The development of large language models (LLMs) has been defined by the pursuit of raw scale. While increasing parameter counts into the trillions initially drove performance gains, it also introduced significant infrastructure overhead and diminishing marginal utility. The release of the Qwen 3.5 Medium Model Series signals a shift in Alibaba’s Qwen approach, prioritizing…

In the competitive arena of Multi-Agent Reinforcement Learning (MARL), progress has long been bottlenecked by human intuition. For years, researchers have manually refined algorithms like Counterfactual Regret Minimization (CFR) and Policy Space Response Oracles (PSRO), navigating a vast combinatorial space of update rules via trial-and-error. Google DeepMind research team has now shifted this paradigm…

Large context windows have dramatically increased how much information modern language models can process in a single prompt. With models capable of handling hundreds of thousands—or even millions—of tokens, it’s easy to assume that Retrieval-Augmented Generation (RAG) is no longer necessary. If you can fit an entire codebase or documentation library into the context…

For the past year, AI devs have relied on the ReAct (Reasoning + Acting) pattern—a simple loop where an LLM thinks, picks a tool, and executes. But as any software engineer who has tried to move these agents into production knows, simple loops are brittle. They hallucinate, they lose track of complex goals, and…

In the world of Generative AI, latency is the ultimate killer of immersion. Until recently, building a voice-enabled AI agent felt like assembling a Rube Goldberg machine: you’d pipe audio to a Speech-to-Text (STT) model, send the transcript to a Large Language Model (LLM), and finally shuttle text to a Text-to-Speech (TTS) engine. Each…

In this tutorial, we build an advanced Griptape-based customer support automation system that combines deterministic tooling with agentic reasoning to process real-world support tickets end-to-end. We design custom tools to sanitize sensitive information, categorize issues, assign priorities with clear SLA targets, and generate structured escalation payloads, all before involving the language model. We then…