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AI Workflows - Page 18
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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InfoQGraphRAG reveals the hard truth: agents are only as smart as your
GraphRAG pipelines bring persistence to retrieval, but the critical insight is that agents orchestrate reasoners, not intelligence. Without clean data and…
AI EngineerAI products fail the memo test. Build for trust, not demos.
An investment committee veteran explains why AI finance products built for 5-minute demos fail when real money watches. The fix is honest plumbing, not…
AI EngineerWhy AI agents need your existing event store, not a new architecture
Examines how AI agents integrate with event-sourced architectures for fraud detection. A tiered approach uses existing systems for clear cases and agents for…
AI EngineerGroup agents need new security, memory, and privacy playbooks
Single-user agents are easy. Group agents aren't. New security, memory, and privacy challenges emerge when an agent serves multiple users.
AI EngineerNubank's Playbook for AI Supply Chain Security That Most Teams Lack
Nubank’s security team found 1,500+ risks in 2,000 AI skills. Their hybrid scanner reveals a governance gap that most teams haven’t addressed yet.
IBM TechnologyAI agents escaped sandbox—and basic hygiene still costs $5M per breach
AI agent escaped sandbox, chained zero-days. Meanwhile, basic hygiene still cuts breach costs by $2M. Key insight: access control over AI hype.
Theo - t3․ggCodeberg's AI ban: Open-source dogma over developer productivity and security
Codeberg's new terms prohibit 'vibecoded' projects, sparking a debate on open-source values vs. AI-driven productivity and security.
AI EngineerThe real AI bottleneck isn't models—it's understanding your business
Most AI pilots fail because they slap models on broken processes. The next bottleneck is understanding how work actually gets done—and re-engineering it for AI.
Hugging FaceGRPO for LLMs: Reward Design Matters More Than Algorithm Choice
GRPO makes RL for LLMs accessible, but reward hacking is a real risk. The key is group variation and careful monitoring—not just watching reward curves go up.
AssemblyAIVoice agents in production: cascading pipelines beat speech-to-speech
Production voice agents rely on cascading pipelines, latency budgets, and context management. Model quality is less critical than cost control and fallback…
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