In this series of looking at the people around the table for $SIVE, the next person I found interesting is Heine Thorsgaard. He is the CFO - not the kind of profile that usually gets attention in a semiconductor story. But maybe very relevant for where Sivers is right now. Because Sivers is not just trying to prove the technology. It also has to deal with the boring but critical stuff: reporting, cash discipline, financing, investor trust, strategic finance, and possibly M&A readiness. Before Sivers, Heine was CFO of Napatech, $NAPA / $NAPA.OL, from 2018. Napatech is not a random finance background. It is a listed technology hardware company selling programmable network cards for network performance, cybersecurity, and data center applications. Sound a little familiar? The interesting part is the financial setup he walked into. Napatech had a very difficult 2018: Revenue: DKK 106m Gross margin: 46.2% EBITDA: DKK -75m Free cash flow: DKK -82m Then in 2019: Revenue: DKK 171m Gross margin: 74.5% EBITDA: DKK 15m Positive free cash flow That is a meaningful turnaround. Not saying the CFO alone caused it. But it does show he has been inside a listed hardware company during a messy transition from ugly numbers to a cleaner financial story. The later Napatech years were difficult again. Revenue became volatile. Profitability weakened. The company had to keep dealing with the hard parts of listed hardware execution. But honestly, that is also part of the point. Sivers does not need someone who has only seen perfect spreadsheets. It needs people who understand the ugly middle: lumpy revenue, margin pressure, cash burn, capital raises, investor communication, and the gap between an exciting technology story and actual financial proof. Before Napatech, Heine also had CFO / financial leadership roles around ALECTIA and Orbicon. ALECTIA later merged with NIRAS, creating a larger Nordic consulting engineering group. Orbicon was later acquired by WSP Global, TSX:WSP / $WSP.TO. Again, not forcing a "everything he touched worked" narrative. But the pattern is interesting. He has been around companies where finance was not just accounting. It was about making the company understandable, fundable, integratable, and credible to larger outside actors. That maps quite neatly to Sivers. Right now, $SIVE has had delayed reporting, restatements, PCAOB audit uplift work, a potential Nasdaq New York dual-listing evaluation, cash burn, dilution risk, and a much larger opportunity pipeline. At the same time, the company is talking about AI data center photonics, SATCOM, defense, mmWave, and 2027 ramps. That combination is exciting. But a pipeline is not cash. A design win is not gross margin. And a technology story is not financial trust. This is where the CFO role matters. If Sivers wants to graduate from speculative small cap story to serious semiconductor scale up, the numbers have to become cleaner. Can Heine help get them there? Only time will tell. But his background is exactly the kind of CFO scar tissue I like to see here.

The "fundamentally flawed" critique often reveals more about the critic's mental model than the company itself. Many highly educated investors are trained in environments that reward clean, linear thinking: Better inputs → better outputs Better fundamentals → better company Cleaner model → cleaner conclusion Messy company → reject This works in exams, consulting decks, academic papers, and textbook finance. But fortunately or unfortunately markets do not work that way. Market returns are not normally distributed. They are closer to power law systems. A small handful of outcomes drive the majority of long term returns. The difference between a decent portfolio and a legendary one often comes down to whether you owned one or two extreme winners. This is why the old line "If you’re so smart, why aren't you rich?" stings. Intelligence, effort, and analytical talent may be roughly normally distributed. Wealth and investment success are not. They are skewed by timing, positioning, leverage, cumulative advantage, and sequences of events that compound in ways no clean model can fully capture. That is why "fundamentally flawed" is often an incomplete stopping point. The real question is not: "Is the company flawed?" Of course many high conviction ideas are flawed. Small revenue base. Execution risk. Dilution risk. Unproven manufacturing. Pipeline uncertainty. Customer-conversion risk. The better question is: Are the flaws fatal, or are they bridgeable? Most flawed companies remain flawed. Some are landmines. But a few flawed companies become massive outliers precisely because the market overweights today's mess and underweights the possibility of a transformed future state. This is not an argument for abandoning rigor or blindly buying story stocks. It is an argument for the right kind of rigor in a power law environment. Instead of demanding perfection, the real work is underwriting asymmetric optionality: 1. Can the company cross from current mess to larger scale? 2. Are the bottlenecks real, and are they solvable? 3. Are the people capable of crossing the chasm? 4. Is the market mispricing the probability of a positive tail outcome? That is the difference between gambling on hope and deliberately positioning in messy branches with outlier potential. Perfection is rare. Obvious perfection is usually expensive. The edge is not in saying "this is flawed." The edge is in knowing which flaws are fatal, which flaws are bridgeable, and which bridgeable flaws the market has mistaken for fatal ones.

Sometimes the biggest stories are not always about the biggest names. Cape Verde is to the World Cup what $SIVE is to photonics: small on the map, bigger in the system than people think. #FIFAWorldCup

After the bounce, everyone (including me) suddenly has a clean explanation. "AI was always going higher." "The dip was obvious." "The war headline was just noise." But a few red days ago, the same market felt completely different: "AI bubble popped." "Multiples were too high." "Retail was exit liquidity." That is the narrative fallacy in markets. The lesson is not "always buy the dip." The lesson is to write down what you believed before the chart fixed your memory. It will help you in the long run

This is a good finance 101

Translation: @JohnCena doesn't like 0DTE option traders

Sweden won 5–1. Congratulations to all Swedish people. 🇸🇪 Now it's time to celebrate the victory by buying $SIVE

One thing I think many people underestimate in AI discussions is how deeply human centered our institutions are. Banking, law, medicine, education, government, religion, corporate governance, insurance, defense. These systems were not built around compute. They were built around human judgment, accountability, trust, incentives, and relationships. Could AI automate more and more of these functions? Absolutely. But replacing a task is very different from replacing the foundations that entire institutions are built upon. Human processes are often frustratingly slow, but they are deeply embedded in how society coordinates itself. That is why Satya's framing of human capital and token capital working together resonates with me. The future may not be humans versus AI. It may be organizations that learn how to compound both faster than everyone else. x.com/i/status/2066135861280…

JUST IN: Case

But who's Justin? he seems to have all the breaking news.

Over the last few days, I’ve spoken to people working in very different sectors: banking, law, medicine, space, and even a priest. Different domains, same pattern: nobody wants fully autonomous black box AI for serious decisions. They want AI that helps humans reason, audit, decide, and act. Guess which company enables human-in-the-loop operational AI? $PLTR

How $SIVE haters LARP when they go outside

This is kinda... weird? $SPCX

The 1/16 framing is doing narrative work. 500M / world population is about 6%, so the arithmetic is close, but the interpretation is weak. The right question is not "how many humans exist?" but "how many internet users, YouTube users, active accounts, duplicates, inactive users and bots are in the denominator?" The same mistake happens in markets: the number can be real while the framing can be misleading.e.g. TAM ≠ demand. Orders ≠ delivered revenue Backlog ≠ guaranteed sales Growth ≠ quality of growth etc.

JUST IN: I am also welcoming the US-Iran deal.

TIL Rolls Royce builds nuclear reactors

Pizza bottleneck quiz from Naples: There is a pizzeria on almost every corner here. So, I was wondering... If you had to invest in the pizza supply chain, which companies would you buy? Which companies do you think are controlling the supply chain bottlenecks?