By Austen Jones, York Apps · Published 2 July 2026 · Last updated 8 July 2026 When building an AI agent architecture, you’ll face decisions that tutorials rarely cover. Choose a single agent for narrow tasks and an orchestrator when you need parallel workloads or specialised sub-agents. Apply least privilege to every tool, validate structured…
By Austen Jones, York Apps · Published 2 July 2026 · Last updated 8 July 2026 When a single AI agent hits its context window limits, compounds errors, or stalls on parallel workloads, you’ve reached a structural ceiling that better prompting won’t fix. Multi-agent systems solve this by splitting work between an orchestrator and specialised…
By Austen Jones, York Apps · Published 6 May 2026 · Last updated 8 July 2026 Agentic AI isn’t just answering your questions — it’s completing your work. Unlike traditional AI that waits for prompts, agentic AI autonomously plans and executes multi-step tasks, adapts to obstacles, and coordinates across tools and data sources without constant…
By Austen Jones, York Apps · Published 6 May 2026 · Last updated 8 July 2026 An AI agent is software that perceives information, makes decisions, and takes action on your behalf — without you triggering every step. Unlike a chatbot following a fixed script, it reasons through variables, executes multi-step tasks, and learns from…
By Austen Jones, York Apps · Published 6 May 2026 · Last updated 8 July 2026 AI agents aren’t overhyped in theory, but they are in practice. You’ll find the gap between a polished demo and a stable deployment is massive, and it’s mostly a data infrastructure problem. Vendors promise seamless automation, but you’re usually…