Hello Builders!
This week’s edition is a little different. This one’s a conversation-inspired field guide to category creation, go-to-market sequencing, and culture that scales.
SecurityScorecard’s journey offers a masterclass in turning an unmeasured pain (third-party cyber risk) into a measurable standard (security ratings), then extending it into a collaboration platform. Big takeaways: create a metric before a market, win with design partners, delay GTM until the product earns it, invest in architecture early, and treat culture as an operating system - not a poster.
Opening Frame: The wake-up call that created a category
A single incident set the trajectory: while integrating a vendor tool, unencrypted credit-card data from other companies appeared in the upload flow. That “outside-your-control” risk moment crystallized a universal job-to-be-done: “How do I know if the companies I rely on are safe?”
From there, SecurityScorecard pioneered a security ratings model - type a company’s name, get a score correlated with breach likelihood - used across three durable use cases:
Third-party risk (procurement & supplier oversight)
Cyber insurance underwriting (pricing risk)
Board reporting & benchmarking (governance)
They later layered on MAX (supply chain detection & response): not just measuring risk, but collaborating with suppliers to reduce it: workflows, outreach, remediation, and shared visibility.
PMF lesson: If the problem is invisible, instrument it. If it’s instrumented, operationalize it.
Playbook Move #1: Make the invisible measurable
Create a metric before you create a market. Their pipeline:
● Collect diverse signals across the internet (exposure, patch cadence, malware indicators).
● Discover the external attack surface (assets, subsidiaries).
● Benchmark against a decade of outcomes to correlate score ↔ breach risk (e.g., poor grades → ~13× higher breach likelihood).
Why this works: Standards become language. Language becomes category. Categories buy you time, margins, and a defensible position.
Founder prompt: What single leading indicator could compress your customer’s uncertainty into one number that everyone can rally around?
Playbook Move #2: Sequence GTM after truth, not before it
Early growth focused on R&D and product, deliberately waiting to hire sales/marketing until Year 2. Storytelling stayed founder-led to secure visionary design partners (<$2M ARR phase).
What they’d redo: spend more time on architecture upfront to avoid painful rewrites at scale.
Signals you’re ready to scale GTM:
● You can explain your value in a sentence and demo it in a minute.
● Design partners pull roadmap items into production use, not pilots.
● Architecture withstands 10× data/tenant growth without re-platforming.
Anti-pattern: spraying headcount on go-to-market before the product can carry it.
Playbook Move #3: Build a moat from interactions, not just models
In a world where foundational AI capabilities commoditize, the defensible layer becomes:
● Proprietary historical interactions (who engaged, what changed, how outcomes shifted)
● Embedded position in workflows (alerts → actions → outcomes)
● Network effects (suppliers collaborating with buyers)
Founder prompt:Where can you capture interaction data that competitors can’t copy and that makes your product smarter for the next customer?
Playbook Move #4: Culture is your scaling system
Early days were co-located to accelerate osmosis, then evolved into a distributed org with intentional in-person time to maintain trust. Culture shows up in behaviors (e.g., leaders being on time) more than slogans.
● Hire for low-ego excellence. The hardest exits are brilliant but toxic performers - optimize for team velocity over individual brilliance.
● Design deliberate comms as you scale (no more hallway fixes).
● Coach for sustained peak performance. Help people reignite passion; don’t just light fires under them.
Founder prompt: Which small leader behaviors are silently authorizing the opposite of your values?
Playbook Move #5: Fundraising truth table & runway math
Four constraints govern scale: Market pull → Team speed → Unit economics → Cost of capital.
● Runway rule of thumb: keep ~12 months of cash; start raising ~6–8 months before needed to preserve leverage.
● Hardest round (today): often Series B - the leap from a handful of “friendlies” to repeatable, scalable revenue.
● Investor fit matters: pick partners who get your domain, give tough feedback, and will barbecue with you on Saturdays.
Founder prompt: What exact milestone justifies your next valuation step and how many months of burn will it take to get there with 2 chances at a term sheet?
AI & the Risk Surface: “Robots vs. robots”
● Attackers: lower barriers via deepfakes, automated recon, and off-the-shelf malware.
● Defenders: AI to collapse alert floods into 1-2 actions that matter; agentic workflows that let one analyst do the work of five.
Strategic stance: Treat AI as a force multiplier for defenders; embed it where decisions happen (supplier outreach, remediation paths, exception handling).
Closing Thought
The enduring lesson from SecurityScorecard: The fastest path to PMF is often measuring what everyone feels but no one can see, then turning that measurement into a shared operating system. Do that, and you won’t just win deals; you’ll define the terms on which the market competes.
Until next time,
Firas Sozan
Your Cloud, Data & AI Search & Venture Partner
Find me on Linkedin: https://www.linkedin.com/in/firassozan/
Personal website: https://firassozan.com/
Company website: https://www.harrisonclarke.com/
Venture capital fund: https://harrisonclarkeventures.com/
‘Inside the Silicon Mind’ podcast: https://insidethesiliconmind.com/