Stuff worth reading: My 2024 highlights

December 2023:

• Lakestar published its 2023 deep-tech report: Key insight -
  Deep tech start-ups take ~35% more time and ~50% more capital to reach $5m ARR, suggesting more dilution for investors to reach a similar product-market-fit. Interestingly, they take the same time to reach $1m, and only 10% more capital to reach $10m.

  This gap may well narrow over time, nudging VCs to finally abandon their penchant to bankroll “B2B SaaS with the homies”-type endeavors and return to their true calling: funding high risk technologies that matter.

  As Jamin Ball of Altimeter says, with today’s VC fund sizes, the 2% mgmt fees charged by VCs to LPs becomes a very meaningful part of the “get rich” equation. This results in VCs raising as much as possible, investing as quickly as possible, only to raise an even larger fund. The job of a VC investor has almost completely changed since its ‘inception’ - “if the job is to find the next investment to deploy the next dollar, it gets hard to actually slow down” …and make meaningful investments that actually matter.
  As a founder, ask yourself if you’re working with a 2% mgmt fee venture firm or a 20% carry venture firm.

• Brian Chesky, Airbnb’s founder, on Lenny’s Podcast: A year before Paul Graham made “founder mode” the topic of the town in his Sept. blog post, Brian Chesky was explaining how he was taking back greater control and creating more accountability at Airbnb. He explains that VCs keep telling him and other product-led founders to step away and delegate product responsibilities. “But this leads to delegating away what we’re best at”. Some more memorable quotes:
  “I think the CEO should be the CPO of product or tech company”
  “Leaders are in the details - this is not micromanagement, there is a difference between telling people what to do and being in the details”
  “There should be no people managers in the entire company”
  He explains how he first restructured the product mgmt. department through:

  • combining traditional product mgmt. tasks (understanding customer needs, collaborating with engg. & design teams, prioritizing features) with traditional product marketing tasks (creating messaging, GTM strategies, engaging sales teams to drive adoption, developing campaigns)

  • making product mgmt. department significantly smaller and more senior

  • delegating away program mgmt. tasks to actual program mgmt.

  This ensures more purposeful products being built, no misalignment between product and customers, and most importantly more accountability from PMs.

  Secondly, he explained how he made sure that every exec was an expert in their domain (i.e. no people managers)
  Finally, he stopped pushing decision-making down and reigned it back in to the top 30-40 people in the company.

• The Generalist wrote about Hummingbird: Hummingbird is an oddly successful European seed-fund. They delivered >10x returns on 3 funds without investing in any of the overpriced mainstream companies. This is their reported philosophy:

  • Amazing companies have 2-3 near death moments - this is the moment to double down

  • Invest in the most exceptional people on earth; “not the top 1%, but the 0.1% with unreasonable ambitions, astonishing clock speed and frightening hunger creating a deep personal unease”

  Hummingbird invested in companies like Kraken, Peak Games, & Gram Games.

  • E.g., when Peak Games was sold to Zynga for $1.8b, they made $276m from a $5m investment. This alone returned ~9x of the fund.

  They have a team of 10 investors which can invest in all regions and topics - “If an associate wants to map out the Thai ecosystem or obsess over the NFT market, they can do so”.

  The investor’s goal is to speak to 20-30 companies per week.

  The firm’s goals is to 10x, which:

  • caps AUM at ~$250m - “its just hard to return anything above that”

  • excludes very diversified portfolios

  • excludes complex & lengthy decision-making processes

  • excludes playing in saturated markets without a lot of alpha / arbitrage

• Andreesen Horowitz says GenAI will disrupt how video games are made:

  Before 2010 most video game developers created their own engines, nowadays games are built using all-purpose 3rd party engines (except the largest ones which develop their own engines e.g., EA).

  a16z says the dominant game engines are optimised for legacy on-premise compute architecture - “given cloud computing, GenAI and new spatial platforms, 3D creation is poised for end-to-end disruption”.

  • New entrants won’t compete with incumbents on every use case, they will focus on a vertical (i.e. specific genres & styles e.g. FPS, MMORPG, world building etc.)

  • They will not charge a SaaS fee; rather a 2-5% revenue share will likely be the norm

• The Economist compared GenAI adoption to tractor adoption in 20th century: Tractors didn’t immediately improve productivity and weren’t immediately adopted. “The productivity growth from tractors in the 20th century probably never exceed 3%” - implying the effect is felt over decades. Tractors weren’t immediately adopted due to price, perceived utility and labour markets not changing as quickly as people projected.
  Similary, GenAI models require too much compute for simple tasks and companies haven’t embraced the complete reorganisation required. For instance, in a Dec’24 interview, the CEO of DataBricks mentioned that “data mgmt” and “data strategy” - fundamental prerequisites for training proprietary models - are not even on the agenda for the vast majority of Fortune 500 CEOs.
  It does however seem to me that literally every company is wide awake for this GenAI wave, far more so than with previous waves like the internet, mobile, or cloud - suggesting that while awareness is high, the knowledge around proper execution may still be lacking.

• An SF VC, Nikhil Trivedi, asked tech leaders for their 2024 predictions:

  • Jamin Ball (Altimeter) - faster app development cycles. GenAI will answer key questions around security, cost, compliance during prototyping while also converting prototypes, internal tools into fully developed, customer-facing solutions

  • Jake Saper (Emergence) - consulting will be productised. Mgmt. consultancies like MBB, Accenture will face pressure to productise as start-ups like Mechanical Orchard, which offer better, faster, cheaper digital transformation strategies & tools, eat into their margins. It raised $50m in series B from Google Ventures

  • Rick Zullo (Equal) - While overhyped AI companies chase ultimately unrealistic valuations, there will always be a handful of start-ups which are simply good businesses with PMF, solid unit economics, and decent growth. These companies will not impress multi-billion AUM VCs just looking to deploy their dry powder (think Adam Neumann’s Flow), many of whom will have depleted their capital overspending on the AI frenzy. This leaves an ideal environment for outsiders i.e. traditional PE funds, who now have the opportunity to acquire high-growth businesses at reasonable multiples.

