Simon Arkell

@Hertz 15 minutes to check out of the parking area after getting my car. No wonder you’re getting killed by Uber. 4 barcode VIN scans.

Super excited to close a seed round in this environment for @RyghtAI. We have created an AI digital twin of every clinical trial site in the world and changing the game for sponsors and CROs needing the best sites for their trial fast. We also automate documents and research.

@StokeyyG2 Mondo

Who is the actual goat of their sport? Like no one comes anywhere near 2nd to the first guy

Delighted to keep adding major academic medical centers to the @RyghtAI Research Network. Clinical trial sponsors and CROs now access tens of thousands of sites around the world, including major partners like this with #AgenticAI driving real time selection and fast activation.

AI Agents will be the biggest shift to enterprise software business models that we've ever seen. The typical business model of enterprise software has generally been that one user on the system equals one licensed seat. This model is obviously logical in a world where most users get roughly the same amount of value from each license of the software. But it's also had the limiting effect where your TAM is naturally constrained by the employee headcount tied to the particular use-case of your customer. Historically, this has meant that the only solution to growth is going after larger and larger seat-based categories of software. There are exceptions recently in vertical SaaS that have made a killing on flipping the trend, but even they get TAM-limited too soon. In a world of AI Agents, clearly this is going to be very different. Agentic workflows have no upper limit on how much they can be deployed by an enterprise. And all of a sudden the software categories that were once constrained by seat volume, have no such limits anymore. We're already seeing examples of AI Agents in coding, research, legal work, and other advanced categories that are being billed at multiples of their prior seat-based software equivalent price. This provides a completely new growth vector for software companies in AI, and has major implications to software business models. For a wide number of use-cases, there may be little to no connection between the number of users on a platform and the total amount of usage of AI Agents that use the software -- and what the value is that those Agents can deliver. And for many use-cases, the idea of a user seat being tied to the agentic workflow altogether is unnecessary when agents are just running around completing work in the background for an enterprise. We're still very early in discovering how this will ultimately evolve, and a big open question will be how the industry lands on the units of measurement of these AI Agents. AI Agents may logically be represented by a single agentic user performing an action in a system (like a superuser of the platform), but there's little architectural difference between having 100 agents complete one action a minute vs 1 agent completing 100 actions a minute. No matter the ultimately pricing construct -- which will likely have to correlate to the amount of output the AI Agents are producing -- it's clear that this will lead to a TAM increase in software. Very exciting times ahead.

@RichardSocher I had no idea you invented prompt engineering. Legend status!

As a long-time researcher and German I used to be skeptical of what I thought were overly optimistic predictions and AI timelines. Even as I've pushed AI & NLP research forward and invented prompt engineering in 2016/18, I assumed things would move slower. While, over the last 5 years, almost all my predictions still turned out to be right, I started to realize that having constructive optimism is a competitive edge. Believing we can push AI towards AGI is a massive advantage.

@gregisenberg No argument here.

SaaS is being dismantled as we speak! We're witnessing the slow-motion collapse of an entire business model that dominated tech for two decades. The $1.3 trillion SaaS is being quietly hollowed out from within by AI agents. Here's how I see it playing out: Phase 1 (Now): AI as co-pilot. We're seeing this everywhere, Copilot for developers, Gamma for presentations, Harvey for legal research etc. These AI layers sit atop existing software, making it more efficient. The SaaS companies feel safe, even excited, as AI seems to make their products more valuable. They're bringing knives to what they think is a knife fight. Phase 2 (Next 12-18 months): The agent invasion. AI moves from co-pilot to autonomous operator. They're replacement workers that can fully operate existing software on your behalf. The dam breaks when someone can say "analyze our Q2 performance" rather than clicking through Tableau, or "optimize our ad campaigns" instead of navigating Meta's ad manager. The expertise previously bundled with the software gets unbundled by agents. Phase 3 (2-3 years): Software invisibility. The final phase happens when the agents bypass the human interfaces altogether. Why render dashboards, buttons and menus when AI can just access the APIs directly? The value proposition of SaaS, bundling software, workflow, and expertise into user-friendly interfaces unravels completely. The interfaces were designed for humans, but agents don't need them. Most SaaS incumbents don't see it coming because this isn't a classic disruption pattern. It's not about competing products with better features. It's about the evaporation of the core assumption that humans will operate software. What's more, the barrier to creating custom, internal software is collapsing simultaneously. Companies that once had to choose between expensive custom development or off-the-shelf SaaS can now spin up bespoke solutions in days instead of months. Why pay Hubspot $1,500/month for a CRM when your team can build 'HubspotForUs' with an AI coding assistant over a weekend? The same features, perfectly tailored to your workflow, with no ongoing subscription costs. This democratization of software creation means every company becomes a potential software producer rather than just a consumer. The specialized knowledge that SaaS companies monopolized is now available to anyone with access to an AI coding agent and domain expertise. It went from $1M to build an MVP to build a SaaS to basically free overnight. I bet the metrics will be puzzling at first, DAUs remain strong while feature usage mysteriously declines. The power users who drive revenue suddenly need fewer seats. Customer success calls shift from "how do I use this feature?" to "can your software work with my AI agent?" Or worse: "we built our own version that better fits our workflow." The survivors won't be those with the best features or even those who add AI features fastest (from no AI to "ai-assisted"). The winners will be companies that expose their software's capabilities through agent-friendly APIs and position themselves as the most trustworthy information sources and execution engines in their domain. There's also the shift from monthly subscriptions to outcome based software (pay per outcome, pay per task etc) but that's a tweet for another day! The $1T question: Will Microsoft, Atlassian, Adobe etc. successfully navigate this transition, or will they be the Digital Equipment Corporation of our era too invested in the previous paradigm to adapt to the new one? All I know is this will be a golden era for startups in the space. SaaS is being dismantled, piece by piece, workflow by workflow, interface by interface. Am I wrong?

