Todd Jackson
@tjack • 16,206 subscribers
Partner @firstround. Former VP Product @Dropbox, Product Director @twitter, co-founder @coverscreen, PM @google, @facebook. Amateur golfer and dad.
Shorts
Videos
There’s a generational land grab playing out in enterprise software right now, and deployments are the frontier. But right now nobody can hire enough FDEs. It’s a brutal talent war. And even if you can hire them, your best people can only take on so many customers, so you’re forced to ration the high-touch deployment work for your most strategic accounts. Enter withgenera: founded by Will Patterson and James Honsa. Genera helps AI application companies scale white-glove deployments – using a combo of agents, humans, and pricing based on outcomes (not hours). They act as an extension of your in-house team so you can run every deployment like it’s your most critical customer. Fin and Ironclad are great examples. They’ve been using Genera and seen massive impact in scaling high-touch customer deployments (more in the video below on the impact at Fin). Proud to have led their $10M seed round and worked with this team from the very beginning of their story. They’re launching today and hiring across the board. More below:
Todd Jackson31,631 görüntüleme • 17 gün önce
Today we’re opening applications for the sixth cohort of First Round’s PMF Method, happening in Sonoma from 9/27 - 9/30. This intensive, four-day retreat has helped over 100 founders take a straighter path to PMF. We take 0% equity in your company. No accelerator fine print. PMF Method gave Jean-Denis Greze 💡 the yardstick to see how his company was doing against both the different levels of PMF and his peers. His business was working but he threw it all away to pivot Town into a bigger market. The company has now raised over $70M from a16z and First Round. Anne Brandes had the idea for Conway but learned new ways to pressure test it, along with enterprise sales frameworks she still uses today. She raised a seed from First Round and Kleiner Perkins, and now has millions in revenue. And Paul Klein IV founded Browserbase and had early traction, but got the benchmark data he couldn’t find elsewhere to make sure the company was on the right track. The company has raised $67M from CRV, Kleiner Perkins and Notable Capital. These three founders join PMF Method alumni — senior leaders from Anthropic, SpaceX, Stripe, Rippling and more — who’ve raised over $750M in the last 18 months. There are many paths to PMF. Few of them are a straight line. But one program can help increase your odds of finding PMF faster. Apply below:
Todd Jackson36,490 görüntüleme • 1 ay önce
Big First Round news today! We’re launching Product-Market Fit Method (a free intensive 14-week experience for early founders building epic B2B SaaS companies) and publishing the first session on our internal framework for all to read (with benchmarks, Looker's real data, and tactical advice from iconic enterprise founders). Even though finding product-market fit is the single most important thing for a startup, it’s still underexplored and seen as more art than science. We wanted to change that. I’ve personally talked to hundreds of founders about this topic, digging into what they did in the first 6-9 months of company building. (We’ve published dozens of those interviews on The Review in our “Paths to PMF” series.) This video previews some of what we learned — thanks to Christina Cacioppo, Zachary Perret, lloyd tabb, Jason Boehmig, & Jack Altman for sharing their lessons! In addition to that research, we’ve also drawn from our own 20 years of data and 500+ pre-PMF investments. What emerged was a very consistent set of patterns for sales-led B2B companies — the basis for our new framework and PMF Method’s 8 tactical sessions. In the program, we help early founders discover what customers really want, build the right v1 product, and close their first enterprise sales. We ran a beta version late last year with a tight-knit group of founders (ex Stripe, Plaid, Airbnb, Twitter, Greenhouse, Grammarly) and the feedback was great — my personal favorite was: "I feel like I shaved 12 months off the time it would take us to get to PMF.” Here are a few key dates and details: - The Summer 2024 session of PMF Method runs 5/29 - 8/28. - Application deadline is 11:59 PDT May 7th. - Any early founder working on a new B2B SaaS company is welcome to apply. Bonus points if you’re technical, have a clear product idea but haven’t raised yet and are <12 months into working full time on your idea. - PMF Method is 100% free. It costs you $0 and we own 0% of your company. Like with The First Round Review and Angel Track, our mindset is to openly share knowledge that we’ve put hundreds of hours of work into curating with the broader startup community, and give it away for free. That’s why we’ve also published our framework, so every builder can use this resource, even if they don’t do the program (it’s linked in the next post). Check out the links below for more details. Can’t wait to read applications!
Todd Jackson241,604 görüntüleme • 2 yıl önce
10 years ago, Parag Agrawal and I were working together to introduce ranking to Twitter’s timeline for hundreds of millions of consumers. Now he’s started Parallel Web Systems to build infrastructure for a very different kind of user: AI agents. And in a full circle moment, we’re able to work together again, as First Round invested in his seed round last year alongside Khosla Ventures and Index Ventures. Parag and I had a chance to sit down for a great conversation last week (his first interview since leaving Twitter!). It was a fascinating reflection on what he learned and what he’s doing differently. We dig into: - The transition from CTO → CEO → Founder - What he was *really* thinking when all the Twitter drama was going down - Why he chose to be a founder (vs. take another big role) - How he landed on the idea for Parallel - What fundamentally changes when you’re designing for AIs vs. humans - How he thought about fundraising and building his early team - How working with customers like Clay shaped Parallel’s earliest products - The case for building “slow” APIs, and the advice he got from Patrick Collison - His takes on the modern agent stack and how evals need to evolve And much more! Immensely proud to be able to partner with Parag and the entire Parallel team. They’ve made incredible progress in a short amount of time and I can’t wait for more folks to start playing around with the APIs they’ve built. The full conversation is below, as well as more details on what Parallel is up to.
