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Engineering Leadership - Page 32
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 SpaceThe Agent OS and the End of CDC
Databricks open-sourced Omnigen for agent governance and LTAP to eliminate ETL, but production readiness is still unproven.
The Pragmatic EngineerAI Didn't Kill Coding Interviews—It Exposed What Actually Matters
NeetCode says coding interviews persist because they measure thinking, not syntax—the real risk is engineers losing the ability to reason without AI.
IBM TechnologySocial Engineering Won’t End; It’s Shifting to Your Agents
Social engineering won’t stop; it’ll target AI agents instead of people. The threat surface is moving, and your IAM isn't ready.
InfoQStop Prompt Hacking: Architect for Deterministic AI Agents
Prompt engineering won’t make AI agents reliable. Build a skill store: codify successful outputs as deterministic code to skip reasoning for known problems.
InfoQDurable Agents Need Workflow Engines, Not Whole-Loop Sandboxes
Separating agent reasoning from tool execution in a durable workflow engine prevents state loss, eliminates idle waits, and provides an audit trail.
InfoQContext Bloat Will Drain Your AI Budget—Fix It with Just-in-Time Tools
Unused MCP servers silently multiply token costs by 175x. Gateways and registries enable just-in-time tool delivery—but real-world proof is absent.
InfoQAI’s Real Bottleneck: Context, Not Compute
CAST’s graph halved token use and doubled accuracy, letting a team cut a mainframe modernization from 7.5 years to 3.
The Pragmatic EngineerSlow Down Your AI Coding Before It Breaks Your Engineering Culture
Meta’s AI-written, AI-reviewed code caused a security disaster. The lesson: without human oversight, AI coding tools destroy trust and reliability.
GOTO ConferencesYour Architecture Process Is the Bottleneck
Decentralizing architecture decisions with advice processes and ADRs removes bottlenecks, but demands trust and a cultural shift away from gatekeeping.
Machine Learning Street TalkThe Real AlphaFold Lesson: Kill Your Darlings, Not Just Scale
AlphaFold 2's 30-point leap came from ruthless ablation, not SE(3) equivariance. The 100x efficiency gain is a wake-up call for scale-obsessed teams.
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