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Engineering Leadership - Page 12
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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Latent SpaceClaude Code Mods: The Platform Shift Most Teams Aren't Prepared For
Claude Code evolves from CLI to extensible platform. Mods bring real power — and real security debt. Engineering leaders need to plan for agent governance now.
InfoQYour AI tool choice matters less than your team's culture of safety
Psychological safety is the overlooked prerequisite for AI adoption. Without it, teams get stuck in polarization and silence.
AI EngineerAI code has reached enterprise parity; review workflows are the bottleneck
Greptile's data: ~25% of enterprise PRs are now largely AI-generated, and they survive code review about as well as human PRs. Time to rework PR review.
AI EngineerAI builders are moving from factory automation to orchestrated, human-led agent teams
Conductor's co-founder argues fast AI builders run orchestras, not factories: human review zones, centralized context, free-range agents. But it's a launch…
Theo - t3․ggModel wave proves pacing is working: AI is getting less dumb
The new model wave is not proof that frontier pacing failed. It is the strategy working: cheaper, more reliable models, not smarter ones.
David OndrejThe missing business context is the real agent adoption blocker
Teams that can't describe their own workflows will struggle with agents. The useful pattern: one document with evals.
AI ExplainedOpus 5.5: The speed of release hides a broken safety pipeline.
Opus 5.5 is fast and cheap, but the system card reveals broken safety commitments and an evaluation pipeline that can't keep up with model release cycles.
No Priors: AI, Machine Learning, Tech, & StartupsBuying incumbents to refound them as AI-first companies: is it real?
Sequence Holdings is buying incumbents in banking and insurance, then refounding them as AI-first operations. Early results from a community bank show 94%…
AI EngineerAI productivity needs organizational rewiring, not better models alone.
Two talks from AI Engineer Paris: history shows transformative tech takes decades to deliver productivity. Agent safety, sandbox isolation, and workflow…
Machine Learning Street TalkTabular deep learning finally works. Default tools are about to shift.
TabPFN 3 makes deep learning work for tabular data, outperforming XGBoost in a single forward pass. The bottleneck shifts from model tuning to problem framing.
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