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AI Workflows - Page 13
How engineering teams turn AI tools into repeatable work. Curated tldw.news briefings about ai workflows, with practical engineering takeaways from long-form AI and developer-tool videos.
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AI EngineerAgents Become Reportees: The Next Engineering Management Shift
Codex agents are becoming managers, pushing engineers to oversee loops instead of terminals. Attention is now the key constraint.
David OndrejToken Billionaires Fail Without Taste
Token-hungry AI agents are everywhere, but the best engineers rely on loop design, guardrails, data structures, and manual testing—taste still matters.
No Priors: AI, Machine Learning, Tech, & StartupsMoats Are Dead: AI Cuts Costs But Won’t Protect You
Booking’s AI is cutting costs, but its CEO warns there’s no moat. The real challenge? Proving ROI before scaling—and retraining teams before they’re displaced.
Cole MedinThe Personal Agent Trap: Why Markdown Wikis Don’t Scale
Personal AI agents don't scale. Production forces a shift from markdown wikis to database-backed context retrieval and memory. What that means for your team.
OpenAIVoice AI’s Full-Duplex Shift: Smarter, but Still Scripted
OpenAI's GPT Live 1 introduces full-duplex voice and reasoning delegation, erasing turn boundaries but leaving cost and readiness questions open.
AI EngineerWhen Startups Become Side Projects, What’s Left to Build Big?
AI orchestration collapses project tiers: startup scope becomes a side project, and “too big” vanishes. Small teams can now build AWS-like breadth.
AWS DevelopersAgent Hooks: The Middleware Your AI Workflows Are Missing
Hooks bring middleware-like control to AI agents, enabling approval gates and rate limiting. Essential for teams moving agents to production.
AWS DevelopersTool Protocol Temptation: MCP’s Hidden Context and Security Costs
MCP’s promise of standardized agent-tool integration hides a context-bloat and security tradeoff. Filtering tools becomes a critical harness design lever.
AWS DevelopersThe Real Work in AI Agents: Building the Harness, Not the Model
AI agents aren’t just models—they rely on a harness for tools, context, and guardrails. This is where engineering leaders need to focus.
The Pragmatic EngineerThe AI Hiring Caste System Is Already Here
AI is already creating a hiring caste system. Leaders must evaluate how engineers reason with AI, not just code, before the gap widens.
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