Section 01Solo, Not Alone: Jacob Runs an Entire GTM Org with AI Agents
“I’m responsible for marketing. I’m responsible for sales. I’m responsible for customer success. I’m responsible for support. I’m responsible for operations.”, Jacob Bank, Relay.app
Relay.app has zero dedicated go‑to‑market hires, yet new customers keep rolling in, support tickets get answered within minutes, and last week’s webinar somehow turned into a polished YouTube tutorial and a LinkedIn thread that racked up 50,000 impressions. The lone human behind that is Jacob Bank. He’s the CEO, head of GTM, head of Customer Success, and head of Operations. But he isn’t superhuman; he’s agent‑augmented.
“In a pre‑AI world,” Jacob said, “we would have needed to hire at least four, probably seven people to do what I’m doing by myself right now.”
Over the next few minutes, you’ll learn how Jacob:
- Leapt from 10 → 100 → 1,000 customers by betting on exactly one high‑leverage channel per growth stage.
- Built an AI‑agent stack that shaves days off research, content, and support tasks, no data‑science PhD required.
- Dodges dashboard fatigue by trusting “vibes/intuition” and talking to users more than he stares at metrics.
- Turns six‑star support into a word‑of‑mouth engine, even while the entire GTM org is basically…him.
- Plots the next jump to 100,000 customers, including the experiments he’s keeping, killing, or automating next.
Whether you’re a solo founder, a growth hacker maxed out at four simultaneous tests (been there), or a marketer curious about AI agents, this blog lays out a repeatable, boots‑on‑the‑ground framework you can swipe and adapt, minus the vanity dashboards and premature A/B tests.
Let’s dive in.
Section 02Why This Conversation Matters?
Who’s Jacob Bank, and what’s Relay.app? (You can skip this part if you know Jacob.) Jacob is a second‑time founder best known for leading product at Gmail and later founding Timeful (acquired by Google). His latest venture, Relay.app, is a no‑code platform for building AI agents that handle everything from lead routing to content repurposing.
Relay lets you “spin up an agent the way you’d spin up a Zap”, except the workflows think for themselves. (because you know….AI)
Why I cared enough to grill him for 32 minutes. I’m a growth hacker by trade. Pre‑AI, my bandwidth peaked at four concurrent experiments before spreadsheets, copywriting, and analytics turned into a hair‑on‑fire blur. If agents can offload the grunt work, maybe I can test ten ideas at once, or even run an always‑on pipeline of experiments without torching my weekends.
The question on the table:
Can a lean stack of AI agents compress the experiment cycle and replace multiple GTM hires, without gutting the intuition and user empathy that make growth work in the first place?
What does Jacob think? let’s find out.
Section 03“Data‑Driven” ≠ Early‑Stage Growth
“In your pre-PMF days If a channel gets you even one paying customer, that’s a successful experiment and a win. That channel may be viable.”, Jacob Bank
The “One Paying Customer” Litmus Test
In growth hacking, you’re supposed to A/B test everything until a graph tells you the truth. Jason Lemkin (SaaStr) says something else for pre‑product‑market‑fit startups:
- Goal: find one channel that nets one paying user.
- Implication: at the seed stage, qualitative proof-of-life beats p‑values.
Jacob lives by that mantra.
- Warm intros? ✅
- Reddit replies? ✅
- Cold email? ❌ → Felt dead on arrival, he didn’t need a spreadsheet to confirm the vibe.
The lesson: statistical significance is a luxury; momentum is everything pre-PMF.
Dashboards Are Dangerous
“Every minute we stare at dashboards is a minute we’re not talking to users. In the early days, data is more dangerous than valuable.”
Relay once asked new sign‑ups, “How did you hear about us?” The answers were a multiverse of half‑truths: LinkedIn? Word‑of‑mouth? A friend’s forwarded Tweet? Multi‑touch marketing made that data useless and slowed onboarding.
So they killed the question, and most tracking pixels with it.
Jacob now runs on what he jokingly calls “100% vibes attribution.” Customer chats, DMs, and live support sessions tell him which channels resonate. When qualitative signals line up with revenue, he doubles down. When they don’t, he pivots
→ no dashboard or post‑mortem required.
