AITerm vs Memex

AITerm and Memex are both coding assistants tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

AITerm

AITerm threads that needle by pairing a plain-English command proposer with a per-step safety gate that labels every command green, amber, or red before anything runs. The free CLI handles command generation and /fix diagnosis; the paid native macOS app adds tabs, splits, agent modes, and runbooks. Two agent modes ship: /agent proposes each step and waits for your approval, while /auto runs unattended but pauses on anything the safety policy flags as risky or destructive. All of this runs against your own AI — local Ollama, your own API key, or your existing Claude or ChatGPT subscription — so no request touches a middle server. The ceiling appears when you need this outside macOS or want to wire it into a CI pipeline via API, because neither exists.

Memex

Orbit runs as a local harness that pulls one dependency-ordered task at a time, hands it to whichever coding agent you configure, then runs your tests, lint, and type checks before recording the result. Every run writes structured JSON artifacts — what the agent returned, how the output scored against a rubric, and a human-readable recommendation to accept, iterate, or stop. The audit trail is durable and replayable without an API key, which makes it usable in air-gapped environments. The tooling is intentionally minimal, so teams building on top of it will write their own adapter glue for agents that do not speak the expected JSON contract. Orbit does not manage the agent itself — it manages what the agent must prove.

Attribute	AITerm	Memex
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	macOS	Linux, macOS, Python 3.7+
Pros	Per-step approval on every agent action, so a five-step deployment task cannot silently delete a directory — the safety gate labels and logs each command before it runs. Fully local AI execution via Ollama or the vendor's managed Apple Silicon (MLX) engine, which means sensitive commands and credentials stay on your machine and never touch an external server. The /fix command reads actual failed output and proposes the next command in context, so you are not re-explaining the error from scratch after npm test exits 1. Runbooks let you save a multi-step sequence with fill-in variables and replay it later, so repeated deployment or setup tasks stop being a copy-paste exercise from a README. Provider-agnostic model routing — local Ollama, your own API key, or your existing Claude or ChatGPT subscription — so you are not locked to one provider when costs or rate limits shift.	Validation gates block task completion until tests, lint, and type checks pass, which means you stop shipping agent output that looks correct but breaks the build. Durable, structured artifacts written after every run — including rubric scoring and a human-readable progress log — so you have an audit trail when a stakeholder asks what the agent actually did last Tuesday. Deterministic replay with no API key required, so you can rerun any recorded orbit in a local or air-gapped environment without incurring model costs or network dependencies. Agent-neutral adapter contract, so swapping Claude for Codex behind the same task backlog produces comparable JSON artifacts instead of anecdotal impressions about which agent performed better. Dependency-aware backlog sequencing, which means the harness advances tasks in the order your project actually requires rather than letting an agent jump to a task whose prerequisites are still failing.
Cons	The tool is macOS-only with no Linux or Windows support. A team with even one developer on Linux cannot standardize on AITerm, and that team moves to a CLI-based agent tool that runs cross-platform — at which point AITerm stays on one person's machine as a personal preference, not a shared workflow. There is no API. Teams that want to embed command generation or safety-gated execution into their own internal tooling — a deployment dashboard, a Slack bot, a CI step — have no programmatic surface to call. They end up building a separate layer alongside AITerm rather than through it. Agent mode scope is a single terminal session. Multi-agent tasks where parallel agents work across different contexts — one querying a database while another edits files — are not described anywhere in the vendor documentation. Teams needing that pattern are looking at a different architecture entirely.	Agents that do not return structured JSON output require a custom adapter before Orbit can score or validate them — that wrapper is yours to write and maintain, and the docs describe it as a contribution target rather than a solved problem. There is no hosted service, no web UI, and no managed execution layer; teams that need cloud-hosted runs, a visual dashboard, or multi-user access to the artifact store will build all of that infrastructure themselves or switch to a commercial agent orchestration platform that ships those layers. The harness is intentionally small, which means complex branching logic — tasks that conditionally fan out based on what a prior agent returned — is outside what Orbit models; teams with multi-path workflows end up scripting the branching outside Orbit and using the harness only for the leaf-level validation step.

Bottom line

AITerm is paid while Memex is free; Memex is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between AITerm and Memex?

AITerm is Paid, while Memex is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AITerm better than Memex?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

AITerm vs Memex: which should I pick?

Pick AITerm if its pricing model, openness, or platform fit matches your constraints; pick Memex otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.