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Engineering Leadership - Page 3
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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Y CombinatorJensen Huang: Why NVIDIA's near-death moment built its AI dominance
NVIDIA's CEO reveals the company almost failed because their founding algorithm was wrong. The real lesson for engineering leaders: technology choices matter…
AI EngineerWhy most AI benchmarks are quietly fake and what actually matters
Data markets are in a fog of war. Most benchmarks are quietly fake. The real signal is which domain-specific workflow data labs are actually buying, not…
IBM TechnologyAI fluency creates an interpretation bottleneck that STEM alone can't solve
AI can speak fluently without understanding meaning. The humanities—epistemology, rhetoric, ethics—become operational skills for engineering teams building…
AI EngineerSilent failures at scale: why your training code probably has undetected bugs
Poolside reveals how broken GPUs and FP8 kernel bugs silently corrupt pretraining. The solution isn't better data—it's training infrastructure that can catch…
AI EngineerHow SonderMind built safe AI coach: modular guardrails, clinical evals
SonderMind's approach to mental health AI: separate guardrail LLMs, clinician-defined evals from real conversations, and a design philosophy that favors…
Y CombinatorAI has killed the pure software moat—hard problems are your only defense
YC partners argue pure software is now a commodity. The real moat? A hard problem—hardware, regulation, or distribution. Engineering leaders must reassess…
Y CombinatorLLMs don't lead to AGI: Why world models are the next AI
Alex Lebrun argues LLMs can't achieve common sense because they learn from text, not experience. World models trained on video and sensory data may be the…
Y CombinatorPhysical AI's Data Bottleneck: The Next Platform Shift Requires New Infrastructure
Physical AI is coming, and data infrastructure is the bottleneck. Encord's founder on why petabyte-scale multimodal data is the next challenge.
AI EngineerYour Agent’s Real Benchmark Isn’t Public — It’s Your Production Trace
Turning agent traces into simulations creates a private benchmark that mirrors your tools and policies — the only reliable way to ship agents with confidence.
AI EngineerUber’s AI Agent Lesson: Redundant QA Gates Stop Reward Hacking
Uber’s photo agent auto-tunes via closed-loop evals, but layered QA gates stop hallucinations and reward hacking before reaching users.
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