1st money in. Investing 150+ early stage, capital efficient B2B startups per year. ex-Microsoft ex LinkedIn. 🇺🇸

Silicon Valley | Vancouver
Joined October 2009
Put me on the waitlist. I need one to keep my westie company
SITUATION DETECTED: Warhound launched from stealth today with a $200M seed at a $1.2B valuation. Ben Lamm and Palmer Luckey are cloning gene-edited bio-enhanced dogs and equipping them with custom Anduril vests, goggles, and sensors for the military and law enforcement.
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John Eng (Right Side Capital) retweeted
BREAKING: @noxmetals, the YC-backed manufacturing startup, says it has reached a $25M annualized revenue run rate in less than a year. The Detroit-based startup is automating metal cutting and supply for the American industrial base.
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John Eng (Right Side Capital) retweeted
TLDR; we will probably never get another ARR number from Anthropic, which is healthy. Should force the market to move away from extreme focus on Anthropic/OpenAI ARR numbers to hyperscale growth rates, which are a much better metric for AI at this point given they capture Muse, Grok, Gemini and Open-Source. Anthropic FCF positive in Q3 and reaccelerating in October on Opus 5.5 per third party data. Roadshow in several weeks will happen after this has been widely confirmed. Unit economics much better than expected given positive FCF with 75% of their compute going to training. All per public reporting.   OpenAI continuing to grow at the same pace per Sarah Friar interview after they took share vs. Anthropic in Q3. Means the sum of Anthropic/OpenAI growth is accelerating from the Q3 pace. OpenAI probably hits FCF positive in the next few months.   Open-source growing much faster than either Anthropic or OpenAI. Modal tripled since May and is 15x YoY per yesterday’s announcement. Open-source tokens generate more revenue and profit for the hyperscalers/neoclouds than frontier tokens. *Every* open source inference cloud I am aware of is growing faster both sequentially and YoY than either Anthropic or OpenAI. And their combined compute spend is becoming material.   Third party data pointing to hyperscalers continuing to accelerate in Q3. All report in the next two weeks. Acceleration should continue in Q4 and Q1 as installed base of compute slowly reprices higher closer to spot and new capacity comes online at higher prices. Continued acceleration in hyperscalers should help address external funding concerns.   10 year yield down in a straight line over the last 24 hours.   Some risk of escalation in Iran next few days, but earnings and mid-terms probably outweigh taking an ultra long-term view and looking out 30 days.   Biggest risk imo remains cyber and OpenAI/Anthropic dominating the model layer. Fragmentation, competition and lower margins at the model layer are good for everyone else in the ecosystem and for America. Slower for longer is much better than an overbuild and an actual bubble.
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Great post. Scary. Exciting.
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!
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Martin is a great advocate for his portcos
If you would rather have investors who actually care if you succeed. HMU.
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John Eng (Right Side Capital) retweeted
Curious about the Forum Ventures accelerator program? Join us LIVE this Wednesday at 4pm ET / 1pm PT for an AMA with our Head of Platform Leandra Elberger. Register here -- luma.com/yih5qaen
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Sunday evening. My favorite time at the gym.
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How is San Jose on this list? And not Vancouver BC?
New York City was just ranked the best city in the world.
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John Eng (Right Side Capital) retweeted
New York City was just ranked the best city in the world.
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I can watch this all day
Carrier Ronald Reagan outbound off Mutiny Bay, Whidbey Island.
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I'm starting the UFC but for tech founders and their VCs. Four fighters in the octagon. Who wants to back this?
You are a struggling second tier competitor that is more unethical and lying just because you have no decency or sense of proper behavior and shows your desperation. Straight out lying about if Chris being fired I thought would be below even you.
Readers added context they thought people might want to know
Khosla is an investor in both Cognition and Factory. khoslaventures.com/category/enter…
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John Eng (Right Side Capital) retweeted
We are excited to announce that World Labs is joining @AMD. The research and technical breakthroughs we have achieved since our founding in 2024 have given us a clear vision for AI’s potential to solve problems in the spatial and physical world. Accelerating the future of spatial and physical intelligence requires scaling our efforts, scaling our reach, and getting closer to the hardware.
