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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 hop […]
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 use
In this tutorial, we focus on building a transparent and measurable evaluation pipeline for large language model applications using TruLens. Rather than treating LLMs as black boxes, we instrument each stage of an application so that inputs, intermediate steps, and outputs are captured as structured traces. We then attach feedback functions that quantitatively evaluate model
ByteDance Seed recently dropped a research that might change how we build reasoning AI. For years, devs and AI researchers have struggled to ‘cold-start’ Large Language Models (LLMs) into Long Chain-of-Thought (Long CoT) models. Most models lose their way or fail to transfer patterns during multi-step reasoning. The ByteDance team discovered the problem: we have
For the last few years, the AI world has followed a simple rule: if you want a Large Language Model (LLM) to solve a harder problem, make its Chain-of-Thought (CoT) longer. But new research from the University of Virginia and Google proves that ‘thinking long’ is not the same as ‘thinking hard’. The research team
In this tutorial, we build a production-style Route Optimizer Agent for a logistics dispatch center using the latest LangChain agent APIs. We design a tool-driven workflow in which the agent reliably computes distances, ETAs, and optimal routes rather than guessing, and we enforce structured outputs to make the results directly usable in downstream systems. We
The balance of power in the digital age is shifting. While governments and large corporations have long used data to track individuals, a new open-source project called OpenPlanter is giving that power back to the public. Created by a developer ‘Shin Megami Boson‘, OpenPlanter is a recursive-language-model investigation agent. Its goal is simple: help you
In this tutorial, we design a practical image-generation workflow using the Diffusers library. We start by stabilizing the environment, then generate high-quality images from text prompts using Stable Diffusion with an optimized scheduler. We accelerate inference with a LoRA-based latent consistency approach, guide composition with ControlNet under edge conditioning, and finally perform localized edits via
In this tutorial, we build a “Swiss Army Knife” research agent that goes far beyond simple chat interactions and actively solves multi-step research problems end-to-end. We combine a tool-using agent architecture with live web search, local PDF ingestion, vision-based chart analysis, and automated report generation to demonstrate how modern agents can reason, verify, and produce
Building simulators for robots has been a long term challenge. Traditional engines require manual coding of physics and perfect 3D models. NVIDIA is changing this with DreamDojo, a fully open-source, generalizable robot world model. Instead of using a physics engine, DreamDojo ‘dreams’ the results of robot actions directly in pixels. https://arxiv.org/pdf/2602.06949 Scaling Robotics with 44k+
