Stop Giving AI the Steering Wheel

Source: Dev.to

A Practical Checklist for Building Controllable AI Agents

AI agents are getting better at planning, reasoning, and completing tasks.
Can I safely let this thing act on my system? In most cases, the honest answer is no.
This post is not about why AI is “bad.” It’s about building agents that are safe enough to run in production.

When an Agent Is Not Production‑Ready

If your agent does any of the following, it’s not ready for production:

• Executes real actions directly (money transfers, infrastructure changes, configuration updates, data mutation)
• Produces different outcomes for the same input
• Depends on hidden context or conversation history
• Can’t explain who approved an action
• Keeps going when inputs are unclear instead of stopping

These are not edge cases.

Layered Architecture (Think in Layers, Not Prompts)

[ AI Agent ]
     ↓
[ Structured Output ]
     ↓
[ Deterministic Decision Layer ]
     ↓
[ Human / Policy Veto ]
     ↓
[ Execution ]

AI should never skip layers.

Good vs. Bad Patterns

Structured Intent vs. Free‑Form Command

Bad

Deploy the new config to production.

Good

{
  "intent": "deploy_config",
  "risk_level": "high",
  "missing_info": ["rollback_plan"],
  "confidence": 0.72
}

Code‑Based Decision vs. Model‑Only Decision

Bad

if model_says_yes:
    deploy()

Good

if risk_level == "high" and not approved:
    block()

Deterministic Output vs. Guesswork

Bad – guessing missing values, trying another tool, “continue anyway”.

Good

status = "FAIL"
reason = "Insufficient information"

Silence or ambiguity is never permission.

Forbidden Direct Calls

Never allow the agent to invoke any of the following without explicit human oversight:

• trade()
• deploy()
• delete()
• write_prod_config()

Agents should propose actions; humans must approve high‑risk actions.

Human / Policy Veto Requirements

• Require a human approval step for high‑risk actions.
• Record who approved and when.
• Make the approval step non‑bypassable.

If no one can say “I approved this,” ask yourself:

“Can I reproduce this decision tomorrow with the same inputs?”

If the answer is no, the agent is not production‑safe. Replayability beats explainability.

Replayability Checklist

• Can I stop the agent instantly?
• Can I replay its last decision exactly?
• Can I point to the human who approved it?
• Can I prove it would do the same thing again?

If any answer is no, do not grant execution rights.

Value of Controlled Agents

Even with these restrictions, agents remain extremely valuable for:

• Semantic parsing
• Risk detection
• Workflow coordination
• Reducing human cognitive load

The future belongs to controlled agents, not fully autonomous ones. The smarter the agent, the more essential robust safeguards become.

Final Thought

Production systems don’t fail because AI is weak.
If you want your agent to survive outside demos, take away the steering wheel and install real brakes.