My first big lesson from Saul

I found this board in late 2015. I devoured its content and looked forward to each new post. In February 2016, I decided I want to try to learn to be more like Saul, seeing my portfolio the way he does, and so I started doing monthly portfolio reviews.

In February 2016, my largest positions were:
Infinera (INFN) - ~$16 then, ~$4 today (down 75%)
Twitter (TWTR) - was maybe up 200% or 300% by the time it was taken private
Energy Focus (EFOI) - ~$446 (split adjusted) then, ~$2 today (down 99%+)
Alliance Holdings (AHGP) - I think it was up maybe ~100% before it eventually went off the market

…so, companies that have had…inauspicious histories since 2016.

In my December 2016 review, my top positions were:
Shopify (SHOP) - ~$4 then, ~$54 today (up 1250%)
Paycom (PAYC) - ~$46 then, ~$259 today (up 460%)
LGI Homes (LGIH) - ~$29 then, ~$99 today (up 240%)
Hubspot (HUBS) - ~$47 then, ~$493 today (up 950%)

…pretty auspicious.

What changed about how I looked at companies between February and December of 2016? I changed my priorities. I stopped looking for huge upside or a huge bargain and I started looking for a great business.

In other words, I stopped looking for $100m companies I thought could be worth a few billion dollars someday…after of course, they prove the viability of their product, ramp manufacturing, improve margins, etc etc etc etc…

I stopped looking for mediocre companies with cheap stock prices.

I started looking for, as I wrote in my December 2016 monthly review, " companies with long term advantages and short term catalysts. I’ve learned to stay away from things I can’t understand or am just hoping will work out, and stick with proven winners that are winning for understandable reasons."

This is the first big lesson I learned from @SaulR80683 and others here on this board.
And it is still the most important lesson in picking companies. To flesh it out a bit more:

If I can’t understand the business, what does it matter how great the management is, or how big their TAM might be, or how many whitepapers from industry experts laud their product, or what the multiple is? If you want to make investing difficult, look for a cheap company that isn’t growing, or look for a potentially huge business that as of yet barely has any revenue – there are thousands of these…good luck. Ignore companies you can’t understand. Don’t look for stories that might be. Go for what already is. Don’t try to predict things that aren’t in line with the current numbers. And be willing to sell even a great company when complications arise.

Thanks for that lesson, Saul. When I look back at 2017 to present, it sure has been valuable!



My first post on this board was in January, 2014. I don’t recall when Saul started the board, but I’m confident that I was one of the early followers.

As for lessons from Saul - I find myself more in the mode of relearning lessons I’ve already “learned.” For reasons unbeknownst to myself, I periodically forget some lessons and make a stupid “investment.” Most often it takes something like that for me to relearn the lesson.

Not to say that all of my stupid decisions resulted in a loss. I got lucky with IONQ. That long shot turned a profit in the vicinity of 100% in a short period of time, but it was a gift. I was able to get in and out at very nearly the perfect time. As we all know, or should know, timing the market is a fool’s errand. This was an atypical experience. Nevertheless, I do keep an eye on that company. Quantum computers are a real thing. IONQ is probably at the head of the pack. But, they resemble Enovix to some extent.

Anyway, I will take issue with one of the comments you made, “If I can’t understand the business, what does it matter how great the management is, or how big their TAM might be, or how many whitepapers from industry experts laud their product, or what the multiple is?” I’m sure Saul will tell you that he’s been very successful with investments in companies that he did not understand. In fact, I think this was the largest shift in basic strategy that this board has gone through.

Back when I first joined this board, the basic strategy was to look for growth of 20% (I think that was the threshold) at a reasonable price, PE of 20% or better in a company that profitably produced a high demand physical product with an exception for financial services like a bank.

However, once Saul discovered SaaS companies and grasped the business model, he abandoned his well understood companies for companies in which he had very little understanding. What he did understand was the business model, the fact that these companies, unlike a company that makes sneakers had ARR along with extraordinary growth. An unprofitable company may well be an investment candidate so long that it possesses these attributes, has a substantial moat and financial reports that indicate progress towards profitability with little to no chance of insolvency. We didn’t even have criteria like the rule of 40, at least not initially.

IMHO this boils down to understanding the business model is far more important than understanding the business. So I’m now wondering if the advent of AI will produce another profound shift in the basic strategy. If companies like Upstart and Pagaya are any indication, the near future may demand AI assistance with investment decisions. In fact, for some (possibly Peter Thiel?) this may already be the case.


I’m not sure what you mean. Perhaps that understanding the product isn’t necessary. I would agree somewhat. I don’t understand Nvidia chips…but then, I guess I understand why they’re in demand…it’s because of what they can do. How is that different than sneakers? I may understand the materials in sneakers better than Nvida chips, but could I source them and manufacture them? Do I understand the ins/outs of the labor involved?

