Julian Cardarelli’s Post

Was at a VC dinner last night where the main topic was the max divergence of public multiples (now 5.2x fwd EV in software and 15.9x for top cos) vs private VC multiples. In AI land we’re back at 2021-era 100x multiples, this time without the elevated public comps. Growth funds are modeling time to “breakeven” from multiple compression at over 2 years with even the most optimistic company forecasts. While there will likely be some number of new generational companies built this cycle, many funds will likely lose $ in the hype, as they had in the 2021 cycle. What will happen from here? - VC consolidation will continue but slowly. As 2021 era investments eventually become marked to mkt, LP allocations to VC will continue to adjust to pre-2021 era. A couple “index” funds may continue to accumulate capital but otherwise selection and discipline (and ability to invest in the long-term winners) will separate returns - AI multiples will remain high. In many cases AI companies are raising large rounds because they are demonstrating remarkably fast revenue and user growth. However, retention remains a leading indicator of which products may reach true PMF (eg it is actually helping people do something 10x faster / cheaper / better) vs which are enjoying AI novelty. As soon as a company’s growth declines from 2-3x to <50% many will struggle to raise a next round at such a high watermark. Understandably many are stockpiling funds while they can now - As we’ve seen from WWDC, in many use cases, incumbents are the largest threat and most likely long-term winner. The M&A market unlocking (post elections) would be a big positive for VC DPIs

Good summarization of the dilemma facing investors. Agreed Amy Wu there will be generational companies but at most in low single digits (OpenAI seems that one). AI startups will have tough survival rates - due to being sandwiched between fast following cash rich hyperscalers (delivering full stack of AI) and product whales (like Apple who can in one OS update can make dozens of AI writing assistant startups irrelevant).

Posting a tweet from Amy Wu here. What a great summary where VC stands today. Must read for all founders. Slide courtesy of Jamin Ball. His weekly newsletter also a must read. "- Was at a VC dinner last night where the main topic was the max divergence of public multiples (now 5.2x fwd EV in software and 15.9x for top cos) vs private VC multiples. In AI land we’re back at 2021-era 100x multiples, this time without the elevated public comps. Growth funds are modeling time to “breakeven” from multiple compression at over 2 years with even the most optimistic company forecasts. While there will likely be some number of new generational companies built this cycle, many funds will likely lose $ in the hype, as they had in the 2021 cycle. What will happen from here? - VC consolidation will continue but slowly. As 2021 era investments eventually become marked to mkt, LP allocations to VC will continue to adjust to pre-2021 era. A couple “index” funds may continue to accumulate capital but otherwise selection and discipline (and ability to invest in the long-term winners) will separate returns - AI multiples will remain high. In many cases AI companies are raising large rounds because they are demonstrating remarkably fast revenue and user growth. However, retention remains a leading indicator of which products may reach true PMF (eg it is actually helping people do something 10x faster / cheaper / better) vs which are enjoying AI novelty. As soon as a company’s growth declines from 2-3x to <50% many will struggle to raise a next round at such a high watermark. Understandably many are stockpiling funds while they can now - As we’ve seen from WWDC, in many use cases, incumbents are the largest threat and most likely long-term winner. The M&A market unlocking (post elections) would be a big positive for VC DPIs"

A great post by Amy Wu Was at a VC dinner last night where the main topic was the max divergence of public multiples (now 5.2x fwd EV in software and 15.9x for top cos) vs private VC multiples. In AI land we’re back at 2021-era 100x multiples, this time without the elevated public comps. Growth funds are modeling time to “breakeven” from multiple compression at over 2 years with even the most optimistic company forecasts. While there will likely be some number of new generational companies built this cycle, many funds will likely lose $ in the hype, as they had in the 2021 cycle. What will happen from here? - VC consolidation will continue but slowly. As 2021 era investments eventually become marked to mkt, LP allocations to VC will continue to adjust to pre-2021 era. A couple “index” funds may continue to accumulate capital but otherwise selection and discipline (and ability to invest in the long-term winners) will separate returns - AI multiples will remain high. In many cases AI companies are raising large rounds because they are demonstrating remarkably fast revenue and user growth. However, retention remains a leading indicator of which products may reach true PMF (eg it is actually helping people do something 10x faster / cheaper / better) vs which are enjoying AI novelty. As soon as a company’s growth declines from 2-3x to <50% many will struggle to raise a next round at such a high watermark. Understandably many are stockpiling funds while they can now - As we’ve seen from WWDC, in many use cases, incumbents are the largest threat and most likely long-term winner. The M&A market unlocking (post elections) would be a big positive for VC DPIs

