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AI Workflows - Page 17
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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IBM TechnologyAgent hallucination is now an operational risk, not just an accuracy problem
Agents hallucinate less when grounded, but autonomous actions make each wrong answer more costly. Mitigation is a design task, not a model update.
AI EngineerAI agents just hacked Chrome V8: security benchmarks are broken
Frontier LLMs can now create weaponized Chrome exploits on par with elite researchers. Existing security benchmarks are broken — they measure crashes, not…
AI EngineerWhy most AI agent benchmarks are lying about 'long-horizon' capability
Most AI agent benchmarks claim 'long-horizon' capability but measure tasks with minimal state dependency. Theta Software explains why this distorts adoption…
AI EngineerThe RLHF Trap: Why AI Is Great at Chat but Terrible at
RLHF made AI great at conversation but terrible at automation. A former OpenAI researcher explains why, and what engineering leaders should do about it.
AI EngineerPost-training shifts from synthetic environments to messy production learning
Post-training is moving from synthetic environments to real production harnesses. The tradeoff: controlled RL vs. messy but realistic learning. Reward…
Google for DevelopersDexterous manipulation is the bottleneck for general-purpose robots
Google DeepMind's Gemini Robotics 2 tackles dexterous manipulation—the unsolved bottleneck for general-purpose robots. Data scarcity, hardware limits, and…
No Priors: AI, Machine Learning, Tech, & StartupsAI Generating $600M in Real-World Revenue: The Boring Vertical Playbook
Netice CEO on generating $600M in customer value through vertical AI for essential services. Most teams chase coding agents; the real revenue is in plumbing…
AI EngineerMiniMax M3 shows open-source models catching frontier labs on agentic tasks
MiniMax M3 is multimodal from scratch. Together AI handles the messy inference optimization. Here's what engineering leaders need to know about deploying…
Y CombinatorJeff Dean: Agent reliability is a systems problem, not a model problem
Jeff Dean argues agent reliability is a systems engineering problem, not a model quality one. The 1% rule for startups: pick problems where models fail…
AI EngineerAI That Optimizes Its Own Kernels: Real Progress or Hype?
Recursive AI claims their system outpaced human experts on CUDA kernel optimization. But the line between automated research and recursive self-improvement…
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