A research request first becomes a ResearchPlan that requires human approval. External documents must be fetched in full, and verbatim quotes must be verified before they can enter a report. Quant review is always append-only, and free-text feedback never flows back into a prompt. This is the complete M5 Copilot loop.
n8n is automation-first: a webhook, schedule, or application event starts a workflow, then an AI Agent may choose tools inside it; production still requires deliberate memory, approvals, credentials, execution data, and scaling architecture.
AI Product Design is the hottest new interview topic in 2025-2026. Core areas: when to use AI (not every problem needs it), human-in-the-loop design patterns (when to let humans intervene), trust building (how to make users believe AI output), AI product challenges (hallucination, latency, cost), and AI product evaluation metrics.
Not everyone should use a coding agent to modify code directly. AI Native teams need interface specs, test-first development, monorepo, security guardrails, human-in-the-loop, and token budget controls. Building an agent platform layer on top of coding agents and clearly redefining developer roles is the right path forward.