The article compares OpenAI’s Codex “Oracle” approach—using server-side compaction to maintain a single coherent thread—with Anthropic’s Claude “Firm” method of delegating tasks to multiple sub-agents. It breaks down trade-offs in cost, speed, coherence, and memory loss, and predicts a future hybrid of both strategies.

• OpenAI's Codex keeps one continuous thread alive via server-side compaction (auto-summarizing/filtering tool calls) to preserve coherence across huge token counts, but this serializes work through a single channel.
• Anthropic's Claude delegates subtasks to parallel sub-agents that report back to a parent thread, yielding faster visible output but risking duplicated searches and dropped facts when sub-agents fail to forward key details.
• Claude's approach costs more and risks inconsistency from repeated operations, while Codex's compaction reduces "forgetting" at the cost of speed since work happens serially.
• Both companies are expected to converge toward hybrids—OpenAI adding agent-style delegation, Anthropic tightening compression—to balance coherence, speed, and cost.