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How to Design a Gemini-Powered Self-Correcting Multi-Agent AI System with Semantic Routing, Symbolic Guardrails, and Reflexive Orchestration

agentic ai, AI Agents, Artificial Intelligence, Editors Pick, Tutorials, Uncategorized

In this tutorial, we explore how we design and run a full agentic AI orchestration pipeline powered by semantic routing, symbolic guardrails, and self-correction loops using Gemini. We walk through how we structure agents, dispatch tasks, enforce constraints, and refine outputs using a clean, modular architecture. As we progress through each snippet, we see how […]

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A Coding Guide to Build a Procedural Memory Agent That Learns, Stores, Retrieves, and Reuses Skills as Neural Modules Over Time

agentic ai, AI Agents, Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we explore how an intelligent agent can gradually form procedural memory by learning reusable skills directly from its interactions with an environment. We design a minimal yet powerful framework in which skills behave like neural modules: they store action sequences, carry contextual embeddings, and are retrieved by similarity when a new situation

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A Coding Implementation of a Complete Hierarchical Bayesian Regression Workflow in NumPyro Using JAX-Powered Inference and Posterior Predictive Analysis

Artificial Intelligence, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we explore hierarchical Bayesian regression with NumPyro and walk through the entire workflow in a structured manner. We start by generating synthetic data, then we define a probabilistic model that captures both global patterns and group-level variations. Through each snippet, we set up inference using NUTS, analyze posterior distributions, and perform posterior

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How to Build an Adaptive Meta-Reasoning Agent That Dynamically Chooses Between Fast, Deep, and Tool-Based Thinking Strategies

agentic ai, AI Agents, Artificial Intelligence, Editors Pick, Staff, Tutorials

We begin this tutorial by building a meta-reasoning agent that decides how to think before it thinks. Instead of applying the same reasoning process for every query, we design a system that evaluates complexity, chooses between fast heuristics, deep chain-of-thought reasoning, or tool-based computation, and then adapts its behaviour in real time. By examining each

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How to Design a Fully Local Multi-Agent Orchestration System Using TinyLlama for Intelligent Task Decomposition and Autonomous Collaboration

agentic ai, Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we explore how we can orchestrate a team of specialized AI agents locally using an efficient manager-agent architecture powered by TinyLlama. We walk through how we build structured task decomposition, inter-agent collaboration, and autonomous reasoning loops without relying on any external APIs. By running everything directly through the transformers library, we create

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How to Build a Meta-Cognitive AI Agent That Dynamically Adjusts Its Own Reasoning Depth for Efficient Problem Solving

agentic ai, AI Agents, Artificial Intelligence, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we build an advanced meta-cognitive control agent that learns how to regulate its own depth of thinking. We treat reasoning as a spectrum, ranging from fast heuristics to deep chain-of-thought to precise tool-like solving, and we train a neural meta-controller to decide which mode to use for each task. By optimizing the

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How We Learn Step-Level Rewards from Preferences to Solve Sparse-Reward Environments Using Online Process Reward Learning

Artificial Intelligence, Editors Pick, Reinforcement Learning, Technology, Tutorials

In this tutorial, we explore Online Process Reward Learning (OPRL) and demonstrate how we can learn dense, step-level reward signals from trajectory preferences to solve sparse-reward reinforcement learning tasks. We walk through each component, from the maze environment and reward-model network to preference generation, training loops, and evaluation, while observing how the agent gradually improves

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How to Design an Advanced Multi-Page Interactive Analytics Dashboard with Dynamic Filtering, Live KPIs, and Rich Visual Exploration Using Panel

Artificial Intelligence, Data Science, Editors Pick, Python, Staff, Tech News, Technology, Tutorials

In this tutorial, we build an advanced multi-page interactive dashboard using Panel. Through each component of implementation, we explore how to generate synthetic data, apply rich filters, visualize dynamic time-series trends, compare segments and regions, and even simulate live KPI updates. We design the system step by step so we can truly understand how each

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A Coding Guide to Design an Agentic AI System Using a Control-Plane Architecture for Safe, Modular, and Scalable Tool-Driven Reasoning Workflows

agentic ai, Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we build an advanced Agentic AI using the control-plane design pattern, and we walk through each component step by step as we implement it. We treat the control plane as the central orchestrator that coordinates tools, manages safety rules, and structures the reasoning loop. Also, we set up a miniature retrieval system,

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A Coding Implementation for an Agentic AI Framework that Performs Literature Analysis, Hypothesis Generation, Experimental Planning, Simulation, and Scientific Reporting

agentic ai, AI Agents, Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we build a complete scientific discovery agent step by step and experience how each component works together to form a coherent research workflow. We begin by loading our literature corpus, constructing retrieval and LLM modules, and then assembling agents that search papers, generate hypotheses, design experiments, and produce structured reports. Through snippets

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