Invest Like the Best [EP.440]: Jeff Horing – Building Insight Partners

Date: September 16, 2025

Host: Patrick O’Shaughnessy

Guest: Jeff Horing (Co-founder & Managing Director, Insight Partners)

Episode Overview

In this candid and in-depth conversation, Patrick O’Shaughnessy interviews Jeff Horing, the co-founder and managing director of Insight Partners, in one of Jeff’s first major public interviews. The episode explores the origins and evolution of Insight Partners—one of the world’s leading tech investment firms, with over $100 billion AUM. Jeff unpacks the mechanics of Insight’s prolific deal sourcing, their unique "one fund" strategy, hard-won lessons about investment selection, and building world-class talent pipelines. The discussion ranges from practical investing math to the impact of AI, talent development, private-to-public market dynamics, and what separates great software companies—and great investors—from the rest.

Key Discussion Points & Insights

1. Deploying Mega-Funds and Learning from the Vision Fund ([05:38]–[10:54])

• Jeff reflects on the challenge of deploying a $100B fund like the original SoftBank Vision Fund.
  • The best private equity/venture deals of all time had major synergy and control—e.g., EMC buying VMware, or PayPal—with "dream" outcomes.
  • If in charge of $100B: “That was a dream I've always had... competing with Microsoft or Palo Alto or eBay for a deal, giving entrepreneurs both liquidity and continued upside.” ([06:55])
• He critiques shifting late-stage venture norms.
  • The size and scale of today’s private company capital raises have changed the landscape, and the mega-fund approach is harder to replicate in 2025.

2. The “Right” Fund Size and One Fund Strategy ([10:03]–[26:15])

• Insight currently deploys about $3B/year from a ~$12B fund.
  • "We definitely don't feel capital constrained to the opportunity set." ([10:05])
• The one fund strategy: Insight doesn’t split its capital by stage or sector.
  • Advantages:
    • Superior risk management (can make small/big checks to manage risk)
    • Doubling down on the best companies after learning more—a "double down bet" strategy: “If you went back in time and looked at our double down checks, they were our best checks.” ([23:59])
  • Trade-offs:
    • Less third-party price validation (potential to “believe your own BS”)
    • LPs have trouble “putting us in a bucket”—Insight is hard to categorize.

3. The Evolution of Software Investing: “College Math” for Growth ([13:14]–[16:28])

• Jeff's education as an investor: Dramatic improvement in understanding which KPIs matter.
  • “Our analysis of what numbers matter has changed a lot... Now we’re closer to college [math].” ([13:14])
• The key metrics:
  • Gross Dollar Retention (GDR) trumps Net Dollar Retention (NDR).
    • “GDR, how sticky is your customer base, how resilient is that... There are very few companies with lowish software, low 80s GDR, in the top 20 market cap businesses.” ([14:07])
  • Second derivative of growth: The change in net new bookings, not just the growth rate.
  • Distillation: “Buying cheap in technology, there’s not a long list of really rich people who’ve done that. As compared to the people who’ve just bought the Dream.” ([16:28])

4. Insight’s Investment Framework – The Five Ingredients ([18:56]–[21:49])

• Jeff’s model for a “perfect investment” includes:
  1. Big ROI / value prop
  2. Big Average Selling Price (ASP)
  3. Fast time-to-value for customers
  4. Outstanding CEO
  5. Strong tech and management team
• Notable quote: “Wiz might be the...when that checked all five. Maybe Monday had a bunch of that too. But to get the time to value and the ASP is really rare.” ([21:49])

5. Building a High-Powered Sourcing Machine ([29:26]–[44:59])

• Origin story: Jeff was inspired by TA Associates’ cold-calling strategy—ripping ‘help wanted’ ads out of newspapers as a means to uncover deals. Insight doubled down and institutionalized this.
  • "I started at Warburg. I sourced a bunch of deals that way, which was pretty unusual..." ([31:31])
• Sourcing at scale:
  • Today, 60–80 analysts and associates systematically canvas global opportunities.
  • No “territories”—everyone has autonomy; deals are “claimed” on pipelines until acted on.
  • The culture is competitive but extremely collaborative (“We tend to overcompensate for cooperation.” [39:36])
  • Insight alumni have founded 16–18 VC and PE funds—a “coaching tree” of talent.

6. Portfolio Construction and Bet Sizing Evolution ([44:59]–[52:57])

• Stage is not a strategy: Insight resists limiting itself to a stage.
  • They pioneered “venture buyouts”—taking control of founder-led software companies before it was mainstream.
  • “There’s tens of thousands of those now. They’re good companies. They should belong somewhere.” ([45:28])
• Flexible allocation:
  • Typical portfolio: 10% early stage, 30% growth, 30–40% venture buyout, 20% LBO.
  • Return targets: ~30% gross IRR on non-buyouts, 5 points lower for buyouts. ([52:01])

7. Winning Deals, Adding Value & Retaining Talent ([58:36]–[60:24])

• How Insight wins competitive deals:
  • “Showing up hard, getting on planes, invited or uninvited.”
  • Operational value creation: “We bought a pretty expensive, large interest in Riviera Partners...the largest tech recruiting firm...especially in AI age, where talent is everything.” ([59:29])
  • Building a resource-rich platform around sales, marketing, and exec recruiting.
• Culture: “We want to be the most helpful voice at the table and we don’t need credit for that help.” ([89:28])

8. Building and Maintaining an Institutional Mindset ([60:24]–[69:47])

• “Only four things we do: find deals, win deals, select deals, and make them work.”
  • On scale: Sourcing is overwhelmingly improved; winning is easier with more resources; and operational support adds further value.
  • Geographic expansion is hard; specialization is a reliable advantage.

