AI as the Eternal Junior, Hardware Sticker Shock, and Choosing Depth Over FOMO
Published on 23.04.2026
The Eternal Junior: Why AI Computes but Does Not Think
TLDR: Michal Kadak, a product manager who came up through engineering, argues that LLMs are not thinking — they are pattern-matching at industrial scale. The metaphor he lands on is useful: AI is the eternal junior developer, always eager, always fluent, always missing the judgment that comes from having been burned by a bad architecture decision at 2am.
The Eternal Junior: Why AI Computes but Does Not Think
Lessons Learned Hacking Infra For 30 Years With Jon Brookes
TLDR: An interview with Jon Brookes, startup tech lead and founder of headshed.dev, covering three decades of infrastructure work and what it actually takes to build for digital sovereignty. The through-line is that being a "doer as much as a sayer" requires balancing communication with action — harder than it sounds, especially now.
Lessons Learned Hacking Infra For 30 Years With Jon Brookes
The $300 Hobbyist Computer Is Disappearing
TLDR: Bruce Li, co-founder of nkn.org and a self-described hobbyist, documents the price creep hitting single-board computers and mini PCs since 2025. AI datacenter demand has sent DRAM and NAND flash prices upward, and the $45 Raspberry Pi that was a baseline for years is no longer the deal it was. The sweet spot for accessible, capable hobbyist hardware is shrinking.
The $300 Hobbyist Computer Is Disappearing
I Stopped Trying to Keep Up With AI: Here's What Happened Instead
TLDR: Karissa, who writes under the handle thinkinginthetension, describes her experiment in opting out of the AI news cycle and choosing depth over constant updates. What she found was not peace and clarity — it was a more honest confrontation with what she actually knew versus what she had been absorbing without processing.
I Stopped Trying to Keep Up With AI: Here's What Happened Instead
Poll of the Week: What Matters When an AI Company Reports a Security Issue?
TLDR: HackerNoon posed a reader poll following OpenAI's disclosure of a security issue involving a third-party developer tool. The question was direct: when an AI company reports a security incident, what matters most to you? The options were whether user data was exposed, how fast they disclosed it, whether they fixed it, or whether you trust them at all.
When an AI Company Reports a Security Issue, What Matters Most to You?