The takeaway is uncomfortable (atleast for me) but freeing: at the earliest stages, obsess over conversations, not cohorts. Data will eventually matter, just not before PMF
Section 04Relay’s Channel Ladder: 0 → 1000 Customers
Jacob’s growth playbook is deceptively simple: each growth stage demands exactly one channel with enough “juice” to reach the next plateau/stage. When a tactic/channel caps out, you thank it for its service and move on.
Here’s the ladder of Relay.app far.
0 → 10: Warm Intros & Reddit Thread‑Hacking
“We got our first ten customers through two mechanisms: warm introductions inside our network, and jumping into Reddit threads where people were complaining about the problem we solve. (building AI Agents)”, Jacob Bank
Phase one was pure elbow grease. Jacob DM’d friends‑of‑friends, then checked in r/b2bmarketing, offering helpful answers, not sales pitches. When watching Reddit manually got painful, he built a Relay agent that pings him any time a post mentions AI, agents, or automation in that subreddit. Manual hustle first, automation second.
10 → 100: Partner Webinars & Bottom‑Funnel SEO
They did joint webinars with Notion or Airtable, got listed on their pages, and then spun up ‘Zapier alternative’ comparison pages. Those two moves, plus some word of mouth, took them from ten to a hundred customers.”
- Their “Pabbly Connect alternatives” comparison page
- Their “Zapier alternatives” comparison page
- etc…
They tried Cold emailing, but it fizzled (“I could just feel it wasn’t working”, said Jacob), so Jacob switched to partner marketing: co‑hosted webinars and directory listings on bigger platforms.
The bottom-of-funnel SEO pages targeting buyers ready to switch (“X alternative,” “X vs Relay”) still generate leads today, but once they stalled below the next threshold, he stopped investing hours in them.
100 → 1,000: Organic Social & Tutorial Video
“In the last eight months I went from 5,000 to 50,000 LinkedIn followers, 100k impressions a quarter to 5 million.”, Jacob Bank
LinkedIn became the top‑of‑funnel rocket. Jacob posts daily, then logs impressions, comments, and reactions in a tracker to refine what works (with a relay ai agent). From LinkedIn, he nudges people to:
- YouTube tutorials: deep, practical demos (5-60 min) that rarely go viral but attract “high‑intent, highly qualified” viewers.
- The Relay newsletter: a drip of case studies and agent recipes that bridge the gap to signup.
Snapshot:
- ~8500 subscribers,
- ~20000 monthly views,
- ~100 hours watch‑time.
Jacob’s most‑watched videos hover near 6000 views. which is proof that 6000 right eyes beat 600,000 random ones.
Ongoing: 1,000 → 10,000
With LinkedIn still surging, Jacob believes it “has enough juice” for the next leap, but he’s layering fresh bets:
- 6‑ to 8‑minute “flagship” YouTube videos aimed at 100k views each.
- Selective influencer sponsorships (early tests flopped; he’ll revisit once the pitch is tighter).
If those GTM plays earn their keep, great. If not, they’ll be abandoned like the channels before them, because on Jacob’s ladder, every rung is temporary, and the only metric that matters is the next order of magnitude.
Section 05Jacob’s AI‑Agent Stack
Chatbot vs Agent
- ChatGPT = strategist. You should fire up a plain chat when you need fast ideation: “Give me five LinkedIn hooks,” “Suggest three webinar titles,” or “List ways to reuse this blog post.”
- Agents = operators. Once an idea passes the smell test, then you wrap it in an agent(Relay) flow that runs forever without babysitting. Anything that’s either (a) brutally repetitive or (b) something AI does better than a human graduates from chat to agent.
The Three Social‑Media Buckets
- Research Agents Scrape Reddit, YouTube, and LinkedIn for questions people are asking about AI automation; surface fresh content gaps every morning.
AI is way better at crawling communities and spotting trends than you’re at day-dreaming ideas.
- Creation Agents Auto‑lift key moments from a YouTube tutorial, re‑frame them into a LinkedIn carousel, a Twitter/X thread, and a newsletter blurb, then hand you a draft for final polish.
