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Engineering Leadership - Page 10
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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AI EngineerAgents Must Prove Safety Before Execution, Not Just Be Aligned
Erik Meijer revives 1990s proof-carrying code to verify agent plans before they mutate the world—shifting safety from hope to check. Is this practical at scale?
AI EngineerThe Real RL Bottleneck Isn't Models, It's Your Workflow Spec
The new open-source RL stack re-centers the AI bottleneck on designing multi-agent workflows, with a $50k, 3-day frontier-model run as proof.
IBM TechnologyAI CodeGen: Trust Is the Real Bottleneck
84% of devs use AI code tools, but 55% of generated code has vulnerabilities. The real question: which translator does your team trust in production?
InfoQAI Governance Begins with Your Test Suite, Not a New Policy
AI governance is boring: tests, scanning, checklists. Sarah Wells on hidden talent and cost risks.
InfoQThe Outage That Wasn’t Human Error
Azure’s global WAN outage was a systemic governance failure, not human error—a blameless deep dive reveals why simplistic root causes are dangerous.
AI EngineerStop Patching, Start Rewriting
AI is discovering old bugs at new speeds. The fix isn't faster patching; it's systemic rewrites in memory-safe languages and AI-powered code review.
AI EngineerHow Tree Structure Solves LLM Hallucination at Industrial Scale
Phaidra solved hallucination at scale by exploiting data center hierarchy, delivering 100% recall and flat cost from 64 to 460k GPUs.
AI EngineerThe Agent Web Won't Be Open Until Discovery Works
MIT's Nanda builds open agent discovery—like DNS for AI—to avoid lock-in. Simulator, index live; governance and adoption remain speculative.
AI EngineerTypeScript Takes AI Agent Throne from Python – But Training Stays Python
Coding agents default to TypeScript, unifying full-stack dev with typing & npm—but model training remains Python. Should your team commit?
Theo - t3․ggGPT-5.6: The Overzealous Power Tool Engineering Teams Must Tame
GPT-5.6’s relentless drive to finish tasks is a double-edged sword: it completes complex work but may write too much code without guardrails.
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