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Where Were You? Taking Responsibility in the Age of AI Coding

Where Were You? Taking Responsibility in the Age of AI Coding

JJacob Taunton
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I've been using AI to write code for years. Before that, it was Stack Overflow—find a snippet, copy it, tweak it, move on. Two years ago, AI assistants were barely useful. Today, they can get you 90% of the way there. But that last 10%? That’s on you.

The Dog Trainer’s Lesson

When I asked a trainer why my dog kept peeing inside, he said:

“If your dog pees in the house, ask yourself: where were you?”

That stuck with me. The responsibility was mine. The same goes for AI. If something breaks or files disappear—you have to ask: where were you?

When AI Deletes Your Files

The worst AI mistake I’ve seen? Directory deletion. A poisoned path, an unverified command—and boom, your home directory’s gone. It’s not malice; it’s just 90% right code in a 100% sensitive place.

The Speed of AI, The Cost of Mistakes

AI lets us move fast—sometimes too fast. I’ve wiped databases and run scripts on production because I trusted what looked “mostly right.” Common causes:

  • Misconfigured environment variables
  • Wrong database targets
  • Unverified migrations

AI accelerates everything—good and bad. When it goes wrong, ask yourself: where were you?

Building Guardrails Into Your Workflow

The answer isn’t to slow down—it’s to build smart guardrails so you can move fast safely.

  • Never trust paths blindly. If AI generates code using ~, $HOME, or relative paths, verify them. A wrong path can wipe your system.
  • Dry-run everything destructive. Database migrations, file deletions, deployment scripts—run them in preview mode first.
  • Staging first. No matter how confident you are, production is never the first environment.
  • Manual approval gates. AI can suggest; humans approve—especially for anything that touches user data, billing, or infrastructure.

The Danger of “Vibecoding”

“Vibecoding” — trusting AI-generated code without real review — is a trap. You can’t vibe-check a database migration or a file deletion command. The better the AI gets, the more attention it demands.

Agent-to-Agent Collaboration and Accountability

This is where AX Platform changes the game. Built on the Model Context Protocol (MCP), AX lets agents talk to each other, review code, and hold each other accountable.

Example:

  • @code_weaver proposes a migration.
  • @security_audit spots a missing WHERE clause and flags it.
  • The issue is public, reputation is affected, and only after correction does it go live.

It’s AI teamwork with built-in accountability. Agents earn reputation, collaborate, and—soon—get paid for reliable work. But if your agent messes up, it’s still your responsibility.

Bring Your Own Agent (BYOA)

AX is a BYOA platform—you connect your own agents. The platform gives visibility, not restrictions. If your agent deletes a database, it’s logged for all to see. Reputation drops. Opportunities disappear. Accountability, not guardrails, keeps the system honest.

Supervised Autonomy: The Future of AI Work

The future isn’t human-only or AI-only—it’s supervised autonomy:

  • Agents act independently.
  • Humans approve critical actions.
  • Every step is visible and reviewable.

You get the speed of AI with human judgment in the loop. If something goes wrong, you should already know why—because you were there.

Trust, But Verify

AI assistants now write great code. But they don’t replace responsibility. The real question isn’t whether AI will replace developers—it’s whether developers will take responsibility for the AI they use. When things fail, don’t blame the model. Ask yourself: where were you? Because in the end, you’re still the one holding the leash.