  • Mike Dubeo (Greylock) - largest retailers won’t dominate ad space anymore (Walmart, Amazon, Instacart). Small retailers will emerge due to:

    • Apple’s privacy changes make it difficult to make use of 3rd party data (cookies, app tracking), so advertisers will need to rely more on 1st party data (owned by retailers) to target customers effectively

    • New tools that lower the cost of creating in-house ad networks

    • Increased pressure to monetize - ad space is lucrative

January 2024:

• Howard Marks’ memo Easy Money: As Warren Buffet said, “When I see memos from Howard Marks in my mail, they're the first thing I open and read.” So let’s start with this memo outlining why the 2023 boom was almost entirely fueled by easy money encouraged by a willingness to take very risky decisions. He says, this not because investors want to be further out on the risk curve, but because the low interest rate environment made them believe it’s the only way to achieve greater returns. The Zero-Interest-Rate-Policy (ZIRP) had a massive but underrated influence - 1) running a business became easy since the economy was growing, 2) investors saw growing asset valuations (see my post on how software company valuations grew over the ZIRP period) 3) easy for investors to take on leverage, 4) easy for businesses to get financing, 5) easy to avoid credit default & bankruptcy. I.e., 2023 was nothing more than an apparently inevitable decade-long ZIRP-fueled joyride - easy times fueled by easy money.

• Chairman of Hg Capital talks about their buy & build of Visma: Feel free to also check out my post featuring a detailed case study on this deal. Context: Hg acquired 50% of Visma in 2006 at a $450m valuation, the company is currently worth $21b, revenue at $2.5b, EBITDA at $800m, with 15k employees. Visma develops accounting, payroll, and compliance software making it highly countercyclical. But more interestingly, its their hyperlocal approach which make them sticky; they build a brand within a particular geography making it the go-to product for businesses who don’t want to take a risk when it comes to compliance, accounting and payroll topics.
  Furthermore, their dominance in the Nordics - where digital adoption is not feared, unlike in other European countries - gives them the advantage of “seeing trends 5 years into the future”. This allows them to make better bets - Visma currently does 30-40 small acquisitions per year.

  To maintain the high levels of organic growth, they also don’t integrate the add-ons (beyond streamlining financial reporting, cash flow mgmt, cybersecurity etc.). Product and GTM are driven entirely separate by founders who have rollover equity. “This is the number one thing as we scale”.

• PwC did a CEO survey on GenAI: Key insight - ~47% of CEOs say GenAI adoption will deliver little to no changes. ~46% of CEOs say GenAI adoption will increase profitability in NTM. ~31% of CEOs say their companies adopted GenAI in 2023.

• Podcast with Bill Gurley (Managing Partner, Benchmark): Key insight - “1.5k start-ups died in 2023, which is the largest death toll since the dot-com crash. A further 1.2k start-ups are expected to die in 2024”. “ZIRP funded start-ups finally started to die”.
  As Howard Marks mentioned earlier; venture investors are especially cyclical - trying to ride any wave going upward and hitting the breaks overnight, much like a gambler following the table’s hottest streak with no conviction for their own hand. This effect however isn’t immediately reflected in the markets because a lot of start-ups accumulated a lot of cash. This explains why the “start-up death-toll” has peaked in 2023 & 2024. 2021 was the year scale-ups accumulated enough cash for a 2-3 year runway, in Mar. 2022 ZIRP officially ended, creating the series of bankrupt start-ups we see in 2021+2/3 years.
  This also explains why everyone says the IPO window is closed; surviving founders are having a tough time accepting their current valuations. But more importantly, Bill says there is a new breed of investors investing in (overpriced?) $1b+ companies who won’t let them go public (think Tiger, Coatue, Softbank, Altimeter), who justifiably want their capital to be put to work before the exit.

  ”AI is the exception, they’re acting like its 2021”

  “Now is a great time to start a company - less competition & more talent”

• Podcast with Keith Rabois on his Founders Fund to Khosla Ventures move: Key insight - FF is hands off and KV is hands-on. FF picks exceptional founders and let’s them do their thing, apparently every step of the way. And KV has plenty of operational support, VC+founder decision-making etc. Since they are both great funds, he explains pro’s and con’s for each, which don’t seem far-fetched so I won’t into detail.

• Podcast with Jamin Ball (Altimeter): This was interesting, Jamin talks about the problem that surviving founders, mentioned earlier, will have in 2024. He says, usually VCs invest at a 1-2 milestone cadence, every 2 years or so. But during ZIRP, every VC was risk-on and emptied their gunpowder, resulting in founders needing to deliver 5-10 milestones in shorter time-spans without follow-on investments. Unfortunately as a result, some likely good businesses are overpriced and under-performing, which means they need to develop a plan around shutting down, being bought, or god-forbid raise a down round.
  He also mentions there is a big bubble in seed stage because of increased competition from later stage VCs investing price-insensitively.

  He describes the M&A environment as a game of musical chairs due to the lack of acquirers in each vertical.

• Pitch, the ppt. competitor: Speaking of unrealistic expectations set on recently funded start-ups - Pitch raised $85m at Series B from Tiger and Lakestar. The investors made a noble move by reducing the ownership stakes of investors, even adjusting the liquidation preference. They used the funds to repurchase overpriced shares, reallocating them to the employee pool with the goal of motivating the team to achieve Rule of 40/50 status, focusing on profitability.

• Podcast with Jan Mohr who is building the Constellation Software of Europe:

  Jan’s fund buys and holds small vertical SaaS firms. He emphasizes the need for amazing managers to oversee the businesses due to the holding’s heterogeneity.
  He says Europe is full of tiny markets where having a 60% market share corresponds to 1m-3m€ business. Combining a dozen of these businesses into one holding will create a more valuable business. Also, country to country differences are big, one can’t simply take a dominant business from say Germany and expand to say France because of 1) local competitors and 2) localization needs.
  There is an urgency to roll-up vertical SaaS because many of the owners are looking to sell, he says this opportunity will be gone 3-5 years.

• Contrary predicted more secondary deals in 2024: Key insight - yoy growth of secondary funds is +200% vs -60% for VCs and -3% for PE funds. Start-ups need liquidation events. Currently ca. 50% of secondary deals are accounted for by Stripe, Bitedance, SpaceX, Databricks, Anduril (which explains why they don’t go public) but many other companies have liquidation needs to keep employees happy. Furthermore VCs are nearing the 8-10 year mark with little in DPI but thankfully plenty in projected IRR to keep the dream alive. Uff.

