The gap between "I use ChatGPT" and "I've built an AI pipeline" is shrinking. Power users are combining tools in ways that weren't possible a year ago.
Custom GPTs with actions – Teams are packaging domain knowledge and API calls into GPTs for support, sales, and internal tools. Actions let the GPT query databases, create tickets, or trigger workflows.
Self-hosted RAG – Open WebUI, LocalAI, and similar tools make it feasible to run RAG over proprietary documents on your own infra. No data leaves the perimeter.
Automation with AI – Make and n8n users are adding AI nodes for classification, extraction, and generation. The pattern: trigger → AI step → conditional routing → action. End-to-end pipelines with no code.
Multi-model strategies – Local for privacy-sensitive or high-volume tasks, cloud for quality-critical work. Hybrid setups are becoming standard for cost and compliance.
The tools are there. The next step is design: clear schemas, error handling, and human-in-the-loop for anything customer-facing.
Discussion
Sign in to comment. Your account must be at least 1 day old.