Dec 1, 2025 · 1h 11m · product-market-fit
How his AI-first services company grew $0 to $40M ARR in one year. | Eric Foster, Founder of Tenex · PMF Show
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In this episode of the PMF Show, host Pablo interviews Eric Foster, founder of Tenex.ai, about how he built an AI-native cybersecurity services firm that scaled from $0 to $43 million ARR in its first year. Foster shares insights on outcome-based AI models, founder-led sales, overcoming legacy industry traps, and his 30-year career as a cybersecurity entrepreneur.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Pablo holds 15.7% of the talking time here. How this is scored →
Pablo as informed peer 4.3 Guest teaching 2.3 Guest disagreement 0.5 Pablo pushing back 0.6
speaking balance: gold is Pablo, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 19:10 Rebuttal of AI doomerism and bubble claims
Eric firmly rejects the premise that AI is a hype bubble or job killer, comparing modern skeptics to 1980s office workers defending typewriters against personal computers.
Hardest push from Pablo ▶ 26:59 Challenging indistinguishable cybersecurity positioningPablo pushes back on the cybersecurity narrative, pointing out that from an outsider perspective every vendor makes the exact same claims about threat defense.
Biggest teaching moment ▶ 57:45 Exposing the industry reality of dropped security alertsEric educates Pablo on the operational reality of enterprise SOCs, revealing that even premier companies discard millions of alerts daily because human analysts lack capacity.
Pablo holds their own ▶ 47:11 Framework for full-service AI outcomes vs SaaS softwarePablo articulates an incisive operational breakdown of how AI shifts software economics away from 90% margin tools toward high-adoption end-to-end service delivery.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Pablo as informed peer | Guest teaching | Guest disagreement | Pablo pushing back | Why |
|---|---|---|---|---|---|---|
| Eric Foster's Early Entrepreneurial Career in the 1990s | 2 | 1 | 0 | 0 | Pablo sets an inviting stage, asking clarifying questions about Eric's origins in tech in the late 1980s and early 1990s. | |
| The Early Landscape of Cybersecurity in the Modem Era | 2 | 3 | 0 | 0 | Eric educates the audience and host on the modem-era cyber threat environment, including wardialing and floppy-disk malware distribution. | |
| Corporate Leadership, Sideris, and the Shark Tank Acquisition | 3 | 2 | 0 | 0 | Pablo inquires about Eric's career path leading into Sideris and its acquisition by private equity alongside Robert Herjavec. | |
| The Founding Inspiration & Mission Behind Tenex.ai | 3 | 2 | 1 | 0 | Eric lays out his core philosophy that AI represents a PC-level revolution rather than a bubble, driving massive productivity gains. | |
| Human-Centric AI & the Global Fight Against Cybercrime | 5 | 3 | 1 | 2 | Pablo challenges the uniqueness of cybersecurity value propositions, noting that from the outside all cybersecurity companies sound identical. | |
| AI-Native Principles vs. Legacy Innovator's Dilemma | 6 | 2 | 1 | 1 | Pablo builds on Eric's innovator's dilemma thesis with his own analytical breakdown of native AI founders versus incumbents attempting to bolt AI onto legacy SaaS. | |
| Tenex's Value Proposition and Live Demo Showcase | 4 | 3 | 1 | 1 | Eric explains how Tenex closes enterprise contracts in under 60 days by showing real backend API execution rather than pre-packaged demo-ware. | |
| Outcome-Based Service Models vs. Black-Box Software | 7 | 2 | 0 | 0 | Pablo delivers an extended, sophisticated breakdown of the full-outcome service model versus pure software, using the hedge fund analyst analogy. | |
| Operational Scaling, Pricing Cohorts, and 100% Alert Coverage | 5 | 4 | 1 | 2 | Pablo presses on the exact mechanics of onboarding and pricing to hit $40M ARR in year one. Eric explains how Tenex covers 100% of alerts that human teams previously ignored. | |
| Go-to-Market Strategy and the Power of Domain Moats | 7 | 1 | 0 | 0 | Pablo articulates a comprehensive thesis on why vertical AI moats depend on domain expertise and rapid go-to-market speed rather than defensive software algorithms. | |
| Product-Market Fit, Startup Highs/Lows, and Founder Advice | 3 | 2 | 0 | 0 | Eric provides tactical advice on utilizing Google Gemini for cost efficiency and discusses navigating startup existential dread. |
Statements from this episode (14)
Foster: Cybercrime Emerged Directly from Online Payments and Financial Transactions
“Cybersecurity, the whole thing exists because that's where the money was. It's the same, that old Willie Horton quote of like, you know, why did you rob banks? Well, that's because that's where the money was. It was the same thing in cybersecurity. The moment …”
Foster: Early Hackers Breached Computers to Steal Internet Connection Time
“A lot of it in the very early days was all just use of services. Like, it cost money to be on the internet. You paid, in a lot of cases, you were paying literally, like, by the minute, To be on the internet. And so you had people who would break into your comp…”
Foster: Sideris Merged into a Combined $1B Cybersecurity Firm
“When we put the two companies together, it was essentially a billion dollar company. So, you know, we basically built about a, call it four or five hundred million dollar, two companies coming together to create that merged billion dollar company.”
Foster: Autonomous driving is a much easier problem space than cybersecurity
“One, I would tell you, like, self-driving cars is actually a much easier problem space than cybersecurity.”
Foster: Tenex engineers ship more code quarterly than during hyperscaler careers
“What we've hired a huge amount of hyperscaler software engineers. It's one of our big differentiators over the rest of our competitors in the managed security services industry is like I've invested in these world-class software engineers that none of my compe…”
Foster: Tenex on track to reach $43M revenue in year one
“We're going to close this first year. It's still a little bit of time left, but we'll probably land this first year, call it forty three million in revenue.”
Foster: Tenex contracted top-5 financial firm in under 60 days
“We went from first contact to them to contracting in less than 60 days. From the first time we met with them to a signed contract in less than 60 days”
Foster: Pure-software AI SOC companies will fail pivoting to services
“I think most of the other AI SOC software companies are going to end up either trying to become services companies, which they're going to fail miserably at because they've never actually built or run services companies. And guess what? It's way harder than yo…”
Foster: Top SaaS Giants Historically Succeeded by Selling Outcomes via Services
“Most of the greatest SAS companies were doing this historically too. They were selling outcomes. And they were delivering those outcomes in a lot of cases with, you know, a huge customer success or pro serve portion.”
Foster: Half of Tenex's first 10 customers were Fortune 500 companies
“The vast majority of our first customers were all global 2000. You know, our first 10 customers, half of them were publicly traded fortune 500 companies.”
Foster: Tenex customer ASPs cluster around $500k and $100k ARR
“One big cluster sitting right around 500 K and there's one big cluster sitting right around a hundred K and it's a, you know, double bell curve.”
Foster: An 80% accurate AI triage is vastly better than discarding alerts
“AI doesn't have to be perfect. It just has to be better than the humans. And when I especially take that route of, like, if you're throwing away millions of alerts a day, because you don't have the human manpower to look at them, if I can look at them with an …”
Foster: Tenex revenue is 40% outbound, 40% channel, and 20% inbound
“We are probably a third of our business is like direct outbound sales. About a third of our business comes through the channel where we've got other partners bringing us and then about a third, and it's actually probably more like 20%. So if you looked at it, …”