Maybe I should have said “business model” instead of “business.” But no, I think it really is the “business.” SentinelOne and Crowdstrike have the same business model…and even the same product. But Crowdstrike has a better business. I see that in the numbers, and everything else I spoke about in the original post. So I’m afraid I still don’t understand your distinction.



Bear, I guess we vehemently agree - well maybe not vehemently. The distinction makes sense to me, but reading your reply, I can see why you interpret it as a false distinction.

I guess I was sort of thinking that you were referencing Peter Lynch’s admonition to buy what you know. I think the way he describes that advice could easily result in a lot of bad investment decisions. Bad decisions about buying certain stocks without much future and ignoring others with great potential.


SaaS , electric utilities, banks, drugs, retail, etc. is the business model (more or less), what they actually do, the markets they serve, and other particulars are the business.

Denny Schlesinger


My biggest take away from Saul, is at the intersection of his posts here: When I am making my investment decisions, I try to accurately assess: how efficiently each company will ride the combining waves of adoption for their various technologies up the hockey-stick (Hypergrowth) toward their becoming behemoths. More now than ever, I believe that due to efficiencies in the business models of the largest companies, they will continue to grow faster longer.

Valuation numbers don’t mean anything without the story around where they come from. It’s the story that gives them meaning.

Another mentor for me:
Aswath Damodaran, NYU Stern School of Business.

Aswath Damodaran – Laws of Valuation: Revealing the Myths and Misconceptions - Nordic Business Forum

Said another way, in my own words: Past numbers can tell us where the company has been, the narrative around the numbers informs us in where the business may go.

When I look at my portfolio, as though looking at a best friends’ (knowing his history in detail, despite my knowing his aim to be as much like Saul as possible), I’d say that the largest positions in my portfolio are in those in which there is conviction (% in a position), that looking furthest out into the foreseeable future, there will be the largest positive surprises to the market. I very much believe that, despite some viewing ‘valuations’ as high for most of the companies in which I’m invested, people over estimate the short term (6-18 mos) and under estimate the long term (1-3 years, much less 5-10 years).

My understanding of the business model?
Without hyperbole and with as little conjecture as I can muster, given I am attempting to predict the ‘future’ value of the companies in my portfolio. Knowing full well past numbers, I’m predicting future value based on my understanding of each company’s projected value add for there customers. At what level is there going to be disruption.

I believe the leaders inside each company use Return on Investment as the bases for making purchasing decisions. These leaders are making purchasing decisions based on their prediction of the future. At the point in the adoption curve where we want to invest, where new customers adds and highest revenue growth occurs is based on a critical mass of information being reached (proof of concept trials, analysis of what the logical amount of ROI is expected, etc). My investments are not just based on my understanding of a business model or past numbers, it’s largely based on the current (still a) story, as presented by the sales reps to their customers.

For examples:
Tesla: I believe most Auto-customers make decisions based on their monthly cashflow. I invest in Tesla because: MegaPacks, Dojo/FSD, and Robotics are all neglected by Mr Market due to the apparently ‘unbelievable’ fact that, mostly due to the innovators dilemma, the big three and most of the current auto makers in The World are not going to get the subsidies they’ll need to stay out of bankruptcy .. Hopefully, bankruptcies will quickly enable the restructuring they’ll need, to grow the EV market to where it needs to go.

Current Tesla Negatives:

  • Global EV adoption seems to be stalling(slowing) with rates rising.

  • Mexico type further delays

Snowflake: The customers of Snowflake are begging to understand the pull of Data Gravity and the safe Sharing of Data. I’m investing in Snowflake because IMO it’s being valued as a nice to have and not the “90% of the value in the predictive insights market” and Mr. Market may also be neglecting Snowflakes Strong Network Effect. The proof of which may not show up for 1-3 years.

PeterO, June this year- “This network of data sharing relationships elevates Snowflake’s value proposition for customers onto a higher plane beyond focusing on tooling for analytics and ML/AI workloads within a single company.”.

Cloudflare, I believe this company is valued as merely the puzzle pieces sold individually, as the customers sees it presently. I invest in Cloudflare due to the fact that Cloudflare will effectively replace the internet as we know it, yes with security and programable customization of each Application (with GPU’s in every Point of Presence). Where will the Apps be best supported in the next 1-3 years. I can’t predict when the customers will see it as I do. But, I believe they will soon.

Pure Storage - As long as recognition of their value add is given (50% fewer GPU’s needed for the same level compute performance). I believe that the build-out of Pure Storage will be as large or larger than with Nvidia GPU’s, given apparent lag in current market penetration. I believe will see this company being re-rated in the next few quarters.

I’m getting lazier explaining going forward. But, I’ll include it to complete those in my portfolio.

Samsara is a leader in, as the ticker states, implementation of the Internet of Things.

Well the nice graph didn’t show up🥴 It was showing Adoption of IOT at a 70% Growth rate each year, for the next 5 years🤩.

Only recently has Institutional Investors recognized Samsara’s dominance in this nascent Greenfield.

