In general, the answer usually is to find people in your own network. If you go by that funnel the first thing you need is a network. LI is great at this. The next thing is to see who in your network is worth talking to. Find out whether the pain-point that you recognized resonates with them. A LI blast to your network might work as well to give you a bit of credibility. One thing that is cited often that does NOT work is spamming people asking for their time to learn about a problem. Nobody ever got back to me wit this method. But asking people in your own network for warm intros almost always works.

what's they key thesis here and the argument ?

*Key thesis:* When technology eliminates meaningful performance differences between products, industries shift from competing on *engineering and function* to competing on *brand and status*. The Swiss watch industry after the quartz crisis is a clear example: mechanical watches stopped being valuable tools and became *luxury symbols whose value comes mainly from branding, scarcity, and signaling wealth*.

*In one sentence:* The essay argues that when technology makes functional differences between products disappear, industries shift from engineering competition to branding competition, and the modern luxury watch market illustrates how that transformation works.

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If you want, I can also explain *why this essay is controversial among economists and designers*—there are a few big assumptions in the argument.

And the counter A few places the argument is debatable (even if it’s persuasive as a narrative):

It treats “brand” and “engineering” as mostly opposed. In practice, luxury buyers often do pay for engineering (finishing, durability, serviceability, movement architecture), and those technical choices can reinforce brand rather than fight it. The tension is real, but not always zero-sum.

It downplays other drivers of the Swiss recovery. The rebound isn’t only “they discovered brand.” Things like Swatch’s role in recapitalizing distribution/production, industry consolidation, improvements in manufacturing, and globalization of luxury demand can explain a lot of the late-1980s revenue surge alongside marketing.

The “artificial scarcity = managed asset bubble” framing is provocative but contestable. Scarcity can be interpreted as: capacity constraints, quality control, long-term brand stewardship, or channel strategy—not necessarily “bubble management.” It may function bubble-like in resale markets, but that doesn’t prove intent or fragility in the way financial bubbles work.

Some claims are asserted more than demonstrated. Examples: Rolex “abandoned research” after ~1960; “only three survived as independents”; “most brands are owned by six holding companies”; “they rebuy hundreds per year.” These might be true in broad strokes, but the essay uses them as load-bearing supports without showing evidence in-text (beyond a couple notes).

The design-history claims are simplified. Watch size and shape trends aren’t only branding; they’re also driven by changing tastes, ergonomics, manufacturing norms, sport/tool styling, and shifting notions of masculinity. “Big = cheap historically” is directionally true in some eras, but not a universal law.

The gender section is especially shaky. “Women never really went for mechanical watches” and the steam-engine analogy read like overgeneralizations—there are strong counterexamples (and cultural variation) that complicate that story.

I have to (unwillingly) do frontend work so I recently read up on CSS quite a bit. I have always thought that using computed numbers for styling is bonkers. Its better to use CSS that uses logical values. The site seems to emphasize that style.

Open source for infrastructure products work just fine. It simplifies distribution by eliminating the need for procurement, builds some kind of attachment since people love using their own tinkered products and hedges risk for the customer since if the devs stop working on the product someone else will pick up.

But having to fill out forms, doing compliance work are great money making levers for which you just charge through the nose. Ultimately, open soircing is a distribution strategy and whether you should adopt it or not is dependent on the context. Most infra products do and it works out fine. Case in point: Clickhouse, Kafka, Grafana, Sentry, RedHat, Gitlab.

For me, I am currently slogging through Lazlo Lovasz's combinatorics book and another one on Monte Carlo method. Dont know why but its just a good way to pass the time while staying away from the internet and its attention hogging.