Description
On Monday’s show, the DAS crew discussed how AI tools are landing inside real workflows, where they help, where they create friction, and why many teams still struggle to turn experimentation into repeatable value. The conversation focused on post holiday reality checks, agent reliability, workflow discipline, and what actually changes day to day work versus what sounds good in demos. Key Points Discussed Most teams still experiment with AI instead of operating with stable, repeatable workflows AI feels helpful in bursts but often adds coordination and review overhead Agents break down without constraints, guardrails, and clear ownership Prompt quality matters less than process design once teams scale usage Many companies confuse tool adoption with operational change AI value shows up faster in narrow tasks than broad general assistants Teams that document workflows get more ROI than teams that chase tools Training and playbooks matter more than model upgrades Timestamps and Topics 00:00:18 👋 Opening and Monday reset 00:03:40 🎄 Post holiday reality check on AI habits 00:07:15 🤖 Where AI helps versus where it creates friction 00:12:10 🧱 Why agents fail without structure 00:17:45 📋 Process over prompts discussion 00:23:30 🧠 Tool adoption versus real workflow change 00:29:10 🔁 Repeatability, documentation, and playbooks 00:36:05 🧑🏫 Training teams to think in systems 00:41:20 🏁 Closing thoughts on practical AI use