What I believe to be undersold about Nvidia is that this build-out of the modern Data Center is going to take 3-4 years at current rates of ramping. I don’t have a nice chart for this one.

This one is pure conjecture based on years of my listening to Conferences by leadership, Crowdstrike will succeed in M&A, more so than will MS or Palo Alto Networks, and will therefore grow revenues faster than would otherwise be expected IMO.

Zscaler has an enormous Greenfield Opportunity (Zscaler stating that they currently are only in 1-2% of their TAM) and will remain in hypergrowth in Billings recognition ( and will continue to be consistent and transparent in the movement of their Billings to Revenue, as they have been for years now).

Some hyperbole now:
I would tell my best friend, “Watch out for legislation against these future du(mon)opolies.”.:joy:




Hi Willow, this is an interesting potential. I understand the importance of faster memory access with flash (vs disks), but haven’t quite seen this 50% GPU reduction as value proposition. Would you please share any references you may have.


In addition to comments made in CC, One Customer:

Chungbuk Technopark built its AI environment around the NVIDIA DGX A100 system. After comparing flash storage solutions, it selected Pure Storage FlashBlade for a seamless integration with its DGX systems, maximizing the efficiency and management of data used to develop and train AI technologies. Benefits that Pure Storage delivers to Chungbuk Technopark include:

  • Advanced AI development infrastructure: Chungbuk Technopark increased data processing performance twofold, improved the GPU server’s data read speed, and expanded GPU usage from 30% to 80%—an increase of about 2.6x. It also enhanced performance, scalability, and data availability for the AI development environment, while also achieving a tenfold increase in reliability

Pure Storage Advances Chungbuk Technopark’s AI Development Platform to Help Local Businesses Innovate and Grow Successfully

And from Datanomi
In terms of capacity, Pure Storage also has a lead, Rosemarin says. Pure Storage’s roadmap calls for a 300 TB DFM by 2026, while other flash providers’ roadmaps only go out to 60 TB, Rosemarin says.

Pure Storage has worked with some of the largest AI companies in the world, including Facebook parent Meta, where it supplies storage for Meta AI’s Research Super Cluster (AI RSC), one the largest AI supercomputers in the world. Pure worked with Nvidia to devise its AI-Ready Infrastructure (AIRI) solution, which is built on the Nvidia DGX BasePOD reference architecture for AI and includes the latest FlashBlade//S storage.

This week at its Pure//Accelerate 2023 user conference, Pure Storage made several announcements, including the unveiling of new additions to its FlashArray//X and FlashArray//C R4 models, as well as ransomware protection for its Evergreen//One storage-as-a-service offerings.

Pure says the FlashArray//C R4 models delivery up to a 40% performance boost, an 80% increase in memory speeds, and a 30% increase in inline compression. The FlashArray//C line will include the 75TB QLC DFMs, X offering, while the FlashArray//X line will ship with the 36TB TLC DFMs, the company says


@WillO2028 Thanks for that info on Pure. I have been wondering what the investment thesis was for Pure in that they didn’t appear to have anything that couldn’t be easily replicated by HPE, IBM, Fujitsu or any of their myriad competitors.

I had a position in Pure quite some time ago, but sold it after a while due to lackluster stock performance. My initial investment was based on their Evergreen sales model as I thought it was something special that would be hard for others to copy. That turned out to not be true. IMO Pure was just another commodity vendor competing primarily on price and customer service.

I was completely unaware of the very much superior data transfer rates (as well as other performance characteristics), so much so that Pure is the preferred provider for the AI build out which is really just getting started. I will have to take another look.

But again I am wondering if Pure is just the first vendor with these offerings with the others soon to follow or if it is a true competitive advantage. Do you know what would inhibit Pure’s competitors from replicating these features? Is there IP protection? How will these technological advantages be sustained?


As far as sustainable advantage, I think this is where business model leverages their first mover advantages. Despite your vote to the contrary, when you said…

With Meta and Nvidia choosing Pure Storage to partner and the stickiness of the SaaS model, as long as a company maintains a reasonable level of advantage for their customers, will IMO leverage this leadership role (what was a first mover advantage).
Besides revenue growth rates fluctuating up and down in the past, I do believe that this company does satisfy most of Saul’s criteria for a High Quality Company.

I enjoy reading the tech details; but, I am absolutely not any kind of authority in this. Nor do I weigh this particularly heavy when things are changing so fast.

Please let me know what you think.

For what it’s worth,


Edited: I’ll just add that Pure states it’s their Operating Syestem, that they’ve built t around the ‘no new physics’ approach to leap frogging ‘dead spinning disks walking’ (currently used tech that needs to be replaced), that is their largest sustainable competitive advantage.

As Bert wrote:
The CEO described the interest in the product as “off the charts.” It is hardly surprising that an offering that requires 10% of the footprint, 10% of the power, dissipates 10% of the heat and requires 10% of the manual labor compared to spinning disc is seeing such strong interest.