Silicon Valley Software Group (DBA Motion Enterprises)

SMBs don’t need more AI hype - they need revenue. On December 15 in San Francisco, three founders building AI that actually moves dollars will break down what’s working across hundreds of real SMB workflows heading into 2026. Our founder, Matthew Kael Swanson will show how SMBs are scaling revenue by staffing sales and marketing teams with AI employees that operate as 1099 contractors. Joining him: • Vadim Rogovskiy 🇺🇦, Founder & CEO of EVE — AI that prevents revenue from leaking out of inboxes by spotting buying signals and drafting replies 24/7 • Ludovic Granger, CEO of Leadbay (YC F25) — domain-specific AI uncovering high-intent SMB leads that CRMs can’t see Moderated by Peter Kovacs — post-exit founder, executive coach, and Bay Area chapter lead of the PEF Community. Expect a sharp, honest, no-fluff conversation. You’ll walk away with: 🟣 2–3 funnel spots where AI can add revenue in Q1 🟣 3–5 tested workflows you can deploy in under 30 days 🟣 A clearer blueprint for protecting margins without expanding headcount 🟣 New connections with operators tackling identical challenges If you’re in the Bay Area and responsible for revenue, ops, or CX, this is the one to show up for. 🔗 Register: https://luma.com/cvxjketr

Most CEOs I speak with are still thinking of AI as a tool, but the real value unlock comes when AI fully automates the work of an employee. Not one task but the entire job. Enter Mark Elliott, Founder & CEO of Opportunity South Carolina. Next Wednesday (Dec 10, 2-4pm PST), he will share how his company has scaled their sales and marketing team by hiring AI employees that have generated over $2M in pipeline. I'm excited to be moderating this session along with the Alliance of Chief Executives where we'll be covering the following topics: - What roles can be fully automated with AI employees - Live examples of sales and marketing AI employees in action - How to align AI employees with revenue outcomes Request to join via the registration link in the comments.

Here is a fun analogy for the AI/web3 nerds out there: AI is to Web3 as embeddings are to tokens (AI : Web3 :: embeddings : tokens) To unpack the analogy, consider an Amazon warehouse. GenAI without web3 is like a robot without a quantifiable purpose — able to reason like a savant but without measurement of what “good” is. Similarly web3 without GenAI is like an amazon warehouse without robots — providing all the instructions needed for an elegant warehouse layout but missing the actors to move the boxes around and decide where to place each asset to maximize value. Each alone offers incremental improvement. Together they provide a new fabric for a technology supercycle. 🤖 GenAI Most enterprise AI use cases today are using traditional predictive analytics. To get into the core workflows that allow for “AI employees”, enterprises will need to tokenize their digital assets into “embeddings”. These embeddings will replace the traditional row/column database tables that underpins all modern day software. Without embeddings, AI agents devolve into clunky frankensteins due to the way databases break the customer profile into discrete rows and columns. With embeddings, AI agents can see a much closer representation of the customer’s domain. To put another way, think of embeddings like fragments of DNA that allow an AI agent to assume the context of any individual (or object), allowing the agent AI agent to talk and act like a specific customer. 🪙 Web3 On the other side of the coin, embeddings allow us to rethink units of value in the enterprise. For example, once we can “tokenize” marketing content into embeddings, we can then assign web3 instructions to the embedding and begin to do all sorts of novel business processes. We can begin tracking the attribution to a closed sell (i.e. did the MQL convert into a sale because of the ad or because of the webinar?). Similarly we can start attributing value to the individuals on the marketing team who are generating the content leading to the eventual revenue event. The current way of compensating the team responsible for generating MQLs leads to perverse behaviors and noisy funnels. Tokenized assets allow creators to be recognized for the specific assets that lead to revenue outcomes (and share in the upside). 🤖 + 🪙 Putting it all together GenAI and Web3 have been operating as separate ecosystems. At MotionERP, we see these technologies converging as two sides of the same coin. We are hiring like crazy with some exciting updates we’ll be sharing soon. Here are some of our most pressing roles: 🔴 Graph Architect - Our AI employees rely on the Motion Graph to understand the world. Your job is to scale our proprietary ontology. 🟢 AI Agent Architect - Design and develop the reusable tools and components that each AI employee uses to get work done. 🔵 Forward Deployed CTO - Help teach our AI employees how to wrangle enterprise data. See link in comments for more info.