• New Consumer published their consumer trends report: Key insight - TikTok’s native shop will be big. Launched in Sept. 2023, TikTokers can post videos of products and earn commission. 65% of TikTok’s US active users say they are both aware and willing to buy something from the shop. Big overlap from those who already buy from Shein and Temu.
  What do people buy? Mainly Jeans, sweatshirts, skincare. Average order value has been $30 and consists of 1.3 items.
  Revenue in US in Oct ‘23: $250m

  Revenue in SEA in Oct ‘23: $1bn

• Louis Coppey (Point 9) wrote about vertical SaaS: Key insight - Traditionally, vertical SaaS’s problem was low TAM, which usually led to 3 initiatives:

  1. Expand scope to increase ARPA (more features)

  2. Expand target customer (different types of companies)

  3. Expand user type (different personas in same company)

  Now vertical software companies have more options within the 1st option above - provide automated workflows/RPAs to capture e.g. HR budget instead of software budget only, financial services, procurement services.

• Podcast with Founder of Procore: Procore provides software tools for the construction industry. Founded in 2002, it took 10 years to reach $5m ARR and another 3 to reach $10m ARR. He says he launched at a time when construction sites didn’t have internet - “we just were super early but I knew it was going to happen, we just had to be patient”. Investing into a company that early requires a lot of conviction, in fact, Bessemer an early investor wrote the best-case scenario for Procore is a sale for $300m. Devastating, I know.
  They started off with a project mgmt. tool, then added a financial services, quality mgmt. tools. He believes he was more successful than competitors because they delayed releases to ship enterprise-grade products. This decision is more difficult than it sounds because solutions must be entirely re-architectured to be able to scale with customers, adding cost and handing over market share to competitors.

• Podcast with Bill Gurley and Brad Gerstner (Benchmark, Altimeter): Key insight - 10% of all start-up funding in 2023 came from Microsoft, Amazon, Google and Nvidia. Its 30% for AI/data start-ups.
  Most of the investment is not cash, its data-center compute credits (OpenAI-Azure, Anthropic-AWS, Hugging Face-GCP), which is opening up new (unprofitable?) business practices. They spoke about 2 interesting practices 1) LLMs are selling their software at negative gross margin since they don’t see cloud credits as COGS, 2) they resell their software with compute credits - giving away capital because they become ignorant to the cost.

• Financial Times writes about VCs raising continuation funds: Continuation funds were initially a PE thing (largely still is) - its when you raise another fund to transfer your first fund’s portfolio to the new fund. This gives first fund investors the ability to cash-out, albeit at a discount and allows the VC to keep the investment longer. Explaining why its a controversial practice.
  Lightspeed is raising a continuation fund, Insight has always done it and NEA is trying to convince LPs to do the same.

February 2024:

• Klarna uses ChatGPT to replace its customer support: Key insight - Klarna apparently laid off somewhere between 500 - 2000 customer service employees. 2/3rds of customer service chats are now run by ChatGPT with a similar customer satisfaction score. It is 25% more effective and significantly faster (2min vs 11min) at errand solutions, leading to a drop in repeat enquiries. It is available 24/7, in 35 languages.

• YC listed key topis they would fund for next years:

  • AI + Robotics: rapid LLM improvements make it possible for robots to have human-level perception/judgement

  • ERP software: traditionally ERP is expensive, painful to implement and disliked by users. Start-ups could tackle this problem by building flexible, easy-to-use ERP software

  • AI + ERP software: automated customization of ERP software. This is what makes ERP software expensive. The core functionality remains the same across most/all customers, they want last-mile customization. Can a customer use a chatbot to write this last-mile customization?

• Bloomberry investigated GenAI impact by analysing jobs on Upwork: Key insight - graphic design, video, software development jobs went up significantly. This might be because GenAI tools are not fully “business ready” for video and graphic generation and perhaps also because people haven’t learnt to use them. Jobs which saw the biggest changes are:

  • writing (-35%)

  • translation (-20%)

  • customer service (-20%)

  • graphic design (+15%)

  • web design (+20%)

  • accounting (+20%)

  • video editing (+40%)

• Brighteye published its edtech funding report: Key insight - Total edtech funding halved in 2023. 2023 raised $5b across 915 deals, and 2022 saw $10b across 972 deals. There were only 3 exits over $500m in 2023. Kahoot! at $1.7b, Parchment and Dreambox at $800m.

• Economist wrote about social media companies becoming unsocial: Its writes about how Facebook was once a place to chat with your close friends, but given that the share of Americans who enjoy documenting their lives has fallen from 40% to 25% between 2020-2023, these platforms are turning into TV-like entertainment feeds for passive consumption. See the currently most popular app, TikTok, which pretty much only exists for this 15min loo-break use-case.

  It seems Instagram is still not going to be the place for authentic day-to-day non-avo-toast, non-24/7-in-bali-baby content, leaving people to also gravitate toward snap, bereal, lapse and apparently even massive telegram groups.

• Podcast with Dave Kellog on company growth: Dave was CMO of BusinessObjects, where he oversaw revenue growth from $30m to $1b, employee count from 240 to 4,500. He also ran 2 other companies from $0 to $80m and $10m to $50m. He says growth is about doing more of whats working best and ignoring everything else - where is the highest win-rate? fastest sales cycle? highest ACV? highest NDR?
  His rules of thumb:

  • Use CAC to determine how much to spend, 1.5x for Enterprise and 1.0x for SMB

  • 105%-108% NDR in 2024, vs 120% in 2021, due to increased churn and tighter customer budgets

  He also says CEOs should give up their religious focus on outbound and instead do more inbound sales (events, content etc.), since inbound leads convert 2-3x more.

• Pennylane raises €40m series C from Sequoia & DST and becomes a unicorn: Pennylane provides accounting software for SMEs, currently used by 120k SMEs and 2k accountants. It also provides electronic invoicing, cash-flow mgmt. and banking functionality, which is key to their success - SMEs want all-in-one solutions.

• Iconiq wrote about SaaS and IPOs: It says equity multiples correlate strongly with interest rates, explaining why public stocks have seen a decline in value with growing interest rates. High-growth companies (+30% yoy) have seen the biggest drop in value. This has to do with good companies being more likely to start off overvalued and then settling onto more realistic multiples now that money isn’t so cheap.

