Why codex /goal fails on complex workflows: compaction amnesia and context rot
The article discusses the limitations of OpenAI's `/goal` feature for complex workflows, particularly highlighting issues with context management. It identifies a problem known as context rot, which degrades the model's reasoning quality during long-horizon tasks. The author proposes a solution through an open-source utility called Nightshift, which isolates tasks to improve performance and reliability.
- ▪OpenAI's `/goal` feature struggles with context management in complex multi-issue workflows.
- ▪The concept of context rot leads to degraded reasoning quality and unreliable outputs.
- ▪The author created Nightshift, an open-source tool that isolates tasks to enhance agent performance.
Opening excerpt (first ~120 words) tap to expand
Hi HN,When Openai released `/goal` earlier this month, I was really excited to try it for long-horizon tasks. But after using it, it didn't blow me away and i did some digging and found a major architectural flaw when using it for complex multi-issue workflows: context rot.This isn't anything new, but given how openai positioned this feature to developers, i was let down by how they'd implemented context management.Though /goal is a step forward in long-horizon coding, it lacks task decomposition and proper handling of context - it uses a multi-tier approach that includes persistent context chaining (PCC) to memory, local vector embeddings for RAG, sliding windows, and compaction.In principle, giving codex a directive of `/goal work towards closing my open issues on github` should work…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.