9. AI as a TAM Accelerator, Not Existential Threat ([80:19]–[86:28])

• AI (“the nuclear bomb that’s gone off in a good way”):
  • Unique among past waves—immediate value versus earlier slow “vision” efforts ([80:39]).
  • “It's also sucking a lot of the air out of the traditional software market...But it's clearly a phenomenal growth engine.”
  • Not threatening to core product moats: “There was never a technology barrier [in software], it was always a business knowledge barrier...”
  • Example: AI enables SaaS companies to automate data collection and massively expand market potential.
  • “My suspicion is this is largely TAM expanding for the established companies.”

Memorable Quotes & Moments (with Timestamps)

• On deploying mega-funds:
  • “If I had $100 billion, that's what I would do because I think you could really differentiate yourself tremendously from the pack.” – Jeff ([07:53])
• On understanding SaaS retention:
  • “It was amazing what we continue to learn about metrics that really are the best predictors for future outcomes, which is really the dream, especially in growth investing.” – Jeff ([13:37])
• On biting off complexity as you scale:
  • “Saying yes leads to growth and it also leads to customization and a big trade off. The more you grow, the more complexity you absorb.” – Patrick ([02:01])
• On disciplined sourcing:
  • “No one tells you, go call xyz. You have to kind of sort this out yourself...It's pretty much a self-starter, highly personalized initiative.” – Jeff ([36:49])
• On outlier investments:
  • “Buying cheap in technology, there's not a long list of really rich people who've done that. As compared to the people who've just bought the Dream.” – Jeff ([16:28])
• On value of Insight’s analyst program:
  • “The training you get at 23 at insight is like no other job in the industry. Because all you’re seeing is at-bats. You were seeing more pitches than any other firm out there.” – Jeff ([55:24])
• On risk appetite and firm-building:
  • “Risk appetite is probably the biggest challenge. Once in a while they get a wacky successful investor who just re-energizes the firm's risk tolerance and it goes back up again.” – Jeff ([78:37])
• On culture and humility:
  • “We don't have to be the loudest voice at the table ever. We want to be the most helpful voice at the table and we don't need credit for that help.” – Jeff ([89:28])
• On AI and software disruption:
  • “The bear case on software is, ‘hey, I could just use Claude to write my next SAP.’ We're not losing any sleep over that. Quite the opposite.” – Jeff ([83:17])
• On winning and competitive drive:
  • “I just want to get my own score as low as possible...I think the culture of the firm has maybe modeled after that. I attracted people like that.” – Jeff ([86:45])

Timestamps for Major Segments

| Segment | Timestamp | |------------------------------------------------------|-----------------| | Opening—deploying $100B funds, Vision Fund lessons | 05:38–10:54 | | Fund sizing and the "One Fund Strategy" | 10:03–26:15 | | Evolution of SaaS metrics: “College math” | 13:14–16:28 | | Five Ingredients for Perfect Investments | 18:56–21:49 | | Insight’s sourcing engine: origin, evolution | 29:26–44:59 | | Talent, incentive models, and coaching tree | 36:29–55:24 | | Portfolio construction and flexible bet sizing | 44:59–52:57 | | How Insight wins and supports companies | 58:36–60:24 | | Institutionalizing judgment, strategy, and scale | 60:24–69:47 | | Dealing with intangibles in investing | 69:47–71:03 | | Valuations and aftermath of 2021/22 market | 71:03–74:37 | | Staying in the firm’s investing lane (not consumer) | 74:37–75:31 | | Jeff’s method for first meetings with founders | 75:31–77:02 | | Management style, risk taking, and the “X factor” | 77:02–80:19 | | AI’s implications for software and investing | 80:19–86:28 | | Winning, culture, and drive | 86:28–87:35 | | Selling and exit lessons | 87:35–88:42 | | Insight’s future outlook and culture | 88:42–89:28 | | Kindest thing—mentorship stories | 90:46–91:53 |

Final Thoughts & Takeaways

• Institutional advantage: Insight’s scale, discipline, and focus on software enable a unique blend of systematic sourcing and opportunistic doubling down.
• Deep culture: From analyst to partner, Insight invests in talent, creating a virtuous circle and an unusually productive alumni network.
• Realism on risk and luck: Jeff is open about flaws, mistakes, and the heavy dose of luck even in great outcomes.
• AI is opportunity, not threat: The firm views AI as an enormous TAM expander for software, not an existential risk.

For a deeper dive—including the origin stories, metrics, and learning moments—listen to the full conversation at Colossus.