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Colossus (Invest Like the Best / Business Breakdowns)Podcast17 Jan 2023Source: joincolossus.comHost: Patrick O'Shaughnessy

Miles Grimshaw - The DNA of Software Companies - [Invest Like the Best, EP.312]

In plain words

This interview argues that investing in software companies requires a biologist's curiosity, not a physicist's formulas. Benchmark's Miles Grimshaw says the best companies don't want to be copies of existing versions—they want to be the best version of themselves. Key holdings discussed: Segment (switched from API-call pricing to per-user pricing, and dropped a big client), Benchling (started with academic users, walked away from a $1M client), and Lattice (bet all engineering resources on a second product at just $5-7M ARR—the product was 'crappy but effective').

AI SummaryAI-generated · may contain errors · verify against the original

At a Glance Benchmark partner Miles Grimshaw proposes evaluating software companies through a biological lens, emphasizing that early-stage investing requires attention to a company's "DNA" (e.g., investing in Segment, Benchling, and Airtable when they had fewer than 30 employees). Core views includ

~13 min full read · 9 sections
Deep Analysis

Miles Grimshaw - The DNA of Software Companies - [Invest Like the Best, EP.312]

At a Glance

Benchmark partner Miles Grimshaw (in his early 30s, who invested early in Segment, Benchling, and Airtable when each had fewer than 30 employees) proposes evaluating software companies through a biological lens, rather than applying SaaS physical formulas. Core thesis: The best companies do not want to become replicas of existing versions; they want to become the best version of themselves—investors should approach with curiosity and imagination, like Darwin stepping off a ship to discover new species, to uncover a company's unique DNA.


I. Investors Are Biologists, Not Physicists: Shifting from "Risk-Seeking" to "Change-Seeking"

Miles Grimshaw argues that early-stage software investing should not rely on physicist-style fixed rules (SaaS metrics, comparable company templates) but instead adopt a biological perspective.

  • Physicist Path: Seeking unbreakable rules and repeatable patterns—i.e., the "SaaS playbook" (speed from 1 to 5, efficiency, comparable companies). Grimshaw believes this approach seems easy but stifles uniqueness.
  • Biologist Path: Like Darwin aboard the Beagle exploring new continents, marveling at how new species adapt to their environments. The core question is "why" and "what could be," not "how to fit into a template."

Key Analogy: YouTube did not want to be Flickr for video; Amazon was not just Barnes & Noble online; Shopify was not Demandware for the mid-market. Grimshaw emphasizes: "People think early-stage investing is about risk-seeking, but the biological perspective is about change-seeking."

Benchling Case: When Grimshaw first encountered Benchling (only 5 people, a single standalone tool), the classic perspective would have said, "This is Viva for R&D." Instead, he chose to be curious: Why are academic institutions using it? This hinted at a natural evolutionary path in R&D from academia to industry. Result: When Viva went public, it had about 150 customers, while Benchling already had 1,000—applying the template would have killed its entire potential.


2. Three Dimensions for Evaluating Corporate DNA: Internal Stickiness, External Ecosystem, and Product Overlay

Grimshaw proposes three dimensions for assessing the "DNA" of early-stage companies, arguing that these are better predictors of long-term success than short-term metrics.

1. Can It Compound Within the Customer Base? — Information Half-Life and Stickiness

  • Information Half-Life: Assesses how "heavy" the data managed by the application is. Recruitment data has a half-life of about 3-6 months (one hiring cycle), with low switching costs; performance management data has a half-life of 12-24 months, offering stronger stickiness.
  • CRM's Excellent Half-Life: Salesforce's customer base from fiscal 2007 has grown 47x to date, and its fiscal 2012 customer base has grown 8-9x over 10 years — a sign of "good DNA."
  • Survival Through "Re-Evaluation Periods": When customers reach a new stage (e.g., growing from 50 to 2,000 employees), a new CXO may re-evaluate tools. Lattice's strategy is to "hold customers tightly between their first decision and graduation," rather than trying to fight natural upgrades.

2. Can It Build an Ecosystem in the External Market? — Agglomeration Effects and Career Empowerment

  • Platform Ecosystem: Others build businesses on top of you (e.g., Segment's integration ecosystem), and you take only a small cut — a symbiotic relationship.
  • Career Empowerment "Meta-Game": Figma not only accelerates collaboration but also makes design work visible across the company, elevating the status of the design department. Grimshaw asks: "Does using your product help users get promoted?"
  • Agglomeration Effect: A concept from urban economics — all bakers on the same street is actually better because demand clusters. Software companies should consider: How can ecosystem partners, executives, and recruitment channels all benefit from your success?
  • Value of User Conferences: Essentially "setting up a street and inviting all bakers to showcase" — celebrating possibilities, sharing progress, and enabling career advancement.

