Aside vs Pi Coding Agent: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Aside and Pi Coding Agent — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Aside
Aside Computer Inc.
A Chromium desktop browser with a built-in agent that signs in and completes real work across your logged-in sites.
Key features
- Agentic Browsing: The agent operates your logged-in websites directly - clicking, typing and navigating - so tasks that need no public API still get done.
- Local Memory: Browsing history is distilled into on-device memory files so the agent already knows which tools and accounts a recurring task involves.
- Agent Password Manager: Credentials are autofilled into pages through hardware-backed encryption and Secure Enclave storage, never handed to the model.
- Human Approval Gates: Sensitive steps such as payments, posts and outbound messages pause for your confirmation before the agent proceeds.
- Access Audit Log: Every credential use and scoped permission grant is recorded so you can see exactly what the agent touched and when.
- Routines: Scheduled recurring tasks, such as a 9am daily briefing, run on their own and drop results back into the browser.
- Bring Your Own Model: Connect an existing ChatGPT or Claude subscription or your own API key rather than paying twice for inference.
- Sandboxed Execution: Filesystem and network access are isolated with guardrails so agent runs cannot reach beyond what the task needs.
Best for
- Operations Backfill: Push the same record update through several internal dashboards that have no shared API.
- Recruiting Prep: Reopen a candidate profile viewed yesterday and assemble interview notes from the sites already visited.
- Inbox and Comment Triage: Draft replies, follow-ups and comment responses across email and social accounts under review.
- Daily Briefing: Schedule a routine that gathers overnight metrics and trending topics into one morning summary.
- Sales Research: Work through prospect sites and CRM screens to collect context before an outreach sequence.
- Spreadsheet and Document Work: Have the agent edit local files and web spreadsheets as part of a longer task.
Pi Coding Agent
Earendil Works (earendil-works)
A terminal-based, extensible TypeScript coding agent and toolkit for building agentic developer workflows.
Key features
- Unified LLM Providers: Abstracts communication with multiple LLM providers and supports provider authentication via /login or environment variables (e.g., ANTHROPIC_API_KEY), letting the agent switch between hosted and local models.
- Built-in Coding Tools: Ships a production-ready set of built-in tools for file operations, search (grep/find), shell execution (bash), read/write/edit, and sharing code/snippets to streamline common developer tasks inside the agent loop.
- Session Persistence & Compaction: Persists full session history to JSONL files and performs automatic in-memory compaction (summarization) when context approaches model window limits while preserving full logs on disk.
- TypeScript Extensibility: Extension system and resource loader for adding custom TypeScript extensions, skills, prompt templates, themes, and pi packages to extend agent capabilities and add custom tools.
- Programmatic SDK: Exposes programmatic APIs (createAgentSession, createAgentSessionRuntime, InteractiveMode, SessionManager) to embed agent sessions into other tooling or CI environments.
- Terminal UI & Editor Integration: Provides a terminal UI (pi-tui) and an Emacs frontend with keybindings, syntax highlighting, and navigation designed for interactive coding workflows.
- Security & Containerization Guidance: Explicitly documents permission model (runs with user/process permissions) and offers recommended containerization/sandbox patterns for stronger isolation in production or CI.
- Unified LLM provider layer (pi-ai) abstracting multiple model providers and authentication (supports API keys and /login flows)
- Agent orchestration loop (pi-agent-core) enabling tool calling and turn management
- Production-ready coding agent runtime (pi-coding-agent) with built-in tools (file ops, shell commands, read/write/edit/grep/find/ls, etc.)
- Programmatic SDK: createAgentSession, createAgentSessionRuntime, createAgentSessionServices, InteractiveMode, SessionManager and factory hooks
- Terminal UI (pi-tui) and CLI entrypoint (pi) for interactive sessions
- Session persistence to JSONL + automatic context compaction to manage long histories and model context windows
- Extensibility via TypeScript extensions, custom tools, skills, prompts, themes, and resource loaders (DefaultResourceLoader)
- Integrations: Emacs frontend, GitHub Action for running Pi in CI/CD, examples and extension patterns in repo
- Security / deployment guidance: no built-in permission sandboxing (runs with user permissions) — recommends containerization/sandboxing patterns
- Supply-chain hardening practices for npm (save-exact, lockfile policies, audit commands) and release tooling
Best for
- Interactive Terminal Pair-Programming: Use Pi in a project directory to iteratively write, refactor, and test code using built-in file and shell tools without leaving the terminal.
- Custom Agent Frameworks: Build bespoke agent behaviors and pipelines by composing pi-agent-core, adding custom tools or skills, and orchestrating multi-agent workflows (e.g., planner/builder/reviewer chains).
- CI/CD Automation: Run Pi inside CI (via community GitHub Actions) to automate code generation, PR descriptions, or repository maintenance tasks as part of build pipelines.
- Local Model & Hybrid Deployment: Connect Pi to local LLMs (Ollama, vLLM, etc.) or hosted providers, enabling offline or hybrid workflows for sensitive code or data while following containerization recommendations.
- Embedding in Editors and Integrations: Integrate Pi with Emacs or other editor workflows to provide chat-driven code navigation, edits, and file exploration from within the editor.
- Open Source Session Sharing & Research: Share anonymized OSS agent sessions to improve agent tooling and model behavior by contributing real-world agent interactions and failure/fix examples.
- Interactive terminal coding assistance and REPL-style development sessions
- Automating repository tasks and review workflows in CI/CD using the pi GitHub Action
- Embedding a coding assistant into developer tools or interfaces (e.g., Emacs integration)
- Building custom agentic workflows and tools that combine shell, file, and API operations
- Running local or remote LLM-backed coding agents (supports local LLM configuration and provider fallbacks)
- Prototyping or shipping production agent systems with session persistence and context compaction