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Colossus (Invest Like the Best / Business Breakdowns)Podcast16 Sep 2025Source: joincolossus.comHost: Patrick O'Shaughnessy

Jeff Horing - Building Insight Partners - [Invest Like the Best, EP.440]

In plain words

This piece unpacks how Jeff Horing runs Insight Partners, a $100B+ VC firm. Its key edge is a single $12B fund that can write both small and huge checks, letting it seamlessly 'double down' on winners—the highest-return move. Horing sees AI as a 'TAM accelerator' for existing software firms, not a disruptor. Key holdings: Wiz (invested at zero revenue, now doubling annually), Monday.com (started small, grew to $200M investment), and Sinch (same pattern).

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At a Glance

Jeff Horing is the co-founder and managing director of Insight Partners, which manages over $100 billion in assets. In this episode, he publicly deconstructs the operating mechanism of this tech investment firm in depth for the first time. The core thesis: Insight’s contrarian “single fund” strategy—flexibly allocating $12 billion across deals ranging from $10 million growth-stage investments to multi-billion-dollar acquisitions—is its most critical competitive advantage. This structure enables seamless execution of “doubling down,” the highest-return action, while eliminating conflicts of interest inherent in multi-fund structures.

~14 min full read · 6 sections
Deep Analysis

Theme 1: The Contrarian "Single-Fund" Strategy — The Art of Risk Management and the Power of "Doubling Down"

Jeff Horing believes that Insight's "single-fund" structure is its core advantage over nearly all peers, addressing two key issues: risk management and optimal capital allocation.

  • Flexibility in Risk Management: Horing uses SoftBank's Vision Fund as an example, noting that it can write a $200 million check, but for a $100 billion fund, that amount carries a risk weight equivalent to just $2 million in a $10 billion fund. Insight's single fund similarly allows for this "risk hedging": by adjusting the size of individual investments, it can "bet small for fun" on early-stage projects and "go all in" on high-conviction opportunities, without being constrained by the investment scope of different funds. Horing states: "You can manage risk with check size... you can look at different stages with a slightly different lens."
  • "Doubling Down" is the Highest-Return Move: Horing argues that the most optimal decision in investing is to "double down," because you have far more information than at the time of the initial investment. The single-fund structure allows Insight to execute this seamlessly. He gives an example: "We've taken a $5 million position up to $1 billion... Without that $5 million position, we would never have seen the $1 billion opportunity." In its largest exits, such as Monday.com and Sinch, the initial investments were all under $25 million, with subsequent additions bringing them to $200 million.
  • Eliminating Multi-Fund Conflicts: Horing points out that many peers have separate early-stage and growth funds, which creates a "mezzanine" problem — when a company scales, its financing round becomes too large for the early-stage fund and not typical enough for the growth fund, leaving it "homeless." A single fund completely avoids such conflicts and eliminates the need to manage profit allocation across different funds.

Extrapolation and Falsification: The potential risk of this strategy lies in the lack of discipline from third-party pricing, which could lead to "believing one's own lies" or "chasing bad money." Horing admits: "You can get a little loose with your judgment... If you're not careful, you will definitely see yourself chasing bad money." The signal to validate this strategy's effectiveness is whether Insight can consistently generate excess returns from "doubling down" and whether its investment discipline can withstand the temptations of a market frenzy.


Theme 2: "The Sourcing Machine" — A Systematic, Scalable, Young-Talent-Driven Deal Flow Engine

Horing describes Insight's "sourcing machine" as a systematic, scalable competitive advantage, centered on a team of 60-80 young analysts who proactively blanket-contact global software companies.

  • Origin and Evolution: The strategy originated from Horing's time at Warburg Pincus, inspired by TA Associates' Kevin Landry, who sourced deals by scanning job ads and cold-calling. After founding Insight, Horing institutionalized this approach, starting with hiring the first undergraduate analyst in 1999 and gradually building it into a "sourcing machine" with annual recruitment from top schools and a systematic training program.
  • Operating Mechanism: Analysts are given significant autonomy with no fixed "territory," allowing them to contact any company freely. Once a potential deal is identified, they can "claim" it through an internal system and hold exclusive rights for a certain period. If not followed up, the deal is reopened. Horing describes his management style as "throwing you into the water and letting you swim." The analysts' job is "sales" — they must convince successful founders to take their calls. Horing notes that some analysts need to make 25 calls, send several FedEx packages, or even "stake out on someone's street corner begging for a meeting."
  • Integration with the Investment Process: After analysts screen attractive companies, they escalate to vice presidents or partners, and ultimately to investment committee (IC) members. Horing reveals that his schedule is entirely arranged by these 24-year-old analysts: "All of today's meetings were set up by analysts... It's quite interesting."
  • Talent Output and Culture: Insight has become a "coaching tree" in the investment world, having spawned 16-18 funds founded by former employees, with over 30 former employees serving as partners at other firms. Horing believes this stems from the fact that young analysts at Insight get far more "at-bats" than their peers, enabling them to rapidly build pattern recognition skills.

