Fig Guide: Features, Pricing, Models & How to Use It (SEO optimized, 2026)

#

The command line interface (CLI) has been the backbone of computing for decades, yet it remained largely untouched by the user experience revolution—until Fig arrived. Now, in 2026, Fig has evolved from a simple autocomplete tool into a comprehensive, generative AI-powered coding companion that integrates seamlessly with your terminal, IDEs, and cloud infrastructure.

This guide provides an exhaustive look at Fig in 2026 (Version 3.0+), covering its transition into a fully agentic AI tool, its pricing models, and how to leverage it for enterprise-grade productivity.

Tool Overview

#

Fig is an AI-driven assistant designed specifically for developers, DevOps engineers, and data scientists who live in the terminal. While its roots are in autocomplete, the 2026 iteration of Fig utilizes advanced Large Language Models (LLMs) to translate natural language into complex shell commands, automate scripts, and manage cloud infrastructure.

Key Features

#

1. AI-Powered Autocomplete: Fig predicts the next subcommand, flag, or file path based on context, history, and the specific package being used (e.g., Docker, Kubernetes, Git).
2. Natural Language to Shell (Fig Chat): Users can type “Undo my last git commit but keep the changes” and Fig converts this into the precise git syntax (git reset --soft HEAD~1).
3. Fig Scripts: A declarative way to build internal developer tools. Teams can share common workflows that appear automatically in the terminal autocomplete.
4. Ghost Text: Inline code generation within the terminal, similar to Copilot for IDEs, but optimized for Bash/Zsh/Fish.
5. Multimodal Error Analysis: In 2026, Fig can analyze screenshots of terminal errors or architecture diagrams to suggest remediation commands.

Technical Architecture

#

Fig operates using a hybrid architecture to ensure low latency (crucial for typing) while leveraging powerful cloud models for complex reasoning.

Internal Model Workflow

#

1. Edge Layer: A local, lightweight model (quantized 7B parameter model) runs directly on the user’s machine to handle keystroke-by-keystroke autocomplete with <10ms latency.
2. Cloud Layer: For “Ask Fig” complex queries, the request is encrypted and sent to Fig’s cloud cluster (running fine-tuned versions of Claude 3.5 Sonnet or GPT-5 equivalents optimized for shell scripting).
3. Context Engine: Fig analyzes the current shell state (directories, environment variables, previous commands) to ground the AI’s responses.

graph TD
    A[User Keystroke] -->|Input| B(Local Edge Model);
    B -->|Confidence > 90%| C[Instant Autocomplete];
    B -->|Confidence < 90% / Complex Query| D{Cloud Inference};
    D -->|Encryption| E[Fig Cloud API];
    E -->|Context + Prompt| F[LLM Core];
    F -->|Shell Script/Explanation| E;
    E -->|Response| G[Terminal UI];
    
    style A fill:#f9f,stroke:#333,stroke-width:2px
    style F fill:#bbf,stroke:#333,stroke-width:2px

Pros & Limitations

#

Installation & Setup

#

Getting started with Fig in 2026 is streamlined, but requires specific configurations for deep AI integration.

Account Setup (Free / Pro / Enterprise)

#

1. Download: Visit fig.io/download or install via package manager.
2. Authentication: Login is required to sync settings and access the AI features.
   • Note: Since the Amazon acquisition integration, you can now use your AWS Builder ID.
3. Shell Integration: Fig automatically detects your shell (Zsh, Bash, Fish) and injects the necessary sourcing script into your .zshrc or .bash_profile.

SDK / API Installation

#

For teams building custom completions (Fig Specs), you need the Fig CLI SDK.

# Install via Homebrew (macOS/Linux)
brew install fig

# Update to latest version (2026 stable build)
fig update

Sample Code Snippets

#

Creating a Custom Completion Spec (TypeScript): To add autocomplete for a proprietary internal tool called deploy-bot.

// src/deploy-bot.ts
const completionSpec: Fig.Spec = {
  name: "deploy-bot",
  description: "Internal deployment CLI for Company X",
  subcommands: [
    {
      name: "push",
      description: "Push code to staging or prod",
      options: [
        {
          name: ["-e", "--env"],
          description: "Target environment",
          args: {
            suggestions: ["staging", "production", "dr"],
          },
        },
        {
          name: "--force",
          description: "Bypass safety checks (Dangerous)",
          danger: true,
        },
      ],
    },
  ],
};

export default completionSpec;

Common Issues & Solutions

#

• Issue: Fig sidebar not appearing.
  • Solution: Check Accessibility permissions in OS settings. Run fig doctor to diagnose socket connections.
• Issue: SSH Latency.
  • Solution: Enable “Fig SSH Integration” in settings. This installs a headless Fig agent on the remote server to process autocomplete locally on the server side.