  The five metrics most highly correlated with value:

  • year over year growth

  • gross margin

  • free cash flow margin

  • rule of 40

  • net dollar retention

• Sam Lessin, a VC, wrote about 2 types of VC firms: He explains why some funds opt for a larger size, while others prefer to stay small. On one side, you have "fee optimizers"—funds focused on growing AUM, which generates more fees. For them, returns only matter as far as they attract more capital. Interestingly, LPs also view them as fee-generating machines, with little incentive to truly outperform for LPs or entrepreneurs beyond clearing a basic hurdle.
  On the other side, there are the "return optimizers." These funds stay small, as it's easier to generate high multiples on smaller sums. They forgo hefty fees and public market attention, instead making money only when their investments succeed, aligning their outcomes closely with those of the entrepreneurs they back.

• Economist wrote about Costco: Costco is the 3rd largest retailer in the world, behind Walmart and Amazon.
  Costco generates >50% of its profits through its $60/year membership fees - in 2023 fees from its 129m members generated $4.6b. Renewal rates are >90%.

  This has a flywheel affect, fees lead to greater buying power/economies of scale, passing down savings to customers, hopefully bringing in more people.

  This loyal customer base drives consistent, sticky revenue, creating the ideal setup for their private label brand - which accounts for 25% of revenue, well above average for a retailer.

• Podcast with Parker Conrad, founder of Rippling: Parker shared a view contrasting with many VCs' preference for vertical SaaS. He argued that building single-point SaaS solutions is increasingly challenging, as many companies now focus on offering a suite of products. E.g. Procore and Pennylane from above, as well as SAP, Oracle, Salesforce, and Microsoft, show the benefit of adopting a best-of-suite strategy. Parker says, especially in today’s environment, suite solutions are the leading strategy because they:

  • streamline product functionality

  • bundle pricing

  • unify user experience

• Reddit published its S1 to go public: Reddit is one of the 10 most visited websites of 2023, it has 75m DAUs, 250m WAUs and 500m MAUs. It generated $800m in revenue in 2023, up from $660m in 2022 (+20% yoy). It is currently -$70m EBITDA, vs -$110m in 2022.

  Reddit outlines that it has the potential to be a commercial ecosystem, e.g. in "r/photoshoprequest” users can request photoshop services for payment.
  Moreover they mention its content’s licensing potential in the AI era. It totalled $200m in contract value to let 3rd parties train their AI algorithms on its data, $65m of which will be recognized in 2024.

• The Time interviews Mr Beast: Aka Jimmy Donaldson, is probably the most watched person on earth. His channel added +100m subscribers in 2023, 2x the growth any other channel.
  His reach is incredible, an average video generates around 50m views within 24hrs - thats >2x the audience size of Barbie and Oppenheimer during opening weekend.
  He says “it was just sad” that he advertised other companies, instead of his own, when he knows his videos get >200m views. Which is exactly why he started a line of snacks with $500m revenue, a food delivery service with >$100m revenue in 2022, a toy company and has a 9-figure deal with Amazon.
  

March 2024:

• Podcast with Jason Lemkin on building a sales team: Jason founded the largest event for B2B SaaS founders, SaaStr. He provides a clear plan:

  • the founder should get the first 10 customers, regardless of how good/bad they are in sales

  • then hire 2 sales reps (so they compete with eachother) - interview 30 people regardless of background. Try to identify whether they just prepared for the sales interviews or whether they are great at selling your product. These sales people should have a few years in B2B sales, since you cannot spend time babysitting

  • after both reps hit their quotas, hire a manager for them; a VP of Sales. These people rarely want to do sales, they want to take you from sales rep #3 to #300, which is great but they must sell as well. You want them to be in deals 20-30hrs/week.

  • interview-guide for VP of sales: ask them what they want to do during the first 30 days. If they don’t want to start by talking to the customers, its a massive red-flag. In the early days they shouldn’t spend time on processes and territory planning. It's advisable to select a candidate who represents a stretch, someone who was previously a director and will receive a promotion within your organization

  • interview-guide sales rep: ask them to sell your product. it shows if they spent 20min researching or 2hrs researching

  • compensation & quote set-up: in the first 3-months, sales reps should get 100% of what they close. This is not sustainable obviously but kickstarts growth. Sales reps should bring in 3-5x their salary, higher for enterprise sales. You want sales people who love money, and you want them to earn a lot.

  • how to scale: as the sales team grows, there should be 1 manager per 8 sales reps/AEs (sales reps are openers and AE are closers) and 1 VP per 8 managers. After you hired your 2 sales reps and 1 VP of sales, the VP should hire 2 managers and 6 sales rep/AEs.

• Elad Gil gave his take on AI models: Elad was successful at Google, later sold his company to Twitter, he’s currently a VC.
  He expects LLMs to be an oligopoly; with closed-source leaders being - OpenAI, Google, Anthropic and open-source leaders being Grok/X.ai, Llama (Meta) and Mistral.

• Bain’s PE report: Key insight - Total deal count is down by 35%, deal value is down by 60%, exit value is down 66%, and number of funds closing has declined by 55%.
  All while, 25% of global dry-powder being 4 years or older - meaning general partners are under pressure to do deals.
  2023 was worse than expected, and LPs aren’t happy either. Significantly lower DPIs mean LPs don’t reinvest back in the PE funds, creating this downward spiral. Moreover, higher interest rates, mean PE funds can’t advantage of leverage, which is seen by deals >$5b dropping by 50% this year, and even a lower average deal size from $1b to $750m.

• Stripes published its 2023 annual report: Key insight - Stripe processed $1t in 2023, +25% yoy, representing 1% of global GDP. They have >100 customers processing >$1b with Stripe.
  Stripe is “obsessed over eliminating barriers to internet purchases”.
  They also mention that the average of a company’s tenure in the S&P 500 is declining significantly; it was 61 years in 1960 and 18 years in 2024. This means CEO’s greatest priority should be their ability to reinvent themselves.

