Show HN: Codex context bloat? 87% avg reduction on SWE-bench Verified traces (www.npmjs.com)

A new tool called **pando-proxy** has been announced, designed to enhance interactions with OpenAI's Codex by reducing memory bloat during long sessions. This local wrapper acts as a proxy, which maintains a compact working memory, allowing multi-turn Codex sessions to stay within context limits without the need to replay the entire conversation history. Early benchmarks indicate an impressive average reduction in prompt size of up to 87%, which is significant for the AI/ML community as it improves efficiency and response times in applications utilizing Codex for software development tasks. The technical implications of pando-proxy include its ability to dynamically manage retained context through a structured memory system, which focuses solely on essential information while aggressively pruning unnecessary data. This tool enables developers to engage in lengthy Codex sessions more efficiently by minimizing resource drains associated with context bloat. Overall, pando-proxy not only enhances user experience, but it also paves the way for more scalable AI applications in programming and other interactive environments, making it a noteworthy advancement in the field of AI/ML.