3. Can It Overlay Product Curves? — Timing and Courage for the Second Act

Grimshaw believes the second product launch should happen earlier than expected, and "bad but effective" is better than "perfect but late."

  • Data Points: Viva began developing Vault at around $50-70M in revenue; HubSpot launched its sales product around the time of its IPO (approximately $70-100M); Segment formed a team to develop Personas at around $30M ARR.
  • Lattice Case: As the third player in the HR market (Reflektive raised $100M, CultureAmp led), CEO Jack made a bold decision at just $5-7M ARR — redirecting all engineering resources from performance management to an employee engagement product. The product was "bad but effective," yet Lattice became the only mid-market company offering both, significantly improving close rates, while competitors could only respond through acquisitions.
  • Key Question: "At the board meeting five years from now, will we still feel there is too much to build?" — If the answer is yes, it indicates good DNA.

3. Don’t Copy Your Heroes: Lessons from API Company Pricing and Implementation

Drawing on his experience at Segment, Grimshaw illustrates that blindly imitating successful API companies (Twilio, Stripe) can lead to fatal mistakes.

  • Mistake 1: Copying the API pricing model. Segment initially priced by API calls, but found that customers had no idea which APIs were valuable. It later switched to MTU (Monthly Tracked User) pricing—the goal was to get customers to feed in all their user data, rather than agonizing over the value of each API.
  • Mistake 2: Copying the “self-service” model. API companies typically need only good documentation, but Segment discovered that customers required extensive change management—more akin to a database migration than a simple API call. Result: some million-dollar contracts remained unimplemented after 12 months, becoming “shelfware.” The solution: build a professional services team, set implementation expectations, and fundamentally overhaul the customer success model.

Grimshaw concludes: “We only later realized that we should have approached implementation, professional services, and support packages more like a vertical SaaS company.”


4. Can Pure-Play API Companies Be Good Businesses? — Market Skepticism vs. Real Stickiness

Addressing the widespread market skepticism toward pure-play API companies (using Twilio as an example), Grimshaw offers a different perspective.

  • Market data: Twilio generates $4B in revenue with a 50% gross margin, and its NDR still stands at 120%. Grimshaw argues: "If it were truly a fully commoditized business, you wouldn't see an NDR like this — customers would churn heavily, or there would be massive pricing pressure."
  • Core issue: Graduation risk (build vs. buy). Uber is the only known large-scale "build-your-own" case. Grimshaw believes the complexity of the API is key — Stripe's global payment processing is extremely complex, while Twilio's SMS sending is relatively simple, yet still involves significant hidden complexity.
  • Investment perspective: Twilio's free cash flow remains negative, with heavy investment in new projects (Segment, Flex, Video, etc.). As a shareholder, you are betting that these investments will generate high returns. However, looking solely at the core business, "I don't think we would say this is a bad business."

5. Founder’s Playbook for 2023: Revisiting Assumptions and Customer Selection

Grimshaw offers two core recommendations for founders in the current environment:

1. Revisit operating assumptions: Should the aggressive support model of the past be maintained? With stronger market positions, capital is now harder to come by for the 15th competitor. Brex exited a certain market segment—the question of "whether to exit" is worth every team’s consideration.

2. Distinguish between core maintenance and growth investment: For companies with $100M+ in revenue, ask yourself, "What is the minimum cost to maintain the status quo?"—anything above that is an investment, and the question becomes, "What is the return on this investment?"

Key lessons on customer selection:

  • Good customers: Those that push the market forward and truly need you (e.g., Robinhood for Plaid, Uber for Twilio, Shopify for Stripe, Regeneron for Benchling).
  • Bad customers: Large and shiny but slow and pulling you backward. Segment once saw platform traffic spike 10x on match days due to Hotstar (Indian cricket streaming) and ultimately chose to drop it. Benchling walked away from a $1M ARR customer, Gen 9. Lattice dropped a large client with 2,000 seats.
  • Grimshaw’s advice: "We would rather have $3 million in revenue than $5 million, if that $3 million is stronger and better positioned to lay the foundation for our future success."