@MrStand_Fast @BillAckman Why didn’t the plane see the helicopter given that it was right in front of the pilot?

Former Blackhawk pilot here. I’ll try to describe it for you. Imagine you are looking at the world through toilet paper tubes, and everything is just different shades of green and black, with stars and ground lights hard to differentiate and aircraft lights that look the same as those. Then you have 3 different radio frequencies going off in your ears. Then you’re trying to navigate without any peripheral vision. And you’re trying to keep the aircraft under control. And you are trying to keep watch for all traffic, not just one plane. Because there are several in the sky at once and you’re tying to mentally keep track of all of them. And you get distracted for like 5 seconds or your focus goes elsewhere, like you instructor pilot asking you a question about airspace regulations. Boom. You’re all dead. Flying these machines is really tough, and the airspace and NVGs make it a heck of a lot tougher.

Someone who has piloted a Blackhawk please explain how this is possible.

Excited to share the close of our second fund, “V2”, at $55.75 million. Thank you to all the founders that we’ve had the privilege to work with and our LPs for their support! Upwards and onwards 🚀

@arny_trezzi @PalantirBullets 100%. This is what we have been saying for 2 years at @RyghtAI also - for the clinical trials space.

$PLTR did it again. DeepSeek makes it clear something that Palantir's management has been saying for months: 1. AI models are set to become commodities. 2. All the value will accrue to the application and workflow layer = helping organizations orchestrate K-LLMs to deliver output. 3. You need ontology's security to ensure the LLMs can only see what they can see (CCP, no thanks). "The real value will be in the intersection between your business logic, your business norms/laws/ethics and the LLMs." Alex Karp, Apr 23: "People have it wrong. They think all the value is in the LLMs. AI models are like hydrocarbons in the ground. They need to be processed. That hydrocarbon-like LLM is essentially worthless to your business without the processing capabilities of Ontology and Foundry. " Alex Karp, Sept 24 "All the value in the market is going to ontology and chips. The ontology allows you take the LLM, refine it and impose it to the logics of your enterprise." Alex Karp, Jun 24 " AI models are converging, all while pricing for inference is dropping like a rock. This only strengthens our conviction that the value is in the application and workflow layer, which is where we excel." @ssankar Nov 24 "We're witnessing the commoditization of cognition with the rapid advancement of AI models." Ryan Taylor, Nov 24 As DeepSeek shakes confidence in the value of AI models, tech leaders are now regurgitating what Palantir has been articulating for months. Can Palantir see the future? 🔮

$1M fine for any company advertising on TV with the sound of a doorbell.

@theallinpod What time? I’ll have to cancel my mountain bike ride if it doesn’t drop in next 30 minutes.

heads up besties! we had to record a day later than usual, so the show will be slightly delayed this week. expect a very late friday/early saturday drop

Our Founder, Simon Arkell, joined Bradley Bostic today on the Boombostic Health podcast. They discuss how Ryght AI is at the forefront of innovation by utilizing generative AI in clinical trials. 🎧Listen here -hubs.li/Q02XPVbk0 #AI #healthcare #podcast #innovation

Great to be invited to do the Boombostic Health Podcast with Brad Bostic. podcasts.apple.com/us/podcast/boo…

Ouch

Big day as we announce the the great Tarek Sherif as an investor and advisor to Ryght . Tarek has one of those amazing stories, having co-founded Medidata Solutions from the dot com era, not having been able to raise VC, bootstrapping an IPO and exiting to @Dassault3DS for $5.8B

@Jason Couldn’t agree more

We’re all being forced to make a binary pick between the two worst candidates of our lifetime

@Jason Yeah sorry @Jason that was my least favorite in years. I love Cuban but he went down an irrelevant rabbit hole for too long about what caused inflation and 80% of it was people talking over each other. Sacks was boring in his defense. Keep politics to 20%, 80% to tech and biz.

Permission to be candid: what did you think of the last All In episode?

Good timing! 😂 twitter.com/salgadinhomusi…

@UNM_Lettermen @joshk97 Had no idea he was a lobo! Wow.

On the edge of our seat. Congratulations @joshk97! 👏👏👏 #Lobos4Life #Paris2024