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John Eng (Right Side Capital) retweeted
Andrew Ng just dropped the best 2-hour course on Graph Engineering: from single agent to full automation 9:14 - your first agent 33:11 - loop engineering 1:02:46 - graph engineering 1:30:15 - agents that rewrite themselves 1:49:05 - full graph system two hours, and it replaces every agent tutorial you bookmarked this year Prompts → Agents → Loops → Graphs most people will stop after the first agent and call it automation he saves the last forty minutes for the graph that runs it without him same model, same tokens, completely different week watch it today the step-by-step guide is below, save it while it is still early ↓
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John Eng (Right Side Capital) retweeted
News: We’re moving NFX to self-funded. Taking it private. No more external LP’s after fund IV. The four GP’s stay intact. 8 more big seed investments to make in Fund IV, so hit us up. After that, we'll be doing $100K - $3M investments w/ our own money. Thanks to @homebrew who led the way! @NFX @GigiLevy @peteflint @omri_drory nfx.com/post/self-funding-nf…
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John Eng (Right Side Capital) retweeted
a YC partner who closed millions in founder-led sales just laid out her 8 rules for cold email
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John Eng (Right Side Capital) retweeted
Hiring across the Right Side Capital Management portfolio this week — 300+ open roles at 45 companies. → Finni Health (YC W23) — 111 roles, mostly clinical (BCBA, RBT, BT) across 18 states, plus Chief of Staff, FP&A Manager and Credentialing Manager → Gloss Genius — 23 incl. Growth Lead, Staff Software Engineer (Backend), Senior Engineering Manager, Infrastructure → Narmi— 13 incl. VP of Product, VP Finance & Accounting, Head of Design: jobs.gem.com/narmi → Novo — 12 incl. Lead DevOps Engineer, Senior PM (Banking), Staff Product Designer: jobs.ashbyhq.com/novo → Order.co — 11 incl. Principal Applied AI Architect, Staff Applied AI Scientist, Staff Security Engineer → Fitnescity Health — 11 incl. VP of Engineering, Head of Operations, BD Manager: fitnescity.com/jobs-sec → Fireflies.ai — 10 incl. Security Engineer, Full Stack Engineer, AI-Native Performance Marketer: jobs.gem.com/fireflies → Motion — 9 incl. Senior Software Engineer (Backend), Executive IC Engineering, Mid-Market AE: jobs.gem.com/motion → Push Operations — 8 incl. Full Stack Engineer II, Software Engineer (Testing), Payroll AE → Pryzm — 6 (Forward Deployed Engineer, Deployment Strategist, BDR): jobs.ashbyhq.com/pryzm → Akia — 5 (Enterprise AE, CSM, Director of Sales, Software Engineer): akia.com/careers → Nuel — 5 (Lead Data Scientist, Senior Full Stack, Front End, Back End): wellfound.com/company/nuel → Lumi AI — 5 (AE, BDR, Full Stack Engineer, Value Engineer) → Instant Teams — 10+ remote customer-care and leave-management roles: instantteams.com → Faber Technologies — 4 (Project Manager and Estimator in Calgary, Account Manager in Edmonton, Accounting Manager) → Branch, Datch, HAAS Alert, People Data Labs, Root Access — 3 each → First Arriving, Ground News, Inscribe AI, Outlast, Pavilion, Testlio, Maya AI, Social Cascade — 2 each → One role each: Alloy, ALETHIA AI, AIcelerate AI, Community Benchmark, Droplet, FloatMe, Fyrii, Healthie, Importal, Last Lock, Quickpage, Sware, TCARE, Trust & Will, Velou
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John Eng (Right Side Capital) retweeted
Tomorrow: RSCM Managing Director Dave Lambert will do a live pitch deck teardown with @HubSpotForStartups. 3 founders, 5 min to pitch, 10 min of real feedback — live, no filter. Joining Dave: George Damouny (Plug and Play Ventures) + Georgie Smithwick (Techstars Ventures) + Dan Gallagher (HubSpot). Watch here: offers.hubspot.com/live-pitc…
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John Eng (Right Side Capital) retweeted