API Call Flow Diagram

#

sequenceDiagram
    participant User
    participant Terminal
    participant FigLocal
    participant FigCloud
    
    User->>Terminal: Types "git c..."
    Terminal->>FigLocal: Intercepts keystroke
    FigLocal->>FigLocal: Query Local Spec Database
    FigLocal-->>Terminal: Shows "commit, checkout, clone"
    
    User->>Terminal: Types "fig ask 'Revert last 3 commits'"
    Terminal->>FigLocal: Detects AI Intent
    FigLocal->>FigCloud: Send Prompt + Shell Context
    FigCloud->>FigCloud: LLM Processing
    FigCloud-->>Terminal: Returns "git reset --hard HEAD~3"

Practical Use Cases

#

Fig is not just for software engineers. In 2026, its utility spans across various sectors requiring technical interaction.

Education

#

Scenario: Computer Science 101. Instructors use Fig to scaffold learning. Instead of memorizing obscure tar flags, students use Fig to explore available options.

• Workflow: Student types tar - and Fig explains that -x is extract and -v is verbose.
• Benefit: Reduces “syntax anxiety” allowing focus on logic.

Enterprise

#

Scenario: Onboarding new DevOps engineers. Companies define private Fig Specs for internal CLI tools.

• Workflow: A new hire types company-cli and immediately sees all available commands, descriptions, and required arguments without reading a wiki.
• Benefit: Reduces onboarding time by 40%.

Finance

#

Scenario: Quantitative Data Fetching. Quants interact with secure databases via CLI.

• Workflow: fig ask "Fetch Q3 OHLC data for AAPL from DB_PROD and save to CSV"
• Output: Generates the complex SQL query wrapped in a Python execution command.
• Benefit: Ensures syntax accuracy prevents database locking due to malformed queries.

Healthcare

#

Scenario: HIPAA-Compliant Data Pipelines. Bioinformatics researchers processing genomic data.

• Workflow: Automating the batch processing of BAM files. Fig suggests the correct samtools flags to ensure data anonymization is preserved during piping.

Data Flow Example

#

The following table illustrates how Fig translates intent across different industries:

Prompt Library

#

Mastering Fig in 2026 requires understanding how to prompt its AI assistant (“Ask Fig”).

Text Prompts

#

These are natural language requests converted to shell commands.

1. Cleanup: “Delete all node_modules folders in subdirectories recursively.”
2. Git: “Change the author of the last 5 commits to ‘John Doe’.”
3. Networking: “Show me all active connections on port 8080.”

Code Prompts

#

Fig can generate short scripts directly in the terminal buffer.

1. Python Utility: “Write a python one-liner to start a simple HTTP server.”
2. Bash Logic: “Create a loop that renames all .jpg files to .png.”

Image / Multimodal Prompts

#

New in 2026: You can drag an image into the terminal (supported in iTerm/VS Code) and ask Fig about it.

1. Error Debugging: [User drags screenshot of stack trace] -> “Fix this Java memory leak.”
2. Infrastructure: [User drags AWS diagram] -> “Generate the Terraform CLI commands to build this VPC.”

Prompt Optimization Tips

#

• Provide Context: Instead of “Undo,” say “Undo the last git commit keeping files staged.”
• Specify Tool: “Using ffmpeg, convert this video to mp4.”
• Safety: Always append “–dry-run” when asking for deletion commands to verify before execution.

Top 10 Fig Prompts

#

Advanced Features / Pro Tips

#

Automation & Integration

#

Fig integrates deeply with workflow automation tools.

• Zapier/Webhooks: You can configure a Fig Script to trigger a Zapier webhook. For example, a command fig run notify-deploy could send a Slack message via Zapier indicating a deployment has started.
• Notion: Export terminal logs to Notion for documentation. history | fig export --to notion-page-id

Batch Generation & Workflow Pipelines

#

Fig introduced “Fig Pipelines” in late 2025. This allows chaining AI commands.