As I continue to dig deeper into the VC asset class, starting with its origin and comparing it to the "whaling" industry, the return profile of the “VC” and “whaling” as asset classes - It's time to examine the total investments made in the VC asset class over the last 10 years. $3.5T is the total VC investments in the last 10 years, doubling from $170B in 2013 to $344B in 2023. If this data is sliced by quarters, no single quarter stands out. Investments in all quarters have been more or less evenly spread, with Q1 at $831B, Q2 at $852B, Q3 at $849B, and surprisingly Q4 leading the pack with $909B, despite the notion of lower investments due to the holiday season. Will VC investments continue on this trajectory? Will VC investments increase or decrease with all the advancements in AI, where opportunities to build million-dollar and billion-dollar companies exist with limited resources? Thoughts? #VC #venturecapital

🚨 The Most-Read Deal Today: J.P. Morgan Has Completed Advisory on Scale AI’s $1bn Y Combinator-Bid Series F Funding Round - Deal Summary Krugman Insights offers Reliable and Comprehensive Insights across M&A, Investment Banking, Private Equity, and Asset Management. 🔎 Placement Agents on the Deal: J.P. Morgan, Allen & Company LLC. 🔎 Key Investors: Y Combinator, Index Ventures, NVIDIA, Amazon, Wellington Management 💡 Scale AI has successfully raised $1 billion in its Series F funding round, led by Accel and advised by JP Morgan. This funding, which values Scale AI at nearly $14 billion, aims to further their mission of ensuring data abundance for advanced AI model development. Scale AI, renowned for addressing data challenges for industry leaders like OpenAI, Meta, and Microsoft, will use this capital to enhance its offerings for both public and private sector clients, including the U.S. Department of Defense. The funding will also support projects such as the White House-announced DEFCON 31 red-teaming event. The Series F round evidences clearly the continued strong interest in AI-driven innovation and the critical role of high-quality data in this sector. ✅ FULL ARTICLE HERE: https://lnkd.in/eXKSp3R5 ✅ TRY 30 DAYS FREE: https://lnkd.in/eBHYx37M #JPMorgan #ScaleAI #Accel #MergersAndAcquisitions #InvestmentBanking #CorporateFinance #TechFunding #StrategicPartnership #GlobalGrowth #FinancialAdvisory

Here are 5 predictions for successful Private Equity growth in 2024.

Silicon Valley Bank's H1 2024 State of the Markets Report goes live today - and it's incredibly good. A few key takeaways below, and you can download the full report here: https://lnkd.in/ez3-6-JJ AI: 1 in 4 funds closed in 2023 had a stated focus in AI; and AI accounted for 1 in 5 VC deals in 2023. DOWN ROUNDS: Over 60% of companies that raised a down round since 2016 have gone on to raise another equity round—good news for the 1 in 4 Series D+ companies raising down rounds in 2023. $$$: Revenue growth for companies that successfully raise a series A has fallen from 176% in 2020 and 2021 to 127% in 2022 and 2023. VALUATIONS: Seed Valuations have increased 25% since 2021 despite every other stage experiencing declines — with series D+ valuations falling 59%. RUNWAY: The typical early-stage company has just 10.3 months of runway; with sectors like frontier tech falling to just 7.4 months of runway. GROWTH: For companies successfully raising venture deals, revenue growth has slowed by 36 to 42 percentage points depending on the company size. BURN: Nearly 70% of startups reduced net burn year over year in 2023, leading to an overall improvement in EBITDA margins for VC-backed tech companies. EXITS: 21% of companies exiting today via M&A are selling for less money than they raised.

If investors have learned anything from the funding craze of 2021, it’s that revenue growth at all costs isn’t always the best strategy.

Not understanding Artificial Intelligence is a liability and a risk as it will play a meaningful role in the advancement of the merger and acquisition environment. A&M is M&A.