In this video, I tested Zenflow hands-on and explained the core shift: orchestrating vs prompting. Instead of gambling with one-off prompts (and ending up in prompt hell), Zenflow anchors AI coding agents to a structured workflow where they understand requirements, generate specs, plan tasks, implement, test, and review—like a real engineering team. The big idea is simple: give agents the same foundations great teams rely on—workflow orchestration, spec-driven development, multi-agent verification, and parallel execution—so you can actually ship production-grade software. I walked through the Zenflow app UI, task types (quick change, fix a bug, planning-first, and full spec-driven development), and model settings (including using different models and even connecting MCP servers like Playwright for automation). Then I demoed a full SDD workflow by building a “News in a Glance” React + Vite app from a PRD. My favorite part: I had another model review the generated spec inside the workflow, caught API format issues early, and corrected the spec before coding—saving a ton of downstream bug-fixing. Finally, I ran the project locally, validated the output, and pointed out how incremental improvements (dark theme, missing images) map naturally to Zenflow’s task types.