• Podcast with Gili Raanan: Gili worked at Sequoia for 15 years before starting his cybersecurity focussed VC in Israel. He mentions in the early days he was looking at markets, TAM, tech, moat and realized “its all bullshit - everything will change except the team”.
  He says he doesn’t even ask founders about market, tech or product. “We spend an hour talking about their childhood, their mother. Thats enough to pick amazing teams. This understanding helps me predict their behavior going forward”.
  He tries to understand why they do what they do and early signs of excellence. “I’m looking for the individual who was socially isolated as a child, I’m looking for people who went through real difficulty in life and became successful”.
  Gili created a step-by-step approach to building cybersecurity companies - after finding the founders, he asks them to sit with CISOs of fortune 500 companies over a 3 month period and identify pain points. They specifically ask “which problems would they prioritze if they had $100m for engineering investments over the next 3 years”. After this phase, they pitch their ideas to the same CISOs over the next 3 months asking if they would be first customers. Following this, this they develop a commericial PoC in the next 3 months.
  This process allows companies to scale faster because you ask all the tough questions at the beginning, instead at the end after you created a product and sit with many of CISOs. “why buy us instead of a competitor product from PAN? how would you price us? how would you distribute this?”
  21 companies went through this VC, 7 became unicorns and 1 is Wiz, which Google wanted to buy for $23b.
  He speaks at length how Sequoia managed stay the best VC for so long. Key insight was: he says they have strangely endless hunger; “you could invest in Google and the next moment they would ask how can you improve? They are just never happy”.

• Chris Dixon, a16z partner, writes about early career choices: He writes ambitious people often fall into the trap of prioritizing short-term progress over long-term goals. This tendency, highlighted by behavioral economists, stems from a natural inclination to take the next upward step, even if it leads them further away from their ultimate aspirations. For ambitious individuals, this pull can be particularly strong, making it harder to resist immediate rewards in favor of patiently working toward broader ambitions.

  Early in their careers, people should embrace a more exploratory approach, inspired by the hill climbing computer science problem. Instead of climbing the nearest hill for quick gains, they should take time to meander, explore new areas, and experiment with different paths. Once they identify the "highest hill"—the area with the most potential for long-term fulfillment—they should commit fully, even if the immediate steps up the current hill seem tempting.
  This explains why so many ambitious people end up in finance, consulting and law.

• Mark Mullen shares how a $100m seed fund would work:

  • $100m seed fund means $75m investible capital (net of fees)

  • 55% of $75m is allocated to 27 initial seed checks (avg $1.5m size, 11% ownership)

  • 45% of $75m allocated to follow-on checks in Series A and B (assume 2/3 or 18 go from seed to series A, $1.5m avg check size; assume 5 go from Series A to B, $1m avg check size)

• Thoma Bravo outlined their plan to take-private software companies: Their rationale; since 2008 market cap of public software firms increased 10x ($1t to $10t) but EBITDA increased insignificantly (-3% to -2.5%). This is an opportunity to take them private, implement operational efficiency initiatives and take them public again.
  They argue software is still a great business model:

  • software company revenues are +16% vs +5% for the avg S&P 500 company

  • software company gross margins are 70% vs 45% for the avg S&P 500 company

  • software company EBITDA margins are strangely -2.5% vs 26% for the avg S&P 500 company

  This means they have higher growth rates, higher gross margins, and more opportunity for operational improvements. (SaaS expected to grow 20% yoy, and IT spend expected to grow 10% as well)
  They calculated the estimated equity required to purchase a median software company:

  • $750m LTM revenue

  • +15% revenue growth yoy

  • 70% gross margin

  • -2.5% EBITDA margin

  • 5.5x EV/LTM revenue multiple

  • 25% assumed premium means, purchase multiple = 5.5 + (5.5 * 0.25) = 7x

  • Purchase price: $5b

  • Assuming 75% equity check size: $4b needed

April 2024:

• Podcast with CFO of Booking.com speaking on stock based comp: Stock options became mainstream during the 90s, but were criticized after the dotcom bust. Employees at larger companies also criticised their significant dilution.
  This led to the intrduction of RSUs which not only lowered dilution from -3%/year to -1%/year, but also inherently had value. Stock options only have value when the stock goes up (since they are priced at the current market value). RSUs feel like a cash bonus after a vesting period.

  RSU do however cause misalignment between mgmt. and shareholders. E.g., if mgmt. leads the company to a stock price decline, they may still get 80% of their equity award/RSUs. I.e., mgmt. despite shareholders losing.
  He proposes that RSUs be added to the P&L as a cash expense, which should lower the companies EBITDA, similar to a salary bonus payment. This may lead to more aligned company mgmt.

• Iconiq lists key metrics they look for to lead a Series B:

  • >100% ARR growth

    • They say its difficult for <$10m ARR SaaS company to raise VC funding if they don’t double yoy

    • Median yoy growth for <$25m companies is 125%, top quartile is 240%

    • Median yoy growth for 5m<x<10m companies is 165%

    • Investors don’t need a full 2 year history, e.g., they say 8 months of 15% growth is very interesting, but 3 months of 7% growth isn’t enough.

  • >100% net dollar retention

    • Median NRR for <$25m companies is 105%, top quartile is 125%

    • This metric will likely stay over the company’s life, so pay attention here

  • >70% gross margin

  • efficient GTM

    • One way to measure this is via the magic number (current Q’s net new ARR / previous Q’s S&M opex). This will measure how efficient how revenue generation is accounting for sales cycle lag of 1 quarter

    • Median magic number for <$25m companies is 0.8, top quartile is 1.7

• Economist wrote about climate change’s affect on residential properties: They estimate that 10% of the worlds residential properties are at risk to climate change induced affects and further conclude that these affects lead to a 9% value decline by 2050, which amounts to $25t.
  Climate change will lead to increasing home insurance costs and ultimately governments needing to step in to underwrite risks.

• Podcast with Bill Gurley (Benchmark) on IPOing: He talks about how founders expect to stay private for a much longer time. For instance:
  There were 7k public companies in 1996, 4k in 2024.
  There were 2k PE-backed companies in 1996, 11k in 2024.
  Philipp Laffont (Coatue) says that in the past, you could go public with $500m market cap and $50m revenue, now people feel the need to be $10b market cap and $1b revenue (e.g., Stripe).
  Interestingly another VC, Gokul Rajaram, has another take - he says companies <$700m ARR underperform after going public, making it hard to retain employees and investor interest. If you not growing >50% yoy then you should expect a struggle and PE acquisition is an inevitability. “As we’re seeing daily today”.

