Lawtrades nearly failed three years ago.

We couldn't raise Series A or enthusiasm from VCs.

We raised $6M (at a $80M valuation) from 100 customers and investors using a link and no pitching.

Step-by-step:

We refocused our business first.

Lawtrades raised $3.7M while Atrium raised $75M. By comparison, we seemed unimportant.

We had to close the company or try something new.

As I've written previously, a pivot saved us. Our initial focus on SMBs attracted many unprofitable customers. SMBs needed one-off legal services, meaning low fees and high turnover.

Tech startups were different. Their General Councels (GCs) needed near-daily support, resulting in higher fees and lower churn than SMBs.

We stopped unprofitable customers and focused on power users. To avoid dilution, we borrowed against receivables. We scaled our revenue 10x, from $70k/mo to $700k/mo.

Then, we reconsidered fundraising (and do it differently)
This time was different. Lawtrades was cash flow positive for most of last year, so we could dictate our own terms. VCs were still wary of legaltech after Atrium's shutdown (though they were thinking about the space).

We neither wanted to rely on VCs nor dilute more than 10% equity. So we didn't compete for in-person pitch meetings.

AngelList Roll-Up Vehicle (RUV). Up to 250 accredited investors can invest in a single RUV. First, we emailed customers the RUV. Why? Because I wanted to help the platform's users.

Imagine if Uber or Airbnb let all drivers or Superhosts invest in an RUV. Humans make the platform, theirs and ours. Giving people a chance to invest increases their loyalty.

We expanded after initial interest.

We created a Journey link, containing everything that would normally go in an investor pitch:

• Slides
• Trailer (from me)
• Testimonials
• Product demo
• Financials

We could also link to our AngelList RUV and send the pitch to an unlimited number of people. Instead of 1:1, we had 1:10,000 pitches-to-investors.

We posted Journey's link in RUV Alliance Discord. 600 accredited investors noticed it immediately. Within days, we raised $250,000 from customers-turned-investors.

Stonks, which live-streamed our pitch to thousands of viewers, was interested in our grassroots enthusiasm. We got $1.4M from people I've never met.

These updates on Pump generated more interest. Facebook, Uber, Netflix, and Robinhood executives all wanted to invest. Sahil Lavingia, who had rejected us, gave us $100k.

We closed the round with public support.

Without a single pitch meeting, we'd raised $2.3M. It was a result of natural enthusiasm: taking care of the people who made us who we are, letting them move first, and leveraging their enthusiasm with VCs, who were interested.

We used network effects to raise $3.7M from a founder-turned-VC, bringing the total to $6M at a $80M valuation (which, by the way, I set myself).

What flipping the fundraising script allowed us to do:

We started with private investors instead of 2–3 VCs to show VCs what we were worth. This gave Lawtrades the ability to:

• Without meetings, share our vision. Many people saw our Journey link. I ended up taking meetings with people who planned to contribute $50k+, but still, the ratio of views-to-meetings was outrageously good for us.
• Leverage ourselves. Instead of us selling ourselves to VCs, they did. Some people with large checks or late arrivals were turned away.
• Maintain voting power. No board seats were lost.
• Utilize viral network effects. People-powered.
• Preemptively halt churn by turning our users into owners. People are more loyal and respectful to things they own. Our users make us who we are — no matter how good our tech is, we need human beings to use it. They deserve to be owners.

I don't blame founders for being hesitant about this approach. Pump and RUVs are new and scary. But it won’t be that way for long. Our approach redistributed some of the power that normally lies entirely with VCs, putting it into our hands and our network’s hands.

Strange and complex behavior of frog cell blobs

A xenobot “parent,” shaped like a hungry Pac-Man (shown in red false color), created an “offspring” xenobot (green sphere) by gathering loose frog cells in its opening.

Tiny “living machines” made of frog cells can make copies of themselves. This newly discovered renewal mechanism may help create self-renewing biological machines.

According to Kirstin Petersen, an electrical and computer engineer at Cornell University who studies groups of robots, “this is an extremely exciting breakthrough.” She says self-replicating robots are a big step toward human-free systems.

Researchers described the behavior of xenobots earlier this year (SN: 3/31/21). Small clumps of skin stem cells from frog embryos knitted themselves into small spheres and started moving. Cilia, or cellular extensions, powered the xenobots around their lab dishes.

The findings are published in the Proceedings of the National Academy of Sciences on Dec. 7. The xenobots can gather loose frog cells into spheres, which then form xenobots.
The researchers call this type of movement-induced reproduction kinematic self-replication. The study's coauthor, Douglas Blackiston of Tufts University in Medford, Massachusetts, and Harvard University, says this is typical. For example, sexual reproduction requires parental sperm and egg cells. Sometimes cells split or budded off from a parent.

“This is unique,” Blackiston says. These xenobots “find loose parts in the environment and cobble them together.” This second generation of xenobots can move like their parents, Blackiston says.
The researchers discovered that spheroid xenobots could only produce one more generation before dying out. The original xenobots' shape was predicted by an artificial intelligence program, allowing for four generations of replication.

A C shape, like an openmouthed Pac-Man, was predicted to be a more efficient progenitor. When improved xenobots were let loose in a dish, they began scooping up loose cells into their gaping “mouths,” forming more sphere-shaped bots (see image below). As many as 50 cells clumped together in the opening of a parent to form a mobile offspring. A xenobot is made up of 4,000–6,000 frog cells.

Petersen likes the Xenobots' small size. “The fact that they were able to do this at such a small scale just makes it even better,” she says. Miniature xenobots could sculpt tissues for implantation or deliver therapeutics inside the body.