Deduction and Falsification: The challenge of this model is that as the market becomes more crowded, founders increasingly prefer to speak only with senior partners. Insight's response is to have young analysts build deep trust and have partners ready to "jump on a plane" at any time. The signal to verify its effectiveness is whether Insight can consistently discover and win "hidden champions" outside Silicon Valley's mainstream view through this system (e.g., a Norwegian salmon farming software company).


Theme 3: The Five-Factor Framework for Perfect Investments and "College-Level" Software Math

Horing proposes a five-factor framework for evaluating software companies and shares "college-level" software analysis metrics that outperform industry averages.

  • Five Factors for a Perfect Investment:

1. Big ROI: Creates significant value for customers.

2. Big ASP: Compared with existing giants in the target market (e.g., Epic), assesses the potential ceiling of scale.

3. Time to Value: How quickly customers can see value. Horing contrasts SAP (years to implement) with OpenAI (instant use), noting that fast time to value is a key growth driver.

4. Exceptional CEO: Capable of leading the company to success.

5. Strong Technical Team: The product has been the core driver of results over the past decade.

  • "College-Level" Software Metrics:
  • Gross Dollar Retention (GDR) Over Net Dollar Retention (NDR): Horing considers NDR "one of the least informative numbers." GDR measures customer stickiness and is fundamental to predicting future outcomes. He asserts: "Very few companies with low GDR (around 80%) can enter the top 20 by market cap... You can count on three fingers the companies with that statistic." Low GDR means the company must fill a massive revenue gap each year, leading to high customer acquisition costs (CAC).
  • Second Derivative (Growth Rate of New Business): The "rate of change" in new business growth is more important than the growth rate itself. Many companies (especially vertical software) may see flat new business volumes, but with a small base, the growth rate still appears high. Horing notes: "If new business volume is flat, you can 'copyright' that number... but in five years, your exit growth rate will be completely different from Google's (15 consecutive years of 100% compound growth)."
  • LTV/CAC as the Ultimate Goal: GDR is an excellent predictor of LTV, while CAC reflects market pull. The core is understanding the unit economics.

Deduction and Falsification: Horing emphasizes that Insight avoids investing in companies with low GDR unless there is confidence in changing it. However, at least half of the partners believe no compromise should be made on any metric. The signal to validate the framework's effectiveness is whether companies selected by Insight based on this framework significantly outperform market averages in long-term returns.


Theme 4: AI as a "TAM Accelerator," Not a Disruptor

Jeff Horing believes that AI's primary impact on existing software companies is as a "TAM accelerator," rather than a disruptor, with its greatest threat being the siphoning of budgets from traditional software.

  • Dual Impact on Incumbent Companies:
  • Positive (TAM Accelerator): AI enables software companies to solve customer problems that were previously impossible to automate, thereby significantly expanding their addressable market. Horing cites an example: "Several vertical application companies similar to CRM where I serve on the board... if we can automate 95% of the time you spend on data entry, that would be extremely valuable." He notes that over half a dozen of his portfolio companies have re-accelerated growth through new AI-powered products.
  • Negative (Budget Squeeze): AI is sucking the "air" out of the traditional software market. Horing argues: "Buying CRM software today is no longer the coolest thing... That's not my top priority. I want to automate something else." This will impact the growth rates of traditional software companies.
  • Skepticism Toward Disruption: Horing does not believe AI will easily disrupt complex applications like SAP. He points out: "Software has never been a technology moat; it has always been a business knowledge moat." Past generations of productivity tools (e.g., 4GL) did not lead to the displacement of existing incumbents. He adds: "I can't explain why, but we haven't seen software development costs collapse in our portfolio companies."
  • Investment Opportunities: Insight has made approximately 25 investments in "agentic AI," seeing significant potential in the business sector. At the same time, he has also invested in foundational model companies like Anthropic, but emphasizes that this is done through his public market strategy, not the core fund.