- Follow‑Up & Analysis Agents Track impressions, comments, and DMs, flag posts that spike engagement, and queue high‑potential replies so nothing gets lost track.
Together, these agents compress the classic “research → create → engage → learn” loop from days to hours.
Section 06The Word‑of‑Mouth Flywheel
“At least half of our new users come from word of mouth. Every time we try to engineer it, the return is negligible; every time we obsess over helping a customer, referrals spike.”, Jacob Bank
Six‑star support (an Airbnb phrase) is Relay’s hidden growth lever. He personally jumps into live chat, troubleshoots edge‑case Zapier migrations, and writes custom RegEx snippets if that’s what it takes. The payoff shows up in places a pixel can’t track:
- A LinkedIn shout‑out (“Relay’s unique, powerful functionality blew my mind. Kudos, Jacob!”) that snowballs into 10 demo sign‑ups.
- Private Slack groups where someone drops, “Relay solved this in five minutes; hit up Jacob if you’re stuck.”
Contrast that with the “engineered” attempts:
- G2‑review workflow → switched off (low SEO value, felt spammy).
- Affiliate program → minimal lift; advocates preferred sharing screenshots over tracking links.
- “Share on LinkedIn” prompts → polite ignores unless the product moment was truly delightful.
The lesson: you can’t hack genuine advocacy. Deliver a six‑star experience first; build lightweight sharing hooks second.
Section 07Jacob’s Takes on Pitfalls
- Onboarding Attribution Questions Relay scrapped “How did you hear about us?” because it slowed sign‑ups and produced garbage data.
“Multi‑touch reality makes that question impossible. If it’s friction + bullshit, why keep it?”
- Template Marketplaces are not a silver bullet Templates inspire, but rarely import cleanly into another team’s stack. Jacob would rather see users post real wins on LinkedIn than upload a half‑working template to a gallery. Jacob says: “While they're useful for inspiration (and we encourage our users to create them), every customer is so unique that one-click imports rarely work. I'd rather users build their own agent-building skills.”
- Beware the Fake‑Facebook Hack Forcing users through contrived steps because some cohort analysis said “people who add seven friends retain better” leads to bloated onboarding and, paradoxically, worse retention.
“Manufacturing a workflow that isn’t valuable won’t fix churn.”
Collectively, these takes circle back to the same credo: optimize for authentic user value, not vanity levers. When in doubt, cut friction, skip the gimmick, and talk to another customer.
Section 08The Playbook You Can Steal
Below is a step‑by‑step recipe distilled from Jacob’s process and my Growth Hacking Experience. Copy it outright or remix to taste, but keep the order, as each step sets up the next.
- Audit Your Current ExperimentsList every live and back‑burner growth test.Flag the ones that drain the most hours or mental load.Circle any task you dread because it’s repetitive; those are prime AI agent fodder.
- Be Honest About BandwidthIf you, like me, max out at four simultaneous experiments, mark a hard ceiling.Everything above that ceiling must be automated, delegated, or killed.
- Pick One Channel With Enough Juice for the Next 10× JumpAsk, “Could this realistically take us from 100 to 1000 users?”If the answer is “maybe,” run a micro‑test; if “no,” park it.Remember Jacob’s mantra: “Each growth stage needs exactly one channel, so ditch the rest.”
- Use ChatGPT as a Rapid‑Fire StrategistPrompt examples: “Give me five partner‑webinar angles for workflow‑automation founders.” “Suggest LinkedIn hooks for a tutorial on AI agents.”Paste your best ideas into a doc; highlight the ones that excite you and scare you (often the same ones).
- Triage Down to the Time‑SinksWhich tactics require hours of copy‑pasting, crawling, or formatting?Which require skills AI genuinely outperforms you at (e.g., scanning every Reddit thread for fresh questions)?
- Spin Up Agents for Those ChoresResearch Agent → surfaces content gaps from Reddit, YouTube, LinkedIn.Creation Agent → repurposes a 10-minute Loom into a LinkedIn carousel, X thread, newsletter snippet.Follow‑Up Agent → logs post metrics, flags spikes, drafts quick replies.Treat each agent like a junior hire: define the job, set guardrails, review output weekly.