A few thoughts on the current state of venture capital. When the Music Is Playing In July 2007, a few weeks before the credit markets seized up, Chuck Prince, then the CEO of Citigroup, gave an interview to the Financial Times. The line everyone remembers is this one: "As long as the music is playing, you've got to get up and dance." He was mocked for it for years afterward, and he lost his job a few months later. But I have come to think he was saying something honest. He wasn't claiming the music would play forever. He was admitting that he couldn't sit down while it was still going, and neither could anyone else in his seat. I've been thinking about that quote a lot lately, because right now is the most disorienting period in venture capital I can remember, and I have been doing this for a while. Here is what makes it disorienting. It's not that things are bad. Some things are spectacular. We have companies in our portfolio growing faster than anything I have seen in my career, and I don't say that lightly. At the same time, we have companies with no revenue, no product, and a founding team you could fit in a conference room raising billions of dollars at valuations of $10 to $50 billion. Both of these things are true at once, and if you try to reason about them with the same framework you will drive yourself crazy. Two ideas have helped me make sense of it. Neither is mine. The first is reflexivity, which George Soros has been writing about since the 1980s. In most of life, perception follows reality: the weather is what it is, and your opinion of it changes nothing. In markets, it runs the other way too. Prices change what participants believe, and what participants believe changes the prices. The feedback loop can run for a long time, and while it's running it looks exactly like progress. Here is how reflexivity is playing out in AI. Full disclosure: Menlo is an investor in Anthropic, so read the following with that in mind. People watched a frontier lab go from a $4 billion valuation to $18 billion, then $60 billion, then $180 billion, then $380 billion, and now something close to a trillion. They drew the obvious conclusion: that is what a neo lab looks like. So the next neo lab gets priced off that path, not off anything it has built. Then it gets marked up in a subsequent round, and the markup itself becomes the proof. Look at Thinking Machines. Look at Reflection. At that point valuation has stopped being an output of the metrics and has become the metric. Nobody is discounting cash flows. They are discounting the last round. Soros is very clear about one thing, and it's the part people skip: you cannot know when or how a reflexive process ends. You only know that it does. Every one of them has. The second idea is Chuck Prince's, and it explains why smart people keep dancing even when they can see the loop for what it is. As far as I can tell, there are two groups on the dance floor. The first group got in early. Firms like ours were in some of these AI companies before the numbers got silly, and the paper gains are enormous. When you are sitting on gains like that, you start to feel like you're playing with house money. I have been around long enough to know that house money is the most dangerous kind, because you don't respect it the way you respect money you had to earn. The second group missed the early rounds and knows it. Their LPs know it too. So they are trying to make up for lost time by writing very large checks very late, which is the one strategy almost guaranteed to turn a missed opportunity into a real loss. House money on one side, FOMO on the other, and reflexivity feeding both. That's the whole story. Everyone has a reason to keep dancing, and the reasons are different, which is why nobody can talk anyone else off the floor. So what do you do? The instinct in our business is to answer with company identification: just pick the right neo lab and you'll be fine. I think that's the trap. When price has become the signal, being right about the company is not enough, because you can be right about the company and still be wrong about the price by a factor of ten. The public-market investors I admire figured this out a long time ago. They spend as much time on how much to own as on what to own. The winners in venture over the next decade will be the firms that treat portfolio composition and position sizing as seriously as they treat sourcing. How much of the fund is in companies whose valuation rests on the last round rather than on revenue? What happens to the portfolio if the reflexive loop breaks next year instead of in five? Those are not exciting questions. They are the ones that will matter. The music will stop. It always does. Dance if you must, but know where the chairs are.
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