How a Founder Runs GTM for Two Companies Without Hiring

Author: Shawn Ennis, CEO of Rapax | Published: April 24, 2026 | Category: Case Studies, Founder GTM

Meta Description: Learn how Rapax deployed KForce and freed 24 hours per week while generating $10M in pipeline—without hiring a single sales person.

Introduction

I’ve run go-to-market strategy for 25 years. I’ve built and sold companies. I know the playbook cold.

And I can tell you with absolute certainty: GTM is the worst part of every founder’s journey.

Not because selling is hard. I love selling. The pain is everything around the selling: coordinating teams, maintaining infrastructure, managing people you’re paying to not listen, pretending you enjoy social media, and watching your CRM become a graveyard months after you set it up.

Three weeks ago, I stopped accepting this as inevitable.

Instead of hiring a sales team, I built one. Not with people. With AI.

The result: 24 hours per week freed. A $10M sales pipeline. Five inbound requests from outside my network. And for the first time in my career, I’m not exhausted.

This is the story of how KForce changed founder-led GTM.

The Founder’s Dilemma: Why GTM Feels Impossible

Let me paint the picture every founder knows too well.

Your product is strong. The market is hungry. But GTM is a monster that demands everything at once:

You need structure. A CRM, a social media calendar, email sequences, content strategy, analyst outreach, partner coordination. You hire consultants to build it all. You don’t use most of it.

You need consistency. You post on LinkedIn when you think about it, which is never. Your sales process is bottlenecked through your calendar. You can’t scale what you can’t repeat.

You need knowledge. Who is in your pipeline? What stage are they in? What did they say last quarter? Where is competitive intelligence coming from? Your answers are scattered across email, Slack, Google Docs, and your brain.

You need people. An inside sales rep costs $85–120K loaded. A content manager costs $70K. A sales operations person costs $90K. Suddenly you’re running a team instead of a company. And the first person you hire will leave after 18 months with all your pipeline context.

So you accept the pain. You hire anyway. You manage people who manage systems. You post inconsistently. Your CRM becomes historical fiction. And you wonder why GTM feels like pushing a boulder uphill.

The Moment Everything Changed

Three weeks ago, I deployed KForce: two autonomous AI agents running inside a unified platform.

Sage handles sales automation: research, outreach, CRM management, and personalized messaging at scale.

Aria handles marketing: content strategy, social publishing, campaign management, and lead nurturing.

Setup took 30 minutes. Learning curve: email an assistant.

And suddenly, GTM stopped being a management problem and became a leverage problem.

What Sage Does: Sales Automation That Doesn’t Feel Automated

Every morning, I wake up to a brief from Sage. It tells me:

Today’s meetings — with context on each account, the attendee’s background, recent company announcements, and what they care about.

What changed yesterday — new contacts captured, deals moved, competitive intelligence, buying signals I would have missed.

Recommended next actions — specific talking points for each call, follow-up sequences, and objection handling context.

This takes me five minutes to read. It saves me four hours of manual research.

But here’s the real magic: Sage researches and ranks targets at scale.

When I loaded a 1,000-person conference attendee list, Sage processed all of them overnight. It ranked the 28 highest-value targets (CTO/CIO/VP Ops at tier 2/3 operators), pulled their LinkedIn profiles, found their recent activity, and drafted 28 hyperpersonalized connection messages.

One message per person. No templates. No generic “let’s grab coffee.” Every message referenced their company, their recent moves, their role.

I reviewed them in 30 minutes. Most went out unchanged.

Result: 75% connect rate. (Industry average: 20–40%.)

The personalization created a magnet. People responded because the message felt like it was written for them.

And here’s what nobody talks about: Sage auto-captures 500+ contacts per month from my emails, meetings, and LinkedIn. My CRM is accurate for the first time in my career. There are no mystery deals. No data entry tasks. No duplicate records. Just clean, actionable pipeline intelligence.

What Aria Does: Content Consistency Without the Burnout

Aria posts on LinkedIn 2x per week. I post manually 1–2x per week. My podcast goes out Wednesday. Total touchpoints per week: 4–5.

That’s the cadence that drives traction. But maintaining it manually is impossible.

Aria drafted based on three strategic documents I created: one on OSS integration complexity, one on autonomous NOCs, and one on knowledge-driven operations. From those three documents, Aria generates weeks of content—blog ideas, social posts, email sequences, landing page copy.

I spend five minutes on Sunday reviewing this week’s posts in Zernio. I approve, edit if needed (rarely), and schedule.

That’s it.

The result: LinkedIn impressions spiked 683% in 90 days. New connections went from 10/week to 100/week. And five people outside my immediate network reached out unprompted—something that happens rarely unless your content is consistent and strategic.

This matters because consistency compounds. One post gets 500 impressions. Five posts per week gets 4,000 impressions. But 5 posts per week, every week, for 12 weeks? That’s when the algorithm notices. That’s when people start sharing. That’s when inbound starts flowing.

The FutureNet World Story: Personalization at Scale

The real proof came at FutureNet World, a major telecom conference.

Shawn loaded the 1,000-person attendee list into Sage on a Monday evening. By Tuesday morning, Sage had:

• Researched all 1,000 attendees
• Pulled company data, job titles, LinkedIn profiles
• Ranked the top 28 targets (tier 2/3 operators, CTO/CIO/VP Ops decision-makers)
• Drafted 28 hyperpersonalized LinkedIn connection messages

Each message was unique. Each referenced something specific about the person—their company’s recent moves, their role, a recent LinkedIn activity.

