· ai
The Art of Agent Prompting: Lessons from Anthropic’s AI Team
Most “prompt engineering” advice was written for single-turn chatbots — not for agents running in a loop with tools, memory, and side effects. Anthropic’s Appli...
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- · ai
Why observable AI is the missing SRE layer enterprises need for reliable LLMs
As AI systems enter production, reliability and governance can’t depend on wishful thinking. Here’s how observability turns large language models LLMshttps://ve...
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No, you can’t get your AI to ‘admit’ to being sexist, but it probably is anyway
Though LLMs might not use explicitly biased language, they may infer your demographic data and display implicit biases, researchers say....
- · ai
No, you can’t get your AI to ‘admit’ to being sexist, but it probably is
Though LLMs might not use explicitly biased language, they may infer your demographic data and display implicit biases, researchers say....
- · ai
Metric Deception: When Your Best KPIs Hide Your Worst Failures
of Green Dashboards Metrics bring order to chaos, or at least, that’s what we assume. They summarise multi-dimensional behaviour into consumable signals, clic...
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Most Developers Call AI Data With APIs and A2A
A recent Theory Ventures survey found that 91% out of 413 senior technical builders surveyed are either directly building AI, The post Most Developers Call AI D...
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How to Scale Your LLM Usage
has perhaps been the most important word when it comes to Large Language Models LLMs, with the release of ChatGPT. ChatGPT was made so successful, largely becau...
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[Paper] Video-R2: Reinforcing Consistent and Grounded Reasoning in Multimodal Language Models
Reasoning over dynamic visual content remains a central challenge for multimodal large language models. Recent thinking models generate explicit reasoning trace...
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[Paper] Video-CoM: Interactive Video Reasoning via Chain of Manipulations
Recent multimodal large language models (MLLMs) have advanced video understanding, yet most still 'think about videos' ie once a video is encoded, reasoning unf...
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[Paper] Thinking by Doing: Building Efficient World Model Reasoning in LLMs via Multi-turn Interaction
Developing robust world model reasoning is crucial for large language model (LLM) agents to plan and interact in complex environments. While multi-turn interact...
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[Paper] AnyTalker: Scaling Multi-Person Talking Video Generation with Interactivity Refinement
Recently, multi-person video generation has started to gain prominence. While a few preliminary works have explored audio-driven multi-person talking video gene...
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[Paper] ThetaEvolve: Test-time Learning on Open Problems
Recent advances in large language models (LLMs) have enabled breakthroughs in mathematical discovery, exemplified by AlphaEvolve, a closed-source system that ev...