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AI Workflows - Page 28
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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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…
AI EngineerNetflix’s AI agent playbook: Stop fixing performance manually, build a pattern catalog
Netflix engineers built AI agents that turn profiling data into performance fixes in minutes. The key is a reusable pattern catalog that shifts optimization…
Y CombinatorBuilding on LLMs: delete your system prompt, let the model run
Claude Code's creator reveals why you should delete your system prompts and give models harder tasks. The real skill is elicitation, not prompt engineering.
David OndrejCode is dead. Long live workflow design for AI agents.
AI agents are making code cheap. The real work is now designing workflows and information systems. Forston Ball explains why local dev is dying and how to…
Theo - t3․ggKimi K3 Signals a New Era: Open-Weight Models Threaten Frontier Labs
Kimi K3 is a genuine frontier model that threatens the business logic of closed-source labs. The real signal for engineering leaders is not the model's…
Y CombinatorJensen Huang: Why NVIDIA's near-death moment built its AI dominance
NVIDIA's CEO reveals the company almost failed because their founding algorithm was wrong. The real lesson for engineering leaders: technology choices matter…
AI EngineerWhy most AI benchmarks are quietly fake and what actually matters
Data markets are in a fog of war. Most benchmarks are quietly fake. The real signal is which domain-specific workflow data labs are actually buying, not…
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