AITerm
Summary
Every terminal AI tool looks fine on a single command — the gap shows when you hand it a multi-step task and it either runs blind or stops asking for permission at the wrong moment.
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.
Bottom line: Pick AITerm if you want a macOS terminal where an agent can execute a five-step deployment and pause for your sign-off on the destructive steps — but if your team is split across Linux and Windows, or you need programmatic API access, you are building around a wall that is not going away.
Pricing Plans
Subscription- Free Tier
- CLI only; native app requires Pro
Free
CLI for command generation and diagnosis; local Ollama support
- CLI access
- Local models
- Basic error tools
Pro
Full native macOS app with tabs, splits, workspaces, runbooks, and advanced agent features
- Native app
- Tabs & splits
- Agent/autopilot modes
- Runbooks
- Additional cloud providers
View full pricing on ai-term.com →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- 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.
Cons
Sign in to edit- 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.
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About
- Platforms
- macOS
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- 2026-07-15T18:35:38.375Z
Best For
Who it's for
- macOS developers and power users who want AI assistance in the terminal
- Users prioritizing local/private AI execution
- Teams needing auditable command safety gates
What it does well
- Translating plain-English requests into safe shell commands
- Diagnosing and correcting command failures in real time
- Running multi-step tasks with per-step approval or autopilot
- Maintaining privacy with fully local AI execution on macOS
Integrations
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Frequently Asked Questions
- Is AITerm free?
- AITerm has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is AITerm open source?
- No — AITerm is a closed-source tool. Source code is not publicly available.
- Can I self-host AITerm?
- Yes. AITerm supports self-hosting on your own infrastructure.
- What platforms does AITerm support?
- AITerm is available on: macOS.
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Curated lists that include this category
Most terminal AI wrappers translate your sentence into a command and step aside. AITerm stays in the loop: it proposes an editable shell command, shows a risk label, waits for your approval, and — if the command fails — reads the error output and proposes a correction without you having to re-explain the context. The core workflow is propose → review → approve → run, at every step, including inside multi-step agent tasks. The vendor describes this as a native macOS terminal emulator with tabs, splits, and saved workspaces, not a plugin layered over an existing terminal.
The differentiating feature is the safety gate. Every command path — whether you typed it, the AI proposed it, or an agent generated it mid-task — passes through a single policy check that labels the command and writes an auditable decision log. In Autopilot (/auto) mode, the agent runs autonomously but the safety policy still blocks or pauses destructive, network, sensitive, and build/dependency steps. On a locked-down machine, the vendor states that anything classified destructive is blocked outright even in Autopilot — so the agent cannot outrun the policy.
AITerm fits macOS developers and solo power users who run frequent multi-step terminal work and want an agent that asks before it deletes something. It also fits teams with audit or compliance requirements, because the decision log gives you a record of what the AI proposed and what you approved. Where it breaks: the tool is macOS-only, there is no API, and self-hosted deployment means running the desktop app locally — not deploying a server your team shares. Teams on mixed operating systems or teams that need to embed command-generation logic into their own tooling will hit that boundary before they finish evaluating.
On the AI provider side, the free CLI supports local Ollama and standard cloud API keys (OpenAI, Anthropic, OpenRouter, Groq, Gemini, and others). Amazon Bedrock, Azure OpenAI, and subscription-based Claude and ChatGPT access via their official CLIs are paid-only features. The vendor states that cloud requests go directly to the provider with secrets redacted first — no middle server receives your prompts or credentials.