• Step 1: Analyze codebase.
• Step 2: Generate unit tests.
• Step 3: Run tests and fix errors automatically.

Custom Scripts & Plugins

#

You can write plugins using the fig-api.

// A simple plugin that congratulates you after a successful build
fig.listen('command:end', (ctx) => {
  if (ctx.command.includes('build') && ctx.exitCode === 0) {
    fig.ui.notify("Build Successful! 🚀");
  }
});

Automated Content Pipeline Diagram

#

graph LR
    A[Dev Commits Code] --> B{Fig Pre-Commit Hook};
    B -->|Lint Check| C[AI Code Review];
    C -->|Issues Found| D[Auto-Fix Suggestion];
    C -->|Clean| E[Push to Repo];
    E --> F[Trigger CI/CD];
    F --> G[Fig Notification];

Pricing & Subscription

#

As of January 2026, Fig offers a tiered pricing structure ensuring accessibility for students while catering to enterprise security needs.

Free / Pro / Enterprise Comparison Table

#

Recommendations for Teams

#

• Startups: The Pro plan is essential for sharing internal scripts (fig teams) which drastically speeds up development.
• Enterprises: The Enterprise plan is mandatory for companies requiring SSO (Okta/AD) and those who cannot send terminal data to the public cloud (utilizing Fig’s VPC peering option).

Alternatives & Comparisons

#

While Fig is a leader, the market in 2026 is competitive.

Competitor Analysis

#

1. GitHub Copilot CLI:
   • Pros: Deep integration with GitHub repositories.
   • Cons: Less visual; primarily focuses on explaining commands rather than predictive UI.
2. Warp (The Terminal):
   • Pros: A full terminal replacement (not just a plugin). Very fast rendering.
   • Cons: Vendor lock-in; you must use their terminal application, whereas Fig works in VS Code, Terminal.app, etc.
3. Amazon Q Developer (CLI):
   • Pros: Native AWS integration (deepest knowledge of AWS CLI).
   • Cons: Can be heavy; focused heavily on cloud rather than general purpose shell utilities.
4. Oh-My-Zsh (with plugins):
   • Pros: Free, open-source, massive community.
   • Cons: Configuration hell; “dumb” autocomplete (no AI context).

Feature Comparison

#

FAQ & User Feedback

#

Q1: Does Fig log my keystrokes? A: Fig processes keystrokes locally for autocomplete. For AI features, only the specific query sent to “Fig Chat” is transmitted. Enterprise plans offer zero-data-retention agreements.

Q2: Can I use Fig on Windows? A: Yes, as of 2026, Fig supports Windows via WSL2 and has a beta PowerShell integration.

Q3: Does it work offline? A: Standard autocomplete works offline. AI-driven features (Chat/Translation) require an internet connection unless you are hosting a local LLM via Fig Enterprise.

Q4: How does Fig handle secrets/API keys? A: Fig has a “Redaction Engine” that detects patterns resembling API keys or passwords and prevents them from being sent to the cloud model or saved in history.

Q5: Is Fig compatible with Vim/Neovim? A: Yes, Fig creates a headless bridge that populates Vim’s native omnicomplete.

Q6: Why is Fig slow on my machine? A: Ensure you are not running conflicting plugins (like heavy Zsh autosuggestions). Run fig doctor to check for resource bottlenecks.

Q7: Can I write my own autocomplete specs? A: Absolutely. Fig’s “scaffold” command generates a boilerplate TypeScript file for you to customize.

Q8: How does it compare to standard Zsh autosuggestions? A: Zsh suggestions are history-based (what you typed before). Fig is context-based (what the tool actually supports), making it far more accurate for tools you haven’t used often.

Q9: Can I use Fig in VS Code integrated terminal? A: Yes, this is one of the most popular use cases.

Q10: What happens if I cancel my Pro subscription? A: You revert to the Free tier. You lose access to private team specs and unlimited AI chat, but basic autocomplete remains.

References & Resources

#

• Official Documentation: fig.io/docs
• Fig GitHub Repository: github.com/withfig
• Community Discord: discord.gg/fig
• Tutorial: “Mastering Fig Scripts in 2026” - DevPro Blog
• Video: “Fig vs Warp: The Ultimate 2026 Showdown” - TechTube

Disclaimer: Features and pricing mentioned are accurate as of January 2026. Always verify the latest details on the official tool website.