Deduction and Falsification: Horing's judgment can be falsified. If, within the next 3-5 years, there are cases where AI-native companies successfully disrupt large traditional software incumbents (e.g., SAP, Oracle), then his "TAM accelerator" view will be challenged. Conversely, if traditional software companies significantly increase ARPU and expand their customer base through AI features, his view will be validated.


Mentioned Positions

Position Analyst Stance Key Data
Wiz Bullish (success case) Invested when revenue was zero; net new business doubled or more annually for six consecutive years.
Monday.com Bullish (success case) Revenue at investment was approximately $5 million; initial investment below $25 million, later increased to $200 million.
Sinch Bullish (success case) Revenue at investment was approximately $4–5 million; initial investment below $25 million, later increased to $200 million.
Databricks Neutral (viewed as a classic growth trade) Described as a case that "looks like a classic growth trade when divided by 10."
Anthropic Bullish (via public market strategy) Invested in a recent large funding round; CEO Dario has deep insights into the business, and recent data on coding capabilities is "incredible."
VMware Mentioned (as a best-in-class PE/VC deal case) EMC acquired it for $650 million, later sold for $60 billion, generating approximately $60 billion in returns.
Arm Mentioned (as a positive case for SoftBank Vision Fund) Masa invested; Horing believes the return is approximately 4x.
Epic Mentioned (as a market benchmark) Average annual sales of $10 million in the hospital market, used to gauge the potential ceiling of ASP for other companies.
SAP Mentioned (as a comparison case) Long implementation cycle (3 years), but extremely high customer stickiness.
Uber Mentioned (as a missed opportunity) Insight debated intensely internally and ultimately passed on the investment; Horing admits it was a "huge mistake."
Twitter Mentioned (as a successful investment) Successfully invested before Musk's acquisition.

Judgments Worth Remembering

1. “Single-fund” is the highest-return structure (Jeff Horing): Because it enables seamless execution of “doubling down”—the action with the greatest information advantage in investing—and eliminates conflicts of interest across multiple funds. Supporting evidence: Some of Insight’s largest exits (Monday.com, Sinch) began with small investments and were followed by substantial follow-on additions.

2. Gross Dollar Retention (GDR) is far more important than Net Dollar Retention (NDR) (Jeff Horing): NDR is “one of the least informative numbers,” while GDR is fundamental to predicting future outcomes. Supporting evidence: Companies with low GDR (around 80%) are almost impossible to become top-20 software companies by market cap, as they need to fill a massive revenue gap every year.

3. The “second derivative” of new business (the change in growth rate) is more critical than the growth rate itself (Jeff Horing): Many companies have flat new business volumes but, due to a small base, still show high growth rates. Supporting evidence: Vertical software companies tend to saturate their markets quickly, causing new business volumes to stagnate, and ultimately their exit growth rates fall far short of Google’s (which compounded at 100% for 15 consecutive years).

4. Insight’s “sourcing machine” is its deepest moat (Jeff Horing): A team of 60-80 young analysts systematically and proactively reaches out to cover global software companies, uncovering “hidden champions” that are not on the mainstream radar. Supporting evidence: Insight has incubated 16-18 funds, and over 30 former employees have become partners at other firms, demonstrating its talent and pattern recognition capabilities.

5. AI is a “TAM accelerator” for existing software companies, not a disruptor (Jeff Horing): AI enables software to solve customer problems that were previously impossible to automate, thereby significantly expanding the market. Supporting evidence: More than half a dozen of Insight’s portfolio companies have re-accelerated growth through new AI products; at the same time, the biggest threat from AI is its potential to cannibalize budgets from traditional software.

6. Five elements of a perfect investment: Large ROI, Large ASP, Fast Time-to-Value, Exceptional CEO, Excellent Technical Team (Jeff Horing): Wiz meets nearly all five elements, especially the rare combination of “fast time-to-value” and “high ASP.”

7. Insight’s “X-factor” evaluation method: Remove you and see if value is added (Jeff Horing): Given the long investment return cycle and high reliance on luck, Horing assesses talent by evaluating an individual’s “input” contributions across the four stages of “finding, winning, selecting, and enabling,” rather than just short-term “output.”

8. Insight’s culture is “push you off the cliff,” not “pull you back” (Jeff Horing): Horing positions himself as a “tush push” (giving a push from the 1-yard line), encouraging partners to take calculated risks and providing a safety net. He believes that for generational companies, risk appetite is the biggest challenge, and conservatism leads to missed opportunities.