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Pi 1.0 (Earendil) is a terminal-based AI agent harness released by Earendil on October 1, 2026. It serves as a minimal, extensible platform through which users can run AI agents that combine reasoning, tool invocation, and model switching. Its purpose is to help business professionals automate workflows, execute code or scripts, process do***ents, generate images, and chain tasks—all through a unified interface that allows customization and integration with multiple LLM providers. Pi 1.0 targets those who want agentic, programmable AI workflows with fine-grained control over tooling and behavior.
Key Features
Agent Harness & Codemode: Pi 1.0 delivers an agent harness that supports codemode—a mode in which the AI model writes JavaScript code to invoke tools from a sandbox environment rather than operating in a simplistic prompt-reply loop. The codemode implementation is leaner in version 1.0, reducing prompt size for certain tasks. It also supports image generation through the
models.generateImages()API.Deferred Tool Loading & Virtual Models: New in Pi 1.0 is support for deferred loading of tools (tools are only loaded when needed), and virtual model extensions which allow users to compose or wrap multiple models or behaviors into custom “virtual models.”
Cache Warming & Mid-Conversation Changes: To improve performance, Pi 1.0 adds cache warming for certain models (for example, those from Anthropic), as well as support for modifying system instructions or tool sets mid-conversation—allowing agents to adapt their policies or tool capabilities over time.
Minimalism & Extensibility: Pi is open-source under the MIT license. It is designed to be lightweight, malleable, and customizable. Developers can build extensions, define agents with profiles, define tools, manage providers, set thinking levels, and integrate many model backends. Pi also includes a companion experimental package called “Pi Durable” for long-running agentic applications with durable state and multi-surface interaction.
Pricing
Pi itself is open-source under an MIT license, meaning the core agent harness is free to use and can be extended or deployed commercially without paying just for the MIT-licensed software. Token usage and costs arise from the model providers you connect: OpenAI, Claude, Radius, DeepSeek, etc. Different models have different pricing per input token, output token, cache read, and cache write. For example, the Radius provider’s “Balanced” model is priced at approximately 3 USD per million input tokens, 15 USD per million output tokens, 0.30 USD per million cache-read tokens, and zero for cache writes. There are no fixed monthly subscription tiers published for Pi 1.0 itself; instead, costs are usage based, dependent on which model provider and model you employ, how many tokens you consume, and how much tool or cl***ifier invocation happens. If you use Pi with local models, or your own hardware, provider costs may be minimal or limited to infrastructure.
Who is it for?
Pi 1.0 is well suited for developers, engineers, data teams, and technical decision-makers who want to automate workflows or embed intelligent agents into business processes. It is especially appropriate when:
You need custom tooling or scripting—for example, automatically generating reports, transforming data, or executing code based on do***ent contents.
You have multi-step agentic workflows requiring multiple model providers, selective tool usage, or dynamic model switching (e.g. planning in one model, execution in another).
You prefer open-source, self-hosted or extendable systems rather than closed, SaaS-only agents, and want control over what tools, providers, or models are used.
Your workload involves bursty usage or project-based usage where token-based billing (pay-as-you-go) is more flexible than fixed subscriptions.
Pi 1.0 might be less suitable for users who prefer low-latency, turn-key AI ***istants without configuration, or those who are less comfortable managing tool definitions, model credentials, or extensions.
Final thoughts
Pi 1.0 marks a significant maturity milestone for Earendil’s agent harness technology: stable, hardened, and built with a user-first approach to extensibility and performance. It strikes a balance between power and minimal complexity, especially for businesses that need programmable agents rather than opaque ***istants. For any organization with developer capacity and a need for flexible AI agents, Pi 1.0 offers strong value. The payoff is highest when you carefully choose your model providers, optimize tool usage, and manage token costs, since pricing is usage-based rather than subscription based.
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