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Engineering Leadership - Page 13
AI decisions through the lens of teams and execution. Curated tldw.news briefings about engineering leadership, with practical engineering takeaways from long-form AI and developer-tool videos.
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The Pragmatic EngineerWhy agentic design still needs the human sketch
Design engineer Maggie Appleton on why sketching remains essential even as agents accelerate UI prototyping, and why multiplayer alignment is the next big…
IBM TechnologyAI labs are ignoring cybersecurity experts — and it shows
Frontier AI labs focus on alignment while cybersecurity experts point to basic controls like MFA and air-gapping. The gap between the two communities is…
GOTO ConferencesAI Agents Won’t Work Without Platform Engineering
The book 'Thinking in Platforms' argues that AI agents require structured platforms. But the harder shift is organizational: treating platforms as products…
InfoQWhy your AI rollout is creating bottlenecks you can't see
Hendrickson and Tossey argue that AI amplifies hidden bottlenecks. Leaders must observe before pulling levers.
Y CombinatorYC data: Hard tech, solo founders, and the new revenue speed limit.
YC partners share batch data: hard tech startups have tripled, solo founder acceptance has quadrupled, and companies are hitting seven figures in three…
Theo - t3․ggAI didn't kill React Native. Shopify just found a different bet.
Shopify drops React Native for native, crediting AI agents. But the real story is about Expo, OTA updates, and whether this bet generalizes beyond Shopify's…
InfoQAI is hollowing out junior engineers; preceptorship is the fix.
Scott Hanselman argues AI is destroying the junior developer pipeline by eliminating routine coding tasks that build foundational skills. His proposed fix: a…
InfoQRoblox's fix for the trust gap between AI code and production shipping
Roblox's engineering director reveals that the hardest part of shipping AI-generated code isn't the models — it's trust infrastructure, policy changes, and…
AI EngineerWhen AI coding agents produce slop: the architecture lesson from Dioxus
Dioxus's team found AI agents produce thousands of lines that fail quality checks. Their lesson: code is cheap, architecture is not.
Theo - t3․ggNo single best model: choose by mergeability vs autonomy
Fable ships cleaner code, Astra handles computer use and big rewrites. The real decision is mergeability versus autonomous reach—and most teams need both.
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