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AI Workflows - Page 3
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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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…
IBM TechnologyAI fluency creates an interpretation bottleneck that STEM alone can't solve
AI can speak fluently without understanding meaning. The humanities—epistemology, rhetoric, ethics—become operational skills for engineering teams building…
AI EngineerHow SonderMind built safe AI coach: modular guardrails, clinical evals
SonderMind's approach to mental health AI: separate guardrail LLMs, clinician-defined evals from real conversations, and a design philosophy that favors…
AI EngineerEdge AI's dirty secret: DRAM cost, not model quality, is the bottleneck
For consumer robots and IoT, the bottleneck isn't model capability—it's DRAM cost. Google's lead engineer shows why fine-tuning tiny models on synthetic data…
Y CombinatorAI has killed the pure software moat—hard problems are your only defense
YC partners argue pure software is now a commodity. The real moat? A hard problem—hardware, regulation, or distribution. Engineering leaders must reassess…
Theo - t3․ggOpus 5: The first practical default model for AI-assisted coding
Opus 5 offers a compelling middle ground between capable and cheap coding. Real savings are 20-25%, not 50%. Teams should test it as a daily driver before…
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