  Jamie Dimon in his annual letter to JP Morgan shareholders also touched on this - he says we are making going public unattractive through intensified reporting requirements (ESG etc.), higher legal fees, board governance, less compensation flexibility and high pressure to deliver quarterly earnings.

May/June 2024:

• SAP announced to aquire WalkMe: WalkMe helps users when using app through context windows, guidance and support. It recently introduced WalkMeX which is essentially like Microsoft’s copilot, and can suggest next steps for any workflow. It will be integrated into SAP’s copilot, Joule.

  SAP will acquire it for $1.5b and its SAP’s 3rd >$1b acquisition in the last 4 years.

• Perplexity fundraising: Bessemer rumored to lead $250m round at $3b valuation. Perplexity is a wrapper around many of the best models; OpenAI GPT-4, Anthropic Claude Opus, Mistral, and more. Given that they did $20m ARR since the start of the year, they are proving the commercial viability of this approach.

• Creandum fundraising: It raised a €500m seed/series A fund to invest in Europe. Creandum’s success stems from betting early in emerging European tech-hubs - Spain, eastern European countries. And they have a good track record with 1/6 of its 200 investments becoming unicorns.

• Bain takes PowerSkool private: Yet another example of PE funds buying public software companies. The deal is valued at $5.6 billion, with Bain paying a 37% premium—on the higher side—and valuing the company at a 7.8x EV/ARR multiple, which is comparatively moderate.
  Bain’s value creation strategy focuses on expanding internationally beyond North America while enhancing the platform with AI capabilities.

• Mark Leonard (Constellation) speaks about vertical SaaS: He says that about 8 years ago, Silicon Valley poured billions into vertical SaaS, but much of that money was wasted. The few companies that succeeded did so by using lowering prices to attract price-sensitive clients with low switching costs. However, the challenge comes when your competitors start undercutting you, so it’s crucial to build a moat to retain those clients. Here’s how:

  A great example is Veeva, which entered pharma with a low-cost CRM built on Salesforce. They later reduced costs by building their own platform and expanded their moat by adding more applications for the same clients. This strategy—penetrate the market, reduce costs, and expand offerings—is the blueprint for a successful vertical SaaS, though such successes are rare.

• Mistral fundraising: General Catalyst and DST led a €600m round at a €5.8bn valuation. Mistral provides an open-source model catering to large enterprises which want to preserve their data privacy or customize their own models for their business.

July 2024:

• Goldman Sachs wrote about GenAI capex: For AI investments to pay off, the technology must solve complex real-world problems, which it currently isn’t built to do. Only 25% of AI-exposed tasks are expected to be cost-effective to automate within the next decade, impacting less than 5% of all tasks.

  Affect of AI in the short term will focus on mental tasks rather than physical ones, these are limited in scope. For example, ServiceNow has reported an 80% reduction in customer service resolution times using AI, demonstrating potential but far from universal transformation.

• Coatue wrote about the state of public markets: Key insight - software company multiples are at 5x EV/NTM because sales have slowed and because the market favoured infrastructure companies at the early days of the AI revolution. They are near all-time lows, with a median multiple of 7.5x over the last 10 years.
  This is justified by lower growth expectations for software companies.
  AI accounted for 2/3 of the S&P 500 gains, with 1/3 coming from Nvidia.
  AI threats and implications for software:

  • AI will shrink labor force and pressure seat-based SaaS pricing

  • AI will likely kill seat-based model and force founders to price based on value

  Here’s a quick overview of different types of monetization models:

  • On-prem:

    • pricing model: license

    • Avg ARPU/month: $30

  • SaaS:

    • pricing model: seat-based

    • Avg ARPU/month: $50

  • AIaaS co-pilot (new):

    • pricing model: usage-based/AI credits?

    • Avg ARPU/month: $100? (2% of avg employees salary)

  • AIaaS auto-pilot (new)

    • pricing model: value based/ROI?

    • Avg ARPU/month: $3k? (50% of avg employee salary)

  Where are AI VC dollars going?

  • 60%/$14b on Models

  • 20%/$4b on Apps

  • 10%/$2b on AI Ops/Cloud

  • 10%/$2b on Robotics

  Given the backlog of 1400 private unicorns, Coatue wrote why no IPOs:

  • More passive/ETF investing, favouring large companies

    • $10b became new market cap threshold, vs $1b earlier

  • Private valuations higher than in public markets

    • Covid drove peak valuation; avg company is down 50% since their peak

    • liquidity at premium

• Google offered to buy Wiz for $23b, Wiz rejected: Wiz is a cybersecurity start-up, founded 2020. It reached $350m ARR in 2023, planning to reach $1b by 2025, being one of the fastest growing tech companies.

  What does it do? They scan for security risks from leading cloud providers, betting that customers want more protection than offered from AWS, Azure, GCP etc.
  This would have been Google’s largest acquisition by far, and also would’ve been strategically smart to strengthen their multi-cloud, and cybersecurity offerings.

  Wiz raised $1b at a $12b valuation in 2024, with the following cap table:

  • 9% each for 4 co-founders

  • 11% for Index

  • 10% for Sequoia

  • 9% for Insight

  • 5% for Greenoaks

  • 4% for Cyberstart (Wiz went through Cyberstarts’ accelerator)

• Sequoia let its LPs buy $1b worth of Stripe shares at $70b valuation: In 2021 Stripe was valued at $95b, then $65b in 2024.
  This valuation is arguably still high because its competitor, Adyen, processes a similar payment volume, raised $300m and is valued at $30b with a 50% EBITDA margin. Whereas raised $10b, is valued at $70b and barely profitable.
  Sequoia invested ca $500m and its position is worth ca $10b.

August 2024:

• Procore published Q2 report & explained how it wants to scale from $1b to $10b:

  Procore’s international revenues increased 31% vs a 24% in local growth. This convinced Procore’s leadership to switch their global matrix mgmt structure to a local-focused “General Manager” structure. Each general manager will focus on either NA, Europe, Australia, NZ and ME, which will allow them to tailor strategies to the specific countries.
  Furthermore, Procore is introducing Procore Pay which adds financial workflows within construction projects creating a cross-sell opportunity and a longer term platform strategy to add more capabilities.

