11x

11x was founded on a single principle - let humans be human, and stop wasting human time and energy on repetitive tasks. Over the past few years, the team has raised $70M+ from Benchmark and a16z and deployed thousands of digital workers globally. What it’s like to work there - smart people, hard problems, lots of autonomy. It’s a place where people take ownership without being asked and try to solve often impossible-seeming problems. 11x is rapidly growing and hiring across sales, success, growth, engineering, and design. They have offices in San Francisco and London, smaller hubs in Seattle, Vancouver and Toronto, and a remote team. Top 10 roles listed in the link below!

Brainsuite.ai helps the world's biggest brands, PepsiCo, Unilever, eBay, Vodafone, predict how creative will perform before launch. Christian Klingbiel runs outbound for an entire region at Brainsuite, on his own. And he's good at it. The problem was the number of hours in a day. Sourcing, research, writing the messages, it took five of every eight hours. Outbound could only ever stretch as far as one person's day. So Brainsuite brought on 11x to take the manual half off his plate. Now 11x runs the sourcing and sending in the background, overnight. Christian wakes up to replies instead of a to-do list, and spends his day on the part that actually needs him: the conversations, the strategy, the deals. In his words: "When I'm asleep, Alice keeps sourcing and sending. The next morning, the responses are waiting and I can get to booking a meeting right away." The result: → 500+ hours saved every year on outreach → 30% more pipeline → 50% of booked meetings sourced by 11x Same person, same instincts. Just no longer capped by the hours in a day. Full story below.

Three weeks into 11x, and I'm still processing how much happens in a single day here 🏃 Early days at a company are always a mix of excitement and uncertainty. This one's been more of the former. The team is small and extremely talented, the pace is real, and — maybe most importantly — the problem we're solving clearly resonates with customers 💡 We're starting to grow the sales team and looking for AEs who want to be part of an early chapter. You'd be working directly with me and Greg Walder — early enough to shape things, with enough foundation that you're not starting from zero 🚀 If you're interested in the AE role, DM me and lets set up a time to connect!

Loved this conversation with brendan short - AI automates many of the jobs-to-be-done not the entire job itself. Because these roles were never about doing a bunch of these manual recurring tasks. It was about spending time with prospects, building relationships, doing deep discovery, building business cases, and actually closing revenue. Bring the magic back to sales :).

I spent most of my career at product-led companies. Dropbox, Front, Whimsical, TextExpander. You wake up to a pile of free signups, trials, and freemium accounts. Way more than your team could ever personally work. So you do what everyone does. You segment, send the most promising slice to your AEs, and drop everyone else into automated campaigns and lifecycle emails. The reason is just math. A good rep costs significantly over a hundred grand all in and can give real attention to a few hundred accounts a year. You're taking in thousands of signups a month against an ACV of a few thousand dollars. The numbers never let you put a person on most of them. So that big automated bucket runs blind. A couple of generic emails, a "just checking in," a nudge that has no idea what the person did in the product. Real buyers sit in that pile and quietly fall out of the funnel. You know they're in there. You just can't justify the headcount to go find them. That math has changed. An agent can now hold context and carry a real conversation, which drops the cost of a personalized touch close to zero. So you can finally work that whole bucket. Every signup gets a message that knows where they stalled in setup, which feature they tried and which they skipped. It can take a product that usually gets pitched the same way to everyone and frame the value around their role, their industry, even what they post about on LinkedIn. Then it follows up over email, text, or a call. I watched a background-check company do exactly this. They pointed a voice agent at their self-serve signups to answer questions and walk people through setup, and re-engaged the ones who dropped off with messages that knew where they'd left off. This only works if every touch is useful to the person getting it. The moment it turns into automated noise that knows their name, you've made the problem worse. The goal never changed. Get someone to actually use the product and hit the moment where it clicks. For years I could only chase that for the few. Now you can do it for everyone who signs up. This is the playbook I wish I'd had at every PLG company I've been part of. It's a big part of why I'm at 11x now. If you're running PLG, how are you working that self-serve middle today? Still mostly generic lifecycle emails, or starting to do it differently?

Every week someone asks me: "Is the AI app layer dead? Won't OpenAI and Anthropic eat everything?" The answer isn't that simple - it depends entirely on what you're building. I partnered with Joe Schmidt IV & Andreessen Horowitz to tackle this head-on. The premise is simple: the labs are walking the Yellow Brick Road. Everything else is the rest of Oz. Different games. Different rules. Different winners. Three things we've learned building 11x off the road: → Start from outcomes, not models. We built around one question: how do we generate more growth for our customers? Every task flows from there. Some are agentic. Some aren't. The labs hold no edge over a focused application company on the deterministic software underneath. That's where most of the real engineering lives. → Lean into the complexity. Here's a "trivial" GTM problem: don't reach out to contacts at companies that are already your customers. In practice? Parent companies, subsidiaries, company rebrands, stale CRM domains all make it complex. Real-world data is messy. Better models alone don't clear that bar. → Guardrails are the product. A regulated financial services buyer needs different guarantees than a mid-market SaaS customer. Different engagement rules. Different contact rules. Different data access. Different call behavior. One-size-fits-all collapses under that variance. We staff FDEs to tune per customer because this work sits squarely with the application company. The proof: ✅ Positive reply rates up 4x in the last few months ✅ Hundreds of millions in pipeline generated for customers ✅ With one F1000 partner, we now generate more sales opportunities in a single day than their entire SMB sales team produced in a month The application layer is alive. The thin-wrapper version is going to get eaten. Worth a read if you're building or buying in this space: link in comments!

💬 Five SDRs. Half the day lost to research. And the research still wasn't right. Every GTM team selling into a vertical knows this version of the problem: standard tools don't map your category cleanly and your ICP doesn't fit into a neat box. For BuildWitt, a SaaS platform for the construction industry, this was the bottleneck holding back outbound growth. Their buyers are heavy civil contractors who run crews of equipment. ZoomInfo and other tools miscategorized accounts. Before 11x’s Alice, mornings went to researching companies, then contacts, then enrolling them in sequences that often didn't land. 11x was the only tool that surfaced their ICP accurately. Alice now reads company websites, checks vendor registrations, and identifies whether a business actually owns heavy equipment. The impact in under 3 months:  ✅ Over 40% of all booked meetings sourced by 11x  ✅ 120+ opportunities influenced ✅ 50% of SDR time recovered from research and sequencing "We would be trying to do what 11x is doing, but it would take us half a day for each SDR, and we wouldn't be doing it as well. It's like our best guy on their best day, spread across a team of five people. And it doesn't sleep." — Dan Briscoe, Chief Revenue Officer, BuildWitt Check out their story below. 👇

Ramp's spend report on AI-native GTM software is out, and 11x is #1 in enterprise adoption. Enterprises are the hardest part of the market to win because they don't buy hype. They buy outcomes. Ramp Rate is built from anonymized procurement data pulled from twelve months of actual budget movement across thousands of companies. It measures where companies actually decide to spend, renew, and double down. A 40% enterprise adoption rate means some of the companies running the most complex GTM motions in the world are building their pipeline on our digital workers, Alice and Julian. Thank you to our growing list of enterprise customers who trust us everyday to accelerate their growth. These are the teams whose feedback raises the bar on digital workers. We’re excited for all there is to come! 🌟

Excited to announce the first (of many) podcasts coming from the GTM Council, hosted by Andy Mowat and myself, where leading practitioners and founders get into the AI questions GTM leaders are wrestling with right now. This first episode is from our Agentic SDR/BDR series, and features Prabhav Jain from 11x. New episodes releasing every week...