A consultant explains how he often talks clients out of building expensive AI agents when simpler, cheaper automations suffice, sharing examples from his work.
I build automations and AI agents for companies. About forty clients at this point. And the most valuable thing I do on calls now is talk people out of agents. A guy running a supplements brand came to me in March. Seven people on his team, fourteen products. He wanted an AI system that watches his inventory, figures out when to reorder, and emails his suppliers on its own. He'd seen a demo somewhere and got excited. I looked at his Shopify store. He'd been reordering the same products at the same quantities from the same suppliers for over a year. Protein powder hits 200 units, he orders more. Been doing it that way since 2023. There was nothing for AI to figure out. The decision was already made. I quoted him $5,200 for the AI build. Then I told him I could solve it for $700. I set up a simple automated workflow. Every morning it checks his inventory numbers in Shopify, compares them against his reorder points, and if anything is low it sends a pre-written order email to the right supplier. Runs itself. Costs him $60/month. No AI involved at all. He told me it felt too basic. I get that a lot. His ops person got back forty minutes every morning within the first week. He stopped caring about how boring it was after that. I'm not anti-AI though. I built an AI agent earlier this year for a property management company. Tenants text in stuff like "my sink is leaking and the hallway light has been out for a week." That's two problems in one message. The agent reads it, figures out which vendor handles plumbing and which one handles electrical, checks who's responsible based on the lease, and sends both requests out with the right priority. Handles about two hundred messages a month and saves their ops manager close to fifteen hours a week. That one needs AI because people write messy, unpredictable messages and someone has to interpret each one. You can't set a rule for that the way you can set a reorder point. The supplements guy didn't have messy input. He had fourteen products and a number. That's an alarm clock, not a brain. I've started charging more for the planning phase because the most expensive mistake I see is people spending $5k on an AI agent that does the same job as a $60/month automation. If your process follows the same steps every time with the same kind of inputs, you don't need AI. You need a workflow that runs on autopilot, and those cost a fraction of what agents cost to build and maintain.
The author argues that most founders requesting AI agents actually need straightforward automations with minimal LLM integration, citing production failures, compliance hurdles, and higher ROI from simpler workflows. The piece provides a practical decision framework to help builders and founders prioritize reliable automations over complex, unpredictable agents.
After a year of building AI agents, the author argues that businesses don't actually want autonomous agents—they want specific outcomes like reduced support tickets and manual work, and simpler, reliable solutions often deliver more value than highly autonomous systems.
A software developer questions the practical value of AI agents, expressing concerns about control, accountability, and whether manual automation combined with LLMs is more reliable than delegating to autonomous agents.
The article argues that small marketing teams prefer reliable automation that saves time over complex AI agents, emphasizing that clients value getting 3 hours of work done in 10 minutes without needing autonomous reasoning.
The author argues that the hidden cost of unreliable AI agents lies in the cognitive overhead of constant human monitoring, emphasizing that predictability and environmental stability matter more than raw intelligence for real-world deployment. Practical workflows improve significantly when agents operate within controlled, validated environments rather than unpredictable ones.