• The Dispatch argues USA should increase military spending to counter threats: Increasing spending will counter threats from China and maintain its military superiority.
  It says since 1980s defense spending has halved from 6% of GDP to 3% (an interesting way to say it’s been cut in half, if you ask me).
  The US navy is has halved from 600 ships to 280 ships, while China is set to reach 450 ships soon (what of the other military machinery?)

  Eitherway, they do raise good points that it would be good for the US to finally pass an audit (they failed last 7 audits), become cost-efficient and drop all politically congressional mandates.

• Tidemark published vertical SaaS benchmark report: Key insight - multi-product companies have better metrics across key categories:
  (single-product vs. multi-product)

  • median avg revenue per account: $90k vs $225k

  • median annual recurring revenue: 36% vs 47%

  • median gross retention: 88% vs 90%

  • median net revenue retention: 108% vs 111%

  Which products have highest avg revenue per account:

  • Time tracking: $3.5k

  • Inventory mgmt: $2.8k

  • Demand gen: $2.5k

  • Accounting: $1.6k

  • Marketing automation: $1.2k

September 2024:

• Marie Brayer wrote about LLM adoption in enterprises: She writes there are main use-cases:

  • Turning human language into tasks (e.g., better customer support)

  • Helping users process information overload

  • Accelerating content creation

  Currently she doesn’t seem too optimistic about the cost-benefits since they are too expensive ($10 per inference request) and not accurate enough, which don’t make them very practical.
  The greatest advantages currently lie in high-tech industries which use a combination of RPA and LLMs (companies like UiPath and ServiceNow). Their goal is to continue to automate complex tasks, but instead of using traditional programming one can now use human language instead. This shift significantly reduces costs, as it eliminates the need for developers.
  Interestly, this is accelerating adoption of open-source LLMs which are cheaper since one wouldn’t need to scale expensive LLM pipelines.
  For instance, Accenture is using Meta’s Llama model to develop a LLM for ESG which is supposed to have improved productivity by 70% and quality by 30%. Moreover, Shopify and DoorDash are using Llama to automate daily tasks for developers. Llama currently has +350m downloads on Hugging Face (20m last month alone).

• Dan Shipper wrote about OpenAI’s Strawberry model which can ‘reason’: Strawberry was initially developed to create training data for OpenAI’s latest Orion model. Strawberry can generate a training set of questions, and step-by-step instructions to solve the questions. The idea was to build a model that can hallucinate less.
  Models are usually trained via “outcome supervision” meaning they’re only rewarded if they get the answer right. Strawberry is trained via “process supervision” meaning they’re rewarded for correctly moving through each reasoning step that will lead it to the answer.

October 2024:

• Index wrote about early hires: They gave relatively clear advice -

  • of the first 10 hires: 5 tech, 2.5 GTM and 2.5 G&A/ops (one of which is senior - C-level or VP)

  • 50% of founders time should be spent hiring/onboarding

  • 50% of hires should have worked for VC-backed start-up

  • founders should hire mainly from their network - friends of friends, cold calling, inbound (bring in recruiter only at series A)

  • start-ups fail are hiring because they value experience > intelligence

  • maintain a high-bar early on

  Keith Rabois of Founder Fund/Khosla Ventures also wrote about this so I’ll to it here as well. He spoke about how Peter Thiel told him not to hire anyone over 30 because there are enough data points on their CV for the market to have evaluated them correctly - as a start up you cannot provide a high enough salary to outspend large enterprises who have infinite money.

• Rich Barton explains how he founded Expedia, Glassdoor and Zillow: He says he creates “data loops”, which collect submitted data from users (reviews, salaries) shows them to all users which invites more people to submit data. He says he built a business on not hoarding valuable information that travel agents, brokers, etc. keep a secret.

• Revolut’s CEO wrote about creating high-performance teams: He says you usually know within the first 1-2 months if someone will work out.

  He says performance is a CEO priority and shouldn’t be given to HR - he recommends setting up a performance mgmt team, which reports to the CEO. They measure the performance of employee along 3 dimensions

  • deliverables: ability to execute tasks considering speed, quality and complexity

  • skills: technical skills

  • culture: alignment with company values

  He says the top 20% should be promoted quickly and compensated exponentially.

  Bottom 10% should be exited.
  Remaining should be pushed to become the top 20%.

November 2024:

• Financial Times wrote about Thrive Capital: The firm’s approach is to invest in the best, often “over-priced”, start-ups and hope they can 10x-100x. This approach is working very well. Here’s a few examples - Instagram in 2011, Github in 2015, Slack in 2016. They recently invested $1b in OpenAI.
  This approach isn’t new, a16z made “overpaying” for great companies famous. But Thrive doesn’t want to be a conglomerate, they still want to be boutique.
  Thrive built these stakes through buying employee shares in the secondary market and staying very close to founders (i.e. paying any price at the next round). Most VC’s invest in 30 or so start-ups per fund, Thrive invests in ca 10 per fund.

• Visma is considering going public: As mentioned earlier, Hg took Visma private for $500m in 2006, its currently worth $19b and they own ca 70%.

• Databricks raised $10b at a $62b valuation from guess who, Thrive, a16z

Sources:

alexandre.sub stack.com

nextbigteng.sub stack.com

Lakestar's deeptech report - https://dealroom.co/uploaded/2023/09/The-European-Deep-Tech-Report-2023.pdf?x19094

The Generalist wrote about Hummingbird - https://thegeneralist .substack .com/p/hummingbird

a16z wrote about GenAI and videogames - https://a16z.com/unbundling-the-game-engine/

Economist wrote about tractors - https://www.economist.com/christmas-specials/2023/12/20/a-short-history-of-tractors-in-english

Nikhil Trivedi asks leaders about 2024 predictions - https://nbt.substack.com/p/nextbigthing2024

Howard Marks memo Easy Money - https://www.oaktreecapital.com/insights/memo/easy-money

Podcast on Hg and Visma - https://podcasts.apple.com/gb/podcast/visma-mission-critical-european-software/id1559120677?i=1000641947024

PwC CEO GenAI survey - https://www.pwc.com/us/en/library/ceo-survey.html

Podcast with Bill Gurley - https://www.youtube .com/watch?v=5ynVF2eRwZI&t=1339s

Podcast with Keith Rabois - https://www.youtube.com/watch?v=xutt6upP9gE&ab_channel=20VCwithHarryStebbings