Mentioned Positions

Position Guest Stance Key Data
Segment Bullish (Invested) Shifted from API pricing to MTU pricing; Dropped Hotstar customers; Launched Personas development at ~$30M ARR
Benchling Bullish (Invested) Started with 5 people; Academic user base; Dropped Gen 9, a $1M ARR customer; Regeneron as key customer
Lattice Bullish (Invested) Third to market; Launched second product at $5-7M ARR; Dropped a large customer with 2,000 seats
Airtable Bullish (Invested) No specific data provided
Twilio Neutral (Risk warning) $4B revenue, 50% gross margin, NDR 120%; Free cash flow still negative; Uber is the only known large-scale in-house build case
Stripe Bullish (Not invested but highly rated) Key customer Shopify; Global payment complexity extremely high
Figma Bullish (Not invested) Elevated design department status; Cross-functional internal network effects
Viva Neutral (As comparison) ~150 customers at IPO; Launched Vault at ~$50-70M revenue
HubSpot Neutral (As comparison) Launched sales product around IPO (~$70-100M); Adopted "launch-re-launch" strategy
OnlyFans Neutral (As comparison case) Message-based "whale" customer dynamics; Subscription + pay-per-message
Patreon Neutral (As comparison case) Tiered subscription model; Lacks message-based payment feature
Salesforce Neutral (As data point) Customer base grew 47x in FY2007; Customer base grew 8-9x over 10 years in FY2012
Greenhouse Neutral (As comparison) Recruitment data half-life of 3-6 months
Gong Neutral (As trend case) Collaboration tool around sales calls
Jasper Neutral (As AI case) Replaces high-value labor (marketing content)

Judgments Worth Remembering

1. “The best companies don’t want to be replicas of existing versions; they want to be the best version of themselves.” (Miles Grimshaw) — Investors should avoid applying templates and instead ask, “What will make this company the best version of itself?”

2. “The half-life of information determines software stickiness.” (Miles Grimshaw) — Recruitment data has a half-life of 3–6 months (low stickiness), while performance management data has a half-life of 12–24 months (high stickiness). Early on, this can be used to infer customer retention potential.

3. “At $5–7M ARR, Lattice shifted all engineering resources from the core product to a second product — the product was terrible but effective, yet it completely changed the competitive landscape.” (Miles Grimshaw) — Second product launches should happen earlier than expected; “terrible but effective” is better than “perfect but late.”

4. “Segment once had a $1 million contract that was never implemented after 12 months — we mimicked the self-service model of API companies, but what customers needed was change management on the level of a database migration.” (Miles Grimshaw) — Do not blindly copy the pricing and delivery models of successful API companies; the implementation experience of vertical SaaS may be more applicable.

5. “Twilio’s NDR was still 120% at $4B in revenue — if it were truly fully commoditized, you wouldn’t see that kind of customer retention.” (Miles Grimshaw) — Market skepticism toward pure API companies may be excessive; the core issue is graduation risk (build vs. buy), not commoditization.

6. “We would rather have $3 million in revenue than $5 million if that $3 million is stronger and lays a better foundation for future success.” (Miles Grimshaw) — Early customer quality matters more than quantity; proactively walking away from bad customers is an important capability.

7. “Figma not only accelerates collaboration but also makes design work visible to everyone in the company — it elevates the status of the design department and creates a career-empowerment ‘meta-game.’” (Miles Grimshaw) — The value of software lies not only in its functionality but also in how it reshapes power and status structures within an organization.

8. “OnlyFans created a ‘whale’ customer dynamic — the message-based payment model allows superfans to invest deeply, making it more like a gaming economy than traditional subscriptions.” (Miles Grimshaw) — Product architecture determines the business’s genetic code; understanding the demand curve and designing low-friction upselling paths is key.

9. “Pricing and packaging are founder-level genetic setting issues — don’t hand them over to the finance department. Ask, ‘From the perspective of the long-term customer journey, what architecture maximizes value capture?’” (Miles Grimshaw) — First set the global maximization framework, then optimize locally; avoid starting with “how to charge a little more.”

10. “Software is a blend of art and science — the best product experiences have aesthetics and craftsmanship, and this is just as important in B2B.” (Miles Grimshaw) — Product “magicians” (e.g., Figma’s Dylan Field) create simple yet beautiful products while naturally locking in cross-functional usage and ecosystem building.