Browsing: Implementation

OpenAI has released Symphony, an open-source framework designed to manage autonomous AI coding agents through structured ‘implementation runs.’ The project provides…

Time series data drives forecasting in finance, retail, healthcare, and energy. Unlike typical machine learning problems, it must preserve chronological order. Ignoring this structure leads to…

def executor_agent(step: Dict[str, Any], context: Dict[str, Any]) -> StepResult: step_id = int(step.get(“id”, 0)) title = step.get(“title”, f”Step {step_id}”) tool = step.get(“tool”, “llm”) ctx_compact = { “goal”:…

In this tutorial, we implement an end-to-end Practical Byzantine Fault Tolerance (PBFT) simulator using asyncio. We model a realistic distributed network with asynchronous message passing, configurable…

In this tutorial, we build a production-ready agentic workflow that prioritizes reliability over best-effort generation by enforcing strict, typed outputs at every step. We use PydanticAI…

In this tutorial, we build a fully stateful personal tutor agent that moves beyond short-lived chat interactions and learns continuously over time. We design the system…

Today, we are publishing a new open source sample chatbot that shows how to use feedback from Automated Reasoning checks to iterate on the generated content,…

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We…

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment,…

In this tutorial, we walk through an end-to-end, advanced workflow for knowledge graph embeddings using PyKEEN, actively exploring how modern embedding models are trained, evaluated, optimized,…