- Talk to Users > Watch DashboardsSet a rule: for every hour inside analytics, spend two on customer calls or support chat.
- Retire Channels When They Tap OutSEO got you to 100 users but stalled at 250? Freeze active work, keep pages minimally fresh, and redeploy energy to the next bet.Ritualize a quarterly “channel funeral” to cut sunk‑cost attachments.
- Over‑Invest in Six‑Star SupportAim for delight, not just resolution.Screenshot-worthy wins; users will share them unprompted.Trust the compounding effect: half of Relay’s sign‑ups originate from genuine advocacy, not engineered gimmicks.
- Repeat the Loop → Intuition First, Agents Second.Each new order of magnitude restarts the ladder: audit → pick one channel → brainstorm → automate → talk to users.Keep the steps in that order; swapping them breaks the flywheel.
“Whenever we ignore dashboards and talk to people more, things go better for the company.”, Jacob
Follow these ten moves and you’ll replicate the core of Jacob Bank’s one‑person GTM engine. more experiments, fewer hires, zero dashboard anxiety, and customers who sell for you.
Section 09Put the Framework to Work
One last time in a single sentence: pick one channel that can power your next 10× leap, outsource its grind to a fleet of AI agents, and abandon yesterday’s channel the moment its juice runs dry. That’s the relay‑race Jacob Bank runs every time he levels up Relay.app’s growth.
Need inspiration? Jacob’s recorded a short, step‑by‑step tutorial that walks through cloning his Reddit‑surfacing agent and turning it loose in under ten minutes.
See you in the comments and in the next deep dive.
Section 10FAQ: running a one-person GTM with AI agents
Can AI agents really replace go-to-market hires?
At Relay.app they replaced several. Jacob Bank runs marketing, sales, customer success, support and operations himself with zero dedicated go-to-market hires, and his own estimate is that in a pre-AI world the same work would have needed at least four and probably seven people. The agents do the research, content and support grind; the judgement about which channel to bet on stays human.
What is the one paying customer test?
A pre-product-market-fit standard for calling an experiment successful: if a channel gets you even one paying customer, it may be viable and that is enough to keep going. It replaces statistical significance, which is a luxury at seed stage, with qualitative proof of life. At Relay warm intros and Reddit replies passed it and cold email did not, and that call was made on feel rather than on a spreadsheet.
Why did Relay stop asking how did you hear about us?
Because the answers were unusable and the question cost them signups. In a multi-touch world people genuinely cannot tell you whether it was LinkedIn, word of mouth or a friend's forwarded post, so the data came back as a multiverse of half-truths. Relay killed the question along with most tracking pixels and now reads channels from customer chats, DMs and live support instead. Worth noting this is the opposite of the advice on some other pages here, and the difference is the stage.
What was Relay's channel ladder from 0 to 1,000 customers?
One channel per stage, abandoned when it caps out. Zero to ten came from warm introductions and answering people in Reddit threads where they were complaining about the problem. Ten to a hundred came from joint webinars with Notion and Airtable plus bottom-of-funnel SEO comparison pages such as Zapier alternatives. A hundred to a thousand came from organic social and tutorial video, with LinkedIn going from 5,000 to 50,000 followers and 100k impressions a quarter to 5 million in eight months.
Can you engineer word of mouth?
The Relay experience says no. At least half of new users come from word of mouth, and every deliberate attempt to manufacture it returned almost nothing: the G2-review workflow was switched off for feeling spammy, the affiliate programme gave minimal lift because advocates preferred sharing screenshots to tracking links. What did work was six-star support, with the founder personally in live chat writing custom snippets for edge cases. Deliver the experience first, add lightweight sharing hooks second.
Rishikesh Ranjan
I reverse-engineer how the fastest-growing companies actually grow, then run the same plays for a living. First growth hire at ngram, growth at StreamAlive, Spaceonova, CloutFlow, and Airbook. Teardowns, playbooks, and field notes for people already in the trenches.