Beyond the xenobots' potential jobs, the research advances an important science, says study coauthor and Tufts developmental biologist Michael Levin. The science of anticipating and controlling the outcomes of complex systems, he says.

“No one could have predicted this,” Levin says. “They regularly surprise us.” Researchers can use xenobots to test the unexpected. “This is about advancing the science of being less surprised,” Levin says.

As you know, I like to turn my intuition into decision rules (principles) that can be back-tested and automated to create a portfolio of alpha bets. I use one for bubbles. Having seen many bubbles in my 50+ years of investing, I described what makes a bubble and how to identify them in markets—not just stocks.

A bubble market has a high degree of the following:

1. High prices compared to traditional values (e.g., by taking the present value of their cash flows for the duration of the asset and comparing it with their interest rates).
2. Conditons incompatible with long-term growth (e.g., extrapolating past revenue and earnings growth rates late in the cycle).
3. Many new and inexperienced buyers were drawn in by the perceived hot market.
4. Broad bullish sentiment.
5. Debt financing a large portion of purchases.
6. Lots of forward and speculative purchases to profit from price rises (e.g., inventories that are more than needed, contracted forward purchases, etc.).

I use these criteria to assess all markets for bubbles. I have periodically shown you these for stocks and the stock market.

What Was Shown in January Versus Now

I will first describe the picture in words, then show it in charts, and compare it to the last update in January.

As of January, the bubble indicator showed that a) the US equity market was in a moderate bubble, but not an extreme one (ie., 70 percent of way toward the highest bubble, which occurred in the late 1990s and late 1920s), and b) the emerging tech companies (ie. As well, the unprecedented flood of liquidity post-COVID financed other bubbly behavior (e.g. SPACs, IPO boom, big pickup in options activity), making things bubbly. I showed which stocks were in bubbles and created an index of those stocks, which I call “bubble stocks.”

Those bubble stocks have popped. They fell by a third last year, while the S&P 500 remained flat. In light of these and other market developments, it is not necessarily true that now is a good time to buy emerging tech stocks.

The fact that they aren't at a bubble extreme doesn't mean they are safe or that it's a good time to get long. Our metrics still show that US stocks are overvalued. Once popped, bubbles tend to overcorrect to the downside rather than settle at “normal” prices.

The following charts paint the picture. The first shows the US equity market bubble gauge/indicator going back to 1900, currently at the 40% percentile. The charts also zoom in on the gauge in recent years, as well as the late 1920s and late 1990s bubbles (during both of these cases the gauge reached 100 percent ).

The chart below depicts the average bubble gauge for the most bubbly companies in 2020. Those readings are down significantly.

The charts below compare the performance of a basket of emerging tech bubble stocks to the S&P 500. Prices have fallen noticeably, giving up most of their post-COVID gains.

The following charts show the price action of the bubble slice today and in the 1920s and 1990s. These charts show the same market dynamics and two key indicators. These are just two examples of how a lot of debt financing stock ownership coupled with a tightening typically leads to a bubble popping.

Everything driving the bubbles in this market segment is classic—the same drivers that drove the 1920s bubble and the 1990s bubble. For instance, in the last couple months, it was how tightening can act to prick the bubble. Review this case study of the 1920s stock bubble (starting on page 49) from my book Principles for Navigating Big Debt Crises to grasp these dynamics.

The following charts show the components of the US stock market bubble gauge. Since this is a proprietary indicator, I will only show you some of the sub-aggregate readings and some indicators.

Each of these six influences is measured using a number of stats. This is how I approach the stock market. These gauges are combined into aggregate indices by security and then for the market as a whole. The table below shows the current readings of these US equity market indicators. It compares current conditions for US equities to historical conditions. These readings suggest that we’re out of a bubble.

1. How High Are Prices Relatively?

This price gauge for US equities is currently around the 50th percentile.

2. Is price reduction unsustainable?

This measure calculates the earnings growth rate required to outperform bonds. This is calculated by adding up the readings of individual securities. This indicator is currently near the 60th percentile for the overall market, higher than some of our other readings. Profit growth discounted in stocks remains high.

Even more so in the US software sector. Analysts' earnings growth expectations for this sector have slowed, but remain high historically. P/Es have reversed COVID gains but remain high historical.

3. How many new buyers (i.e., non-existing buyers) entered the market?

Expansion of new entrants is often indicative of a bubble. According to historical accounts, this was true in the 1990s equity bubble and the 1929 bubble (though our data for this and other gauges doesn't go back that far). A flood of new retail investors into popular stocks, which by other measures appeared to be in a bubble, pushed this gauge above the 90% mark in 2020. The pace of retail activity in the markets has recently slowed to pre-COVID levels.

4. How Broadly Bullish Is Sentiment?

The more people who have invested, the less resources they have to keep investing, and the more likely they are to sell. Market sentiment is now significantly negative.

5. Are Purchases Being Financed by High Leverage?

Leveraged purchases weaken the buying foundation and expose it to forced selling in a downturn. The leverage gauge, which considers option positions as a form of leverage, is now around the 50% mark.

6. To What Extent Have Buyers Made Exceptionally Extended Forward Purchases?

Looking at future purchases can help assess whether expectations have become overly optimistic. This indicator is particularly useful in commodity and real estate markets, where forward purchases are most obvious. In the equity markets, I look at indicators like capital expenditure, or how much businesses (and governments) invest in infrastructure, factories, etc. It reflects whether businesses are projecting future demand growth. Like other gauges, this one is at the 40th percentile.