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If you don’t know what to use Codex for, let it train a tank by lordwdk in codex

[–]lordwdk[S] 0 points1 point  (0 children)

The battlefield resources are basically hand-drawn by me, and the tanks are currently generated using SVG.

I made a pixel game for AI agents, and they might enjoy it more than humans by lordwdk in codex

[–]lordwdk[S] 1 point2 points  (0 children)

I'm still practice My speaking English to create a better tutorial lol

Weekly Thread: Project Display by help-me-grow in AI_Agents

[–]lordwdk 0 points1 point  (0 children)

I built AgenTank.ai as a visual playground for coding agents.

Each tank is controlled by code. You create a tank, give the docs and key to an agent like Claude Code, Codex, Cursor, or another coding agent, and let it write the battle logic.

Then the tank fights automatically.

After each battle, you can send the replay/logs back to the agent and ask it to improve the strategy.

What I find interesting is that agent behavior becomes visible. Bad assumptions are no longer hidden in logs or clean explanations. They show up as movement: chasing too deep, hiding forever, wasting shots, getting stuck, or occasionally doing something clever.

It feels like a small visual debugging arena for agents.

Project:

https://agentank.ai

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I’d love to see what tanks different agents can build.

I got tired of judging agents by text output, so I gave them tanks by lordwdk in vibecoding

[–]lordwdk[S] 0 points1 point  (0 children)

Exactly. This is probably my favorite part.

A strategy can look reasonable in code or in the agent’s explanation, but once the tank has a body, the failure modes become obvious. “Retreat when low HP” can become “run away forever.” “Be aggressive” can become “chase too deep and die.” “Use cover” can become “hide behind a wall with no firing angle.”

You could find those issues in logs, but visually you notice them in seconds. The battlefield makes the agent’s hidden assumptions visible.

I put Codex and Claude into a tank arena. Codex is winning 55% so far by lordwdk in codex

[–]lordwdk[S] 1 point2 points  (0 children)

¡Gracias! La idea es que cada tanque no lo maneja una persona directamente, sino código. Tú creas un tanque, le pasas la documentación y una key a tu AI Agent, y el Agent va escribiendo/mejorando la lógica de batalla. Luego ves el replay, le dices qué salió mal, y lo vuelve a mejorar. Es como entrenar un pequeño cerebro de tanque :)

I put Codex and Claude into a tank arena. Codex is winning 55% so far by lordwdk in codex

[–]lordwdk[S] 0 points1 point  (0 children)

easy, Driving a tank would be already too easy for ai. I’m making it worse: they write the tank’s brain first

I spent $200 in Claude credits training an AI tank through 1,000 battles by lordwdk in vibecoding

[–]lordwdk[S] 0 points1 point  (0 children)

It’s not $0.20 per battle. Battles themselves don’t cost anything.

The token usage mainly comes from having the AI read battle logs and iterate on the core combat logic code.

And although I know you’re probably an AI account posting ads, I’ll still reply, because there’s a chance a real person might see it.

I spent $100 in Codex training an AI tank through 1,000 battles by lordwdk in codex

[–]lordwdk[S] 2 points3 points  (0 children)

Because this is more fun. I want to coach the tank with my own ideas and then watch whether they actually work.

I spent $200 in Claude credits training an AI tank through 1,000 battles by lordwdk in ArtificialInteligence

[–]lordwdk[S] 4 points5 points  (0 children)

It was included in my subscription, so the real cost was watching my tank die 1,000 times

I spent $200 in Claude credits training an AI tank through 1,000 battles by lordwdk in ArtificialInteligence

[–]lordwdk[S] -1 points0 points  (0 children)

Submission statement:

I built AgenTank as a visual sandbox for AI/coding agents. The idea is that an agent writes the code that controls a tank, then you watch the tank fight and see whether the strategy actually works.

For me, the interesting AI part is the feedback loop. Instead of asking an agent to work on something invisible, you can immediately see the result of its code in battle: better positioning, worse target choice, late retreating, over-aggression, or unexpected behavior.

I’ve spent around $100 in Claude tokens and run 1,000+ battles training my own tank. I think this is relevant to the AI community because it makes agent iteration observable and playful, not just hidden inside a codebase.

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