🚀 Event Announcement: Scaling businesses with AI agents: Throwing out the SaaS Playbook We’re excited to share that our Founder & CEO, Matthew Kael Swanson, will be speaking at the Entrepreneur Cooperative (ECo) Quarterly Meeting on Monday, October 28th at 4:00 PM CST. As GenAI reshapes how companies operate, Matthew will discuss how this new wave of technology is forcing founders to rethink the traditional SaaS playbook, from organization design to compensation. In this session, Matthew will share: 🤖 What roles can be automated with AI employees 🏗️ How to design an org chart to scale with AI employees 💰 Compensation strategies to align AI employees with the rest of the workforce This is the final ECo session of the year, bringing together founders, CEOs, and post-exit leaders ready to build in the GenAI era. We’re grateful to the Entrepreneur Cooperative team for hosting this incredible community of builders and innovators. #AI #Entrepreneurship #MotionERP #AIgents #Founders #Scaling #ECo #FutureOfWork

Last week week the MotionERP team had our first onsite in San Francisco. Our concluding event was an IMAX showing for the opening night of Tron Ares. Here is a personal anecdote of the significance and a roll call for fellow futurists. I remember watching the original Tron as an 8 year old. Sitting on the living room floor, staring up at the screen, seeing personified digital characters defy the bounds of physical embodiment — confined only by their virtues and vices. I was hooked. I picked up my first programming book and my life ever since has been, in one way shape or form, a pursuit of that awe struck feeling of purpose. Fast forward and at 40 I have the fortune to work on a third attempt at creating AI that helps us probe our humanity. The team in this photo constitute “Block 1”. All former founders with similar origin stories. Our shared value is to “embrace change” by challenging seemingly obvious conventions: Is a GUI the best way to show a user data? Is it possible to scale custom pricing? Is a database field the best way to store information? We are hiring like crazy. Not crazy in the traditional sense of a large number of employees, but rather crazy in the types of roles we are looking for. If you are a former founder or early stage leader and you can make sense of one of the following roles, please reach out: ⚫ Token Architect (Head of Finance) - Your job is to tokenize our outcome based customer contracts and design mechanisms for token allocation to employees and investors. 🟢 Forward Deployed CTO - We need 2 more CTOs who can teach our AI employees how to wrangle enterprise data. 🔴 Graph Architect - Our AI employees rely on the Motion Graph to understand the world. Your job is to scale our proprietary ontology. 🔵 AI HR Manager (Head of Customer Success) - Help coach our AI employees on how to be more empathetic with their human counterparts. *** Back at the Tron showing, as we enjoyed the flick, an army of our AI employees were working in the background helping our customers disseminate their values (as measured in currency). For the 8 year old dreamer in all of us, come help create AI that empowers creators 🤖 (DM to learn more about open roles) Eric Dunn Bruce Sinclair Srivatsan Padmanabhan Bill Katsak

I started my first AI SaaS startup in 2010. Here are notable differences as I work on my third in the post GenAI era: ** 1) Scaling ** In previous ventures, we had allotted a significant portion of our funding to sales and marketing headcount after we reached our first 5 enterprise clients. As we transition from pilots to production at MotionERP its much different. We have 1 (superstar) person managing our sales and marketing team of AI agents. This translates to an 80% reduction in our S&M expenses compared with prior ventures. Where does the budget go? We can now eat more of our dogfood with a bigger product team 🤖 ** 2) Pricing ** Selling SaaS at my previous two AI companies was always a battle for attribution. No matter the approach (usage, seats, etc) we were always detached from direct line items in the P&L. Now that our product is labor (AI employees), the pricing challenge has been greatly simplified. We are doing the entire work of junior staff whose expenses are visible to management. That was not possible when AI was a tool, and by automating an entire job junction we can now charge on outcomes which is much more lucrative. ** 3) Product ** Personally, this is the change that I’m most passionate about. I began coding at an early age. Somewhere along the way I started to lose my humanity. Everything I created had to fit into boxes. From the database schema on up, my best product designs always had this limitation. Now, our AI agent platform has liberated us from the row/column dilemma. With embeddings we can bypass artificial structures and let LLMs talk back and forth with the raw inputs of our customers. No more clunky UI, I can finally create a product that talks! GenAI is ushering in new operating models for businesses allowing us to rethink how to scale and deliver value to customers. What's one way you are running your business differently with AI?