Building a Human-Level Deep Research Agentic System using the Time Test Diffusion Algorithm

Below is a technical blueprint and conceptual framing for building a human-level, deep research, agentic system using a Time-Test Diffusion Algorithm (TTDA)—treated as a reasoning-and-verification diffusion process across time, hypotheses, and evidence. 1. Problem Framing Goal: Create an agentic system that can: Conduct multi-week–level research in hours Generate, test, revise, Read more…

Why orchestration is important: typical issues with AI agent deployment and possible fixes

Orchestration matters because AI agents are no longer single models answering prompts—they are systems of models, tools, memory, workflows, and humans that must work together reliably. Without orchestration, AI agents quickly become brittle, expensive, unsafe, or impossible to scale. Below is a structured explanation of why orchestration matters, the common Read more…

The Future of AI Agents is Event-Driven

With their capacity for autonomous problem-solving, flexible workflows, and scalability, artificial intelligence (AI) agents are poised to revolutionise business processes. However, creating better models isn’t the true challenge. In addition to having access to tools and data, agents must be able to exchange information between systems and make their outputs Read more…

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