Todd Jackson114,887 görüntüleme • 1 yıl önce
Reaching the scale to host your own conference is a massive milestone for a company. Since fal’s inaugural Generative Media Conference is this Friday, I sat down with to dig into the last 3 years of their journey. Their 10/24 conference has an insane speaker lineup with lots of real-world use cases of generative media in action. The preview video below is just one example (we used fal’s platform to create all the visuals). Aside from the fun we had turning me into George Clooney and making a giant 3-ton Roomba cat destroy our podcast studio, what stood out was how far all of these models have come in the last few years -- and how easy it is to get started with fal and play around so many different options. There’s a ton of interesting technical optimizations and developer-focused decisions that made that experience possible, so it was great to hear Gorkem unpack all of their unique company and product building choices. One of the more interesting ones that they hardly ever talk about is their pivot (when I invested back in 2022, it was a completely different product for data teams), so it was fun to get into that story as well. Full conversation below, hope you enjoy it!
Todd Jackson57,572 görüntüleme • 10 ay önce
This may be the AdSense moment for the agentic web. When First Round invested in Parallel’s seed, the core thesis was a bet: AI agents would use the web far more than humans ever had, and the infrastructure to support that didn’t exist yet. Now, Parallel has over 100,000 developers and companies like Harvey, Granola, Modal, Manus, Attio and Profound relying on their APIs daily. Watching this thesis play out has surfaced a huge problem no one is tackling: if agents are using content from across the web, who gets paid and how do you even calculate that fairly? Until now, the answer has been closed-door licensing deals between the biggest AI labs and biggest publishers. Today, Parallel is launching Index as a first step toward a scalable, democratic solution. Humans still own content. They’re the writers, data owners, and publishers whose work those agents depend on to do anything useful. Index gives site owners a dashboard showing how agents are using their content and how much it contributes to the value of the work those agents are doing. Compensation is tied to contribution — calculated using impressions, citations, uniqueness, and value (tasks with the highest compute spend). All of this is presented transparently. Launch partners show the breadth of scale: from major news outlets like The Atlantic and Fortune, to data providers like PitchBook and ZoomInfo, to independent creators like Packy McCormick and Mario Gabriele. Proud to keep backing Parag Agrawal and the team at Parallel Web Systems.
Todd Jackson13,834 görüntüleme • 3 ay önce
AI legal startups are a thing in 2024. But as Ironclad’s Jason Boehmig puts it, “nobody was trying to buy an AI legal assistant back in 2015.” Ironclad has one of the most interesting and underexplored stories out there IMO. As we were developing First Round's PMF Method, we learned so much from their journey — super grateful Jason took the time to share his insights for other builders. 🙏 Here were a few of my takeaways: 🔬 Zoom in to find focus “It was actually fairly easy to sign up early customers — what was difficult was finding a product that could address that market. That took us several years of iteration. We had to try to figure out what pieces we could peel off into a repeatable, discrete software product. We quickly realized the really interesting part of the problem was in repeatable business transactions — sales agreements, employment agreements, NDAs licensing agreements, partnership agreements. A lot of our competitors tried to do everything that corporate legal teams do. But we were only doing the contract part.” 📣 Expand an existing category (with an existing buying cycle) But the initial AI legal assistant positioning wasn’t resonating. I’ve talked to 100s of founders about PMF and the story of how Ironclad got unstuck is one of the wildest ones I’ve heard. “100% of the time I had to explain what an AI legal assistant was. We had a [email protected] email on our site. One day I got a one-liner message that said, ‘Hello, are you a CLM?’ I was so close to hitting archive, but it was from someone at a publicly traded company. But what was a CLM? Turns out it’s a Contract Lifecycle Management platform that helps enterprise companies create and manage their legal contracts. By that definition, we were. So of course I wrote back, ‘Yes, we are definitely a CLM, we would love to come demo our CLM for you.’ But while we were really great at creating contracts with our AI legal assistant product, we hadn't put a lot of thought into how you deal with contracts afterwards, with a feature called a repository. And so we had set up this demo with the legal team from this publicly traded company, and I turned to my co-founder Cai, and said, ‘By the way, we have 3 hours to build a repository.’ We took the train from SF to San Jose and he built the first version of a repository, which we demoed live at the end of the train ride. This customer was in a CLM evaluation cycle that had 12 other solutions in it, but they loved the demo. So we went and actually built the full product, and we won. And after that, of course, we changed our messaging. We got serious about building CLM functionality and that's our flagship product to this day. There were lots of people out there trying to buy a CLM so we just got to participate in a lot of buying cycles, but with the AI legal assistant buying cycle, we had to create every one of those.” 👥 Artificially constrain the buyer and build community early “One of the things that we did which was really helpful in hindsight was we artificially constrained the buyer we were going after. Once we decided to make the shift to enterprise, instead of trying to address the whole US market or the whole global market, we decided we only cared about being the number one CLM in SoMa. We got a list of every company that could use the CLM in SoMa and got intros to them — it just provided a ton of focus for us. It's how we also stumbled into doing community. We would host these community dinners and if you were a general counsel of a company based in SoMa, you probably knew other people that were coming to them. We just started to get this buzz of ‘Are you going to the Ironclad thing tonight?’ There's a ton of value if you can discover a part of the organization that no one cares about, and connect that part of the organization to a larger business problem.” 📚 Founder-led sales is learnable I was impressed to learn that Jason still sends cold outreach himself to this day. But founder-led sales didn’t come naturally. “A misconception I had about early-stage startups was that the cartoon character salesperson who's slapping everyone on the back and is a total extrovert is the best salesperson. And it's actually the person who's almost like an engineer in their mindset — super methodical, sends great follow ups, could be very shy. It's a very learnable skill.”
Todd Jackson50,683 görüntüleme • 2 yıl önce
Daha fazla içerik yok.