
Every engineer knows the pain of being paged at 3 AM for a production incident. Usually, it takes 40 minutes just to read through logs, understand the state of the system, and find the root cause, followed by 5 minutes to actually write the fix. AXIOM does the 40 minutes for you, so you only have to do the 5. We built AXIOM because current AI coding assistants only suggest fixes based on snippets. When production breaks, the bottleneck is context. You need to load massive amounts of codebase context, real-time metrics, and log histories simultaneously. Standard GPUs suffer from memory swapping and KV cache bottlenecks when trying to process this much context, leading to fragmented reasoning. By running Qwen2.5-72B on the AMD Instinct™ MI300X, we unlocked the ability to use the massive 192GB of VRAM to maintain full system context without truncation. AXIOM operates on a high-speed OODA Loop (Observe, Orient, Decide, Act) using the new Model Context Protocol (MCP). It observes telemetry via an MCP LogDB server, orients itself using the massive context window to form a hypothesis, and acts by executing live terminal diagnostics and pushing code fixes. Crucially, before any destructive action (like modifying code or opening a PR), it pauses at a Human-in-the-Loop safety gate for approval. To prove it works, AXIOM generates a "War Room Packet" for every incident—a structured audit trail of its evidence chain, hypothesis progression, and before-and-after metrics recovery. We benchmarked it against industry DORA metrics, and AXIOM consistently turns a cascading failure alert into a verified GitHub Pull Request in under 90 seconds.
10 May 2026