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Codex memory is not a promise that every conversation is saved and replayed in later sessions. The OpenAI Codex repository documents a file-based process that selects and consolidates useful information into memory files. That is different from session state, context compaction, or project instructions such as AGENTS.md. OpenCode’s reviewed documentation describes persistent instructions and on-demand skills, but not an equivalent automatic memory-consolidation workflow.
What does Codex remember between sessions?
The documented Codex repository workflow uses files to make selected information available beyond a single interaction. It separates reading memory from writing it: the read component handles developer-instruction injection, citation parsing, and read-usage telemetry classification; the write component supports prompt rendering, filesystem operations, workspace diffs, and related memory-writing tasks. The repository describes these as separate crates in its memory implementation.
The consolidation design assigns two different jobs to its memory files. memory_summary.md is a compact summary intended to be loaded into the prompt. MEMORY.md is a more detailed, searchable handbook. The consolidation template says that MEMORY.md is the durable, retrieval-oriented handbook. It directs the process to put useful, recently updated, validated information near the top and to consult rollout summaries when a task family is ambiguous, important, or duplicated and more evidence could help. These are design intentions, not a guarantee that a particular detail will be saved or retrieved every time.
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The repository’s undated templates are presented as its latest canonical runtime templates, but its main branch is mutable and the cited material does not identify a fixed release version. Implementation details may change.
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Who decides what Codex remembers?
In the documented workflow, a memory-writing and consolidation process makes selections according to its instructions. Those instructions favor useful, validated signal and guide what should be surfaced or checked for additional evidence. This is not described as a human editor deciding each item, nor does it establish complete retention of conversations or facts.
Users have a separate kind of control: they can author or edit project instruction files such as AGENTS.md. Those files guide how an agent works; they are not, by themselves, a record of prior conversations. The Codex CLI prompting guide documents how project instructions are discovered and injected. The distinction is between user-authored instructions and memory artifacts produced or consolidated by the documented memory process.
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Does Codex remember every conversation?
No such guarantee appears in the documentation described here. A consolidated memory file is selective, and its intended use is to make relevant information easier to retrieve—not to preserve every exchange as a complete transcript in active context. Nor does the documentation promise that any specific remembered detail will recur in a future session.
It helps to separate three mechanisms that can otherwise sound like the same thing:
- Session or thread state: The Agents API guide describes saved session configuration, turns, and items. It also says the managed Codex harness performs automatic context compaction. That concerns a running interaction’s state and context, not the same thing as a durable memory handbook.
- File-based memory: The Codex repository documents a read/write workflow and consolidated memory artifacts. The Agents SDK sandbox memory guide describes a separate file-based capability and explicitly distinguishes sandbox memory from conversational session history. That SDK behavior should not be generalized to every Codex product surface.
- Project instructions: Files such as
AGENTS.mdprovide guidance for work in a project. They can affect future work when discovered, but they are instructions rather than a history of past conversations.
How is Codex memory different from AGENTS.md?
They serve different purposes. Memory files are designed to distill and retrieve information from prior work. AGENTS.md supplies instructions that shape behavior in a project or scope. A project file can tell an agent how to work without recording what happened in earlier sessions; a memory file can preserve selected useful context without replacing explicit project rules.
The Codex CLI prompting guide documents instruction discovery and injection. OpenCode’s v2 instructions documentation describes global and workspace AGENTS.md files, with instructions accumulated by scope. In both cases, instructions should be understood as guidance, not proof of an automatic conversation-memory system.
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How does OpenCode memory work?
The OpenCode documentation reviewed describes two persistence mechanisms relevant to continuity: global and workspace AGENTS.md instructions, and reusable skills that are found in project or global locations and loaded on demand through the skill tool. Those mechanisms let users provide persistent guidance and make reusable workflows available when needed.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThe reviewed official OpenCode pages do not describe an automatic extraction-and-consolidation pipeline equivalent to the Codex repository’s memory read/write workflow. That is a comparison of the documented mechanisms, not proof that OpenCode cannot be extended with a plugin or a user-built workflow. The instruction and skills pages also do not establish how OpenCode persists session state, so no session-continuity comparison can be inferred from them.
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Codex and OpenCode: documented continuity mechanisms
| Mechanism | Codex documentation reviewed | OpenCode documentation reviewed |
|---|---|---|
| Persistent project guidance | AGENTS.md discovery and injection are described in the Codex CLI prompting guide. |
Global and workspace AGENTS.md files are documented, with instructions accumulated by scope. |
| Reusable skills | OpenAI documents skills for agent workflows; the core memory documentation discussed here focuses on memory files and instructions. | Skills can be discovered in project or global locations and loaded on demand through the skill tool. |
| Durable memory pipeline | The Codex repository documents dedicated read/write paths and consolidated memory files. | The reviewed instructions and skills pages do not document an equivalent automatic consolidation pipeline. They do not rule out plugins or user-built approaches. |
| Session continuity | The Agents API guide describes saved configuration, turns, and items, as well as context compaction in the managed Codex harness. | Not established by the two OpenCode pages reviewed; those pages focus on instructions and skills. |
When evaluating continuity in either tool, check the persistence scope (thread, project, or cross-run files), who authors or updates the information, how it is discovered and retrieved, whether users can inspect or edit it, and whether the documentation describes automatic extraction or consolidation.
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