately $332 billion and its operating income to more than $122 billion. Meta’s earnings could reach $38.83 per share, which would be 15% above the Wall Street estimate used in Oppenheimer’s model. Meta has an advantage that most other AI companies do not have. Meta already owns Facebook, Instagram, WhatsApp and Messenger, which gives the company a direct path to billions of potential Muse users. Meta does not need to build a new audience because it can place Muse inside the applications people already use every day. The company could eventually connect Muse to its AI glasses, which would allow users to access the agent without opening a phone or computer. Meta could also make money from consumer subscriptions, business agents, developer access and commissions from purchases completed through Muse. Meta is an asset I hold in my portfolio, and if you want to see the rest of my positions, how I’m sizing them, and the trades I’m making across AI, check out my Milk Road Pro portfolio using the link below.