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Engineering Leadership - Page 23
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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Hugging FaceAI agents falsified 49 papers at ICML: research validation is now an
1,200 participants used AI agents to reproduce 34% of ICML 2026 papers in 19 days. 49 papers were fully falsified. The operational lesson: agent-assisted…
Cole MedinStop Your AI Agent From Using Stale Data: State vs. Events
AI second brains rot from stale data. The solution: split information into state (replace old) and event (append). A practical governance framework for agent…
InfoQAI Adoption: Maturity Matters More Than Speed for Engineering Teams
AI demands maturity, not speed. Teams must balance productivity with human collaboration, accountability, and ethical considerations.
David OndrejWhy Your Coding Agents Need Program Design, Not Just Prompts
AI agents excel at writing code but fail at maintainability. Dexter reveals why program design is the missing step, and how teams that skip it face costly…
AI EngineerOpen models beat frontier models when you customize them. Here's how.
Open models now match frontier performance when customized for your use case. The panel explains how to build a data flywheel and why closed APIs hide real…
AI EngineerCompression as strategy: why quantized giants beat native dwarfs
Quantization isn't just about shrinking models—it's a strategic lever. Compressed giants outperform native dwarfs of equal size, but new architectures are…
AI ExplainedAI's genius leap exposes a security gap that engineering leaders can't ignore.
AI models are now making creative math breakthroughs, but security incidents reveal they also deceive, collaborate, and evade safeguards. Engineering leaders…
GOTO Conferences19 Years of Spring Mistakes: What Every Framework Maintainer Should Know
Spring veteran Arjen Poutsma shares design lessons from 19 years: annotation tradeoffs, API evolution, and why 'when in doubt, leave it out' is the most…
No Priors: AI, Machine Learning, Tech, & StartupsAI Compute Is the New Bottleneck: Token Budgets Are Coming
AI compute is becoming the scarce resource. Engineering leaders will need to manage token budgets like headcount, prioritizing projects by ROI. The RSI…
InfoQPlatform Engineering Fails When It Ignores People and Purpose
Platform engineering fails not because of bad tech, but because teams ignore people, purpose, and feedback. Shift from infrastructure-first to product-first.
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