We are currently testing AI agents handling agentic ecosystem within the Tetris game. Best advice is to use your AI agents 1 game per session only, since the output tokens at this early stage are circuiting and we do not recommend more than 1 game because the possible outcome is the AI agents will hallucinate and malfunction inside mini-loops.
Agentic AI Environment — Architecture Overview
When a piece locks, the engine fires onNeedPiece. For human players, the typing zone activates. For AI agents, a word choice prompt is built with the game manual, serialized board, score, level, gravity direction, and custom instructions. The AI responds with a word whose first letter selects the piece. The harness validates the response and retries if it fails.
Once the piece spawns, the AI receives a move prompt with the current board state and active piece. Vision-capable providers (OpenAI, Anthropic, Gemini) also receive a canvas screenshot for visual assessment. The AI responds with one move until the piece locks. The harness enforces a 10s timeout and validates each move before execution.
A reliability layer wrapping every AI call. Retry: up to 3 attempts with exponential backoff. Timeout: 15s for word choice, 10s for moves. Validation: checks responses for valid words and legal moves. Fallback: if AI fails, places a T-piece or does a soft drop. The harness rejects starts with "No AI Agent" when API keys are missing.
Adjustable drop speed at 1x, 2x, or 3x. Affects piece fall rate for all players. The engine calculates dropSpeed = max(2, round((35 - (level-1)*4) / gravitySpeed)). AI agents receive the current speed multiplier in their prompts.
A KD Vibe-A-Thon Project
KrackedDevs
The Agentic Architect
Groq / Cerebras / Gemini
Llama 3.3 70B · Qwen3 · GPT-OSS
OpenAI · Anthropic · Google
Moonshot · Groq · Cerebras
Vanilla JS · Canvas API
No frameworks. Pure chaos.
Playful Geometric
Animated blobs · Noise grain · Hard shadows
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For believing in agentic chaos