MarceliusK

6 ms·

61.
by MarceliusK 6mo ago
Once he could satisfy the expected interfaces well enough, the rest of the system seems to have been surprisingly willing to play along
62.
by MarceliusK 6mo ago
Really impressive work, and a very fun read
63.
by MarceliusK 6mo ago
Apple's primary concern is control over the revenue stream
64.
by MarceliusK 6mo ago
The "educational" exception is definitely a convenient loophole, but it raises questions about consistency and fairness in how these rules are enforced across the board
65.
by MarceliusK 6mo ago
At the end of the day, Apple is justifying this move as rule enforcement, but it's clear that the guidelines seem outdated in the context of rapidly advancing AI tools
66.
by MarceliusK 7mo ago
Understanding the mechanics isn't the same as being immune to the experience
67.
by MarceliusK 7mo ago
I think this is less about a single trait and more about context
68.
by MarceliusK 7mo ago
The hard part is that the same qualities that make these systems helpful (empathetic, responsive, personalized) are exactly the ones that can make them risky
69.
by MarceliusK 7mo ago
Or a third option: eggs are just a terrible proxy for CPI
70.
by MarceliusK 7mo ago
I wouldn't read this as "AI can't do this efficiently yet" but more like "we're still figuring out the playbook"
71.
by MarceliusK 7mo ago
Technically interesting and genuinely well-written end to end
72.
by MarceliusK 7mo ago
Overall this feels less like a quirky egg project and more like a blueprint for how messy real-world data pipelines are going to look going forward
73.
by MarceliusK 7mo ago
The fitness market has been moving in that direction for years
74.
by MarceliusK 7mo ago
It feels like a classic case of a product category being forced into a venture-scale narrative
75.
by MarceliusK 7mo ago
The pitch always seemed aimed at meat eaters who might replace one or two meals a week if the substitute was close enough
76.
by MarceliusK 7mo ago
The irony is that a lot of people who were interested in plant-based eating didn't actually want hyper-engineered meat replacements in the first place
77.
by MarceliusK 7mo ago
What investigators often look for isn't just wallet age, but funding patterns, timing, and linkages between wallets
78.
by MarceliusK 7mo ago
Prediction markets are probably most "accurate" when at least some participants have genuinely superior information
79.
by MarceliusK 7mo ago
I think this is mixing up two different things: influence and knowledge
80.
by MarceliusK 7mo ago
In theory maybe, but in practice companies almost always do care about keeping things like release timing, product status or leadership decisions confidential. Even if they haven't publicly announced a policy about prediction markets s
81.
by MarceliusK 7mo ago
Makes you wonder how much "market accuracy" on these platforms is actually just leakage
82.
by MarceliusK 8mo ago
Historically, tools that made thinking cheaper didn't eliminate thinkers...
83.
by MarceliusK 8mo ago
The scary part is that you can't just "hire mastery" on demand. You have to grow it
84.
by MarceliusK 8mo ago
I'm skeptical that this fully replaces thinking, though. It may replace certain forms of effort, but historically every increase in leverage just shifts where the bottleneck is
85.
by MarceliusK 8mo ago
At minimum, the default should be "pay exact amount"
86.
by MarceliusK 8mo ago
The bigger issue, to me, is that the burden is on customers at all. That's what creates all this awkwardness and moral accounting in the first place
87.
by MarceliusK 8mo ago
And I think people don't mind tipping when they feel it's voluntary
88.
by MarceliusK 8mo ago
The fact that people don't believe you when you explain it just shows how effective the framing is
89.
by MarceliusK 8mo ago
It's one thing to read about dark patterns, it's another to feel your cursor being baited in real time
90.
by MarceliusK 8mo ago
The danger is that these nuanced, legitimate use cases get rhetorically stretched to support much bigger claims. That's where skepticism kicks back in.

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