Podcast with Jamin Ball - https://www.youtube.com/watch?v=kQ-u8nwnq8g

Pitch - https://x.com/christianreber/status/1744292271858622518

Podcast with Jan Mohr - https://open.spo tify.com/episode/56IxVRJTTfXzCwWkCbOVqF

Contrary Research - https://x.com/Contrary_Res/status/1747688397429154158

New consumer report - https://newconsumer.com/wp-content/uploads/2023/12/Consumer-Trends-2024.pdf

Louis Coppey Point 9 vertical SaaS report - https://medium.com/point-nine-news/vertical-software-2-0-e1e0b9810944

Podcast with Procore founder - https://www.youtube.com/watch?v=zi3gTfKkpUc&ab_channel=20VCwithHarryStebbings

Podcast with Bill Gurley and Brad Gerstner - https://www.youtube.com/watch?v=Wu_LF-VoB94&ab_channel=Bg2Pod

Financial Times writes about VCs raising continuation funds - https://www.ft.com/content/18430e05-33c0-4f48-8c87-fae74ff29bbf?

Klarna uses ChatGPT - https://openai.com/index/klarna/

Brighteyes edtech report - https://www.brighteyevc.com/post/the-european-edtech-funding-report-2024

Economist writes about social networks - https://www.economist.com/leaders/2024/02/01/the-end-of-the-social-network

Podcast with Dave Kellogg - https://www.youtube.com/watch?v=exMSjv1bGEU&ab_channel=20VCwithHarryStebbings

Pennylane funding - https://techcrunch.com/2024/02/07/accounting-software-startup-pennylane-becomes-frances-latest-unicorn/

Iconiq saas metrics - https://www.datocms-assets.com/65181/1707778558-iconiq-analytics-insights-decoding-the-saas-ipo-landscape.pdf

YC priorities - https://www.ycombinator.com/rfs

Sam Lessin writes about VC firms - https://x.com/lessin/status/1757126340069958050

Economist writes about CostCo - https://www.economist.com/business/2024/02/15/why-costco-is-so-loved

Podcast with Parker Conrad - https://podcasts.apple.com/us/podcast/parker-conrad-building-a-compound-company/id1154105909?i=1000586238255

Bloomberry wrote about GenAI taking upwork jobs - https://bloomberry.com/i-analyzed-5m-freelancing-jobs-to-see-what-jobs-are-being-replaced-by-ai/

Reddit published S1 - https://www.sec.gov/Archives/edgar/data/1713445/000162828024006294/reddits-1q423.htm

Time's profile on Mr Beast - https://time.com/collection/time100-leadership-series/6693255/mrbeast-interview

Elad Gil talk about what he doesnt know about AI - https://blog.eladgil.com/p/things-i-dont-know-about-ai

Jason Lemkin on building Sales org - https://www.youtube.com/watch?v=eMe_FWldQF0

Bains PE report - https://www.bain.com/insights/topics/global-private-equity-report/

Stripe annual report - https://assets.ctfassets.net/fzn2n1nzq965/1gMd12owbzJaSe4Y560OEJ/2a1dd409beabd1b4796a907554425b45/Stripe_2023_annual_letter.pdf

Podcast with Gili Raanan - https://www.youtube .com/watch?v=jYZPvrJBUn0&ab_channel=20VCwithHarryStebbings

Chris Dixon on career choices - https://cdixon.org/2009/09/19/climbing-the-wrong-hill

Mark Mullen on 100m seed funds - https://x .com/open_lp/status/1771209922836885820?utm_source=sundaycet.beehiiv.com&utm_medium=referral&utm_campaign=data-points

Podcast with Booking CFO - https://www.youtube.com/watch?v=YPt6Cs1hd2k&ab_channel=Bg2Pod

Iconiqs series B metrics - https://www.iconiqcapital.com/growth/updates/what-it-takes-to-raise-a-series-b?utm_source=social&utm_medium=x&utm_campaign=updates

Economist Global Warming Insurance - https://www.economist.com/leaders/2024/04/11/global-warming-is-coming-for-your-home

Perplexity fundraising - https://techcrunch.com/2024/04/23/perplexity-is-raising-250m-at-2-point-5-3b-valuation-ai-search-sources-say/

Creandum fundraising - https://creandum .com/stories/creandum-fund-vii/

SAP acquires WalkMe - https://techcrunch.com/2024/06/05/sap-to-acquire-digital-adoption-platform-walkme-for-1-5b/

Bain takes powerskool private - https://techcrunch .com/2024/06/07/powerschool-provider-of-k-12-education-software-to-go-private-in-5-6b-deal/

Mistral fundraising - https://techcrunch.com/2024/06/11/paris-based-ai-startup-mistral-ai-raises-640-million/

Goldman wrote about GenAI capex - https://www.goldmansachs.com/insights

Coatue annual market analysis - https://www.coatue.com/blog/company-update/coatues-2024-emw-conference

Google offers to buy Wiz - https://techcrunch.com/2024/07/15/googles-kurian-approached-wiz-23b-deal-could-take-a-week-to-close-source-says/

Sequoia offers LPs to buy its shares of stripe - https://x.com/borrowed_ideas/status/1812934484200989169

Procore's expansion - https://investors.procore.com/news/news-details/2024/Procore-Announces-Second-Quarter-2024-Financial-Results/default.aspx

Marie Brayer analyses LLM's adoption in enterprises - https://ontheflyinvesting.substack.com/p/llms-in-the-enterprise-h1-2024

Dan Shipper explains Strawberry - https://every.to/chain-of-thought/openai-s-new-model-strawberry-explained

Index wrote about hiring early hires - https://www.indexventures.com/scaling-through-chaos/

Rich Barton's data content loop - https://kwokchain.com/2019/04/09/making-uncommon-knowledge-common/?__readwiseLocation=

Revolut's high performance teams - https://quantumlightcapital.com/playbooks/performance-management

Financial Times writes about Thrive - https://www.ft.com/content/44c4504c-8d79-4b09-bf72-b04cf8082736?

Visma might go public - https://www.ft.com/content/74a6b766-2050-4b42-b336-9733be835c0b

Databricks - https://www.cnbc.com/2024/12/17/databricks-valued-at-62-billion-from-10-billion-financing.html