Shawn reviewed the 28 messages in 30 minutes. Most went out unchanged.

By Friday, 21 of the 28 had accepted the connection. Within one week, five of those people visited the booth.

That’s a 75% connect rate on cold outreach.

The cost? About $2.40 in API tokens. The time investment? Two hours total from initial list to sent messages.

Doing this manually would take 20+ hours and produce a 30% connect rate—if you were lucky. This produced 75%.

But here’s the insight: This only works because Rapax has good positioning. The personalization amplifies an already-strong message. KForce doesn’t make bad ideas better—it communicates good ideas in a way customers actually understand.

The Numbers: Three Weeks of Real Results

Metric	Result
Time Freed (per week)	24 hours
LinkedIn Impressions (90d)	28,959 (+683.8% vs. prior 90d)
New LinkedIn Connections	100 per week
Contacts Auto-Captured (monthly)	500+
Qualified Meetings (monthly)	20+
Inbound Requests (outside network)	5 in 3 weeks
Website Leads (content)	25
Sales Pipeline (active deals)	$10M
Headache Reduction	80% in 3 weeks

The pipeline is real. Three deals are actively closing. Average deal size is $500K ACV. Sales cycle is 6–9 months.

But the metric that matters most? Time freed. 24 hours per week that I’m not managing systems, not posting to social media, not entering data into a CRM, not writing email sequences.

Those 24 hours are going straight to selling, strategy, and product decisions. That’s traction.

What’s Actually Working (And What Isn’t)

I need to be honest about what this is and isn’t.

What’s working:

• Personalized outreach at scale (75% connect rate isn’t luck)
• Consistent content cadence (no more lumpy posting)
• CRM integrity (500+ auto-captured contacts, accurate pipeline)
• Inbound traction from organic engagement (5 unsolicited requests in 3 weeks)

What’s important to understand:

This doesn’t make a bad idea better. KForce communicates good ideas well. Rapax has strong positioning. The market is hungry. Without those things, even great automation tools fail.

Marketing drives awareness, not lead generation. The 25 website leads are a bonus, not the engine. The real engine is the founder on the phone, selling, understanding the customer’s problem, building credibility.

The founder still does the thinking. I wrote the strategy documents. I qualified deals. I decided which targets matter. I made the calls. KForce is the leverage, not the magic.

What Getting Calls Faster Than Expected Taught Me

“Expect faster calls than you think. Getting calls was WAY faster than I expected. Make sure you have a pitch deck ready, because people will want to talk to you.”

This is the real insight. When you show up consistently with good positioning, people call faster than you’d expect. Your pipeline accelerates. Your close rates improve.

But you need to be ready. Your pitch needs to land in 90 seconds. Your demo needs to run in 30 minutes. Your follow-up needs to land the same day.

Most founders aren’t ready for this. They’re still trying to get the first meeting.

The Bottom Line: Quality of Life + Traction

Here’s what KForce actually gives you: Quality of life and traction.

Not “work less.” Not “automation for automation’s sake.” Real, tangible traction with real, tangible time back.

I am more informed. I am less overwhelmed. I am confident my CRM is accurate. I show up consistently on social media. I’m having better conversations because I’m more prepared. And I’m closing more deals because I’m showing up.

Most importantly: I’m not hiring yet. And I won’t hire until multiple deals close so I can pay them from proceeds.

That’s the promise. Not “do GTM alone forever.” But “don’t hire prematurely. Bootstrap from traction. Prove the unit economics. Then hire from a position of strength.”

For Founders Building Something Similar

If you’re running GTM solo right now, here’s what I’d tell you:

1. Start with positioning, not tools.

KForce amplifies good positioning. It doesn’t create it. Spend two weeks on positioning: Who do you sell to? What problem do you solve? Why does it matter? Get that right first.

2. Consistency compounds.

One post gets 500 views. 5 posts per week for 12 weeks gets exponential traction. But you can’t be consistent manually. You need automation.

3. Personalization at scale is the killer feature.

Generic outreach doesn’t work. Personalized outreach at 1,000-person scale is impossible manually. That’s where AI changes the game.

4. Your CRM is your source of truth.

If your CRM is wrong, everything downstream is wrong. Salespeople spend 30% of their time entering data. AI can fix this. Automate data capture and let your team focus on selling.

5. Lead with traction, not hires.

Don’t hire until you have proof. Traction from founder-led GTM is the best proof you can show an investor or a new hire.

What’s Next

We’re three weeks in. The pipeline is real. The traction is real. The time savings are real.

Next, we’re expanding content repurposing—turning one blog post into five LinkedIn posts, one video, three email sequences, and a landing page. We’re deepening the Aria campaigns with subject line testing and conversion optimization. We’re building a referral program that leverages Sage’s relationship intelligence.

The vision: A founder can run GTM for a $5–10M company without hiring, without losing sanity, and without sacrificing quality of life.

We’re proving it’s possible.

The Offer

If you’re running founder-led GTM right now and you’re tired of the manual work, let’s talk. KForce isn’t for everyone. It’s for founders with good positioning who are ready to scale.

We’ll spend 15 minutes understanding your GTM pain and your positioning. If there’s a fit, we’ll show you exactly how Sage and Aria can free up your time and accelerate your pipeline.

Book a 15-minute conversation →

This case study is based on real results from Rapax, an AI-native network service assurance platform for network telecom operators. Results may vary based on positioning, market conditions, and execution.

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