Practical ideas for working with agents, explanations of memory, and notes from building Space.
Mem0 is a memory layer that developers call from code. Its alternatives split by job: temporal graphs, agents that edit their own memory, local MCP servers, files your tools already read, and shared workspaces for the AI tools a team already uses. Pick the job first, then test two options.
Read articleYour people use different AI tools, and each one reads its own instructions. A skill can carry one way of working into all of them, once you know where each tool looks and how the copies stay in step.
Read articleA Codex skill is a folder with a SKILL.md file that teaches Codex one workflow. Writing one takes minutes; the parts that decide whether it helps are the description, the folder Codex reads it from, and how the rest of your team gets the current copy.
Read articleThe MCP connection is standardized. What a memory server stores, returns and keeps as evidence is not. Here is how to judge one in an afternoon, with a test you can repeat.
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Claude memory means two different things. In the Claude apps it is an account feature that saves topics from your chats; in Claude Code it is Markdown files on your computer, some you write and some Claude writes. Knowing which one owns a fact, and where each stops, makes both easier to trust and to check.
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Codex can carry context in several ways that are easy to confuse. Separating instruction files, generated local memories, and external workspaces makes each one easier to choose and to check.
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An agent can work across a business without carrying every project's assumptions into every task. Here is where workspaces, skills, and Space each help.
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Two saved memories can belong together without saying the same thing. Here is how I use Jev to judge those connections in Space, without comparing every memory with every other memory.
Read articleFrom our benchmark
Median evidence-assessment time
81 reused synthetic cases · separate runs
We tested Jev against GPT-5.6 Luna, then used it to organize memory in Space. Here are the measured speed gains, cost trade-offs, errors, and limits.
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An agent can revise its instructions without retraining its model. Hermes and Prime Agent show how the software around a model can retain useful lessons, organize work, and make improvement measurable.
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An agent can use a saved fact in a later session without being retrained. Understanding that distinction makes memory systems easier to build, evaluate, and trust.
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The next session needs enough context to make a good decision. Here is a small, explicit handoff you can use with a document today.
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Remembering a decision is only part of the job. You also need to know who said it, what it meant, and whether it still applies.
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Our first real client check covered ten MCP calls and work we could inspect in the website. Here is what happened and what that establishes.
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