**Prime Agent** is Prime Intellect's open-source coding and research agent, built for long-running autonomous work rather than single-session chat. It is organized around two abstractions the project treats as load-bearing: the **Recursive Language Model (RLM)**, which turns context into variables and tools into function calls inside a persistent REPL, and the **Continual Harness**, which keeps supplemental prompts, memories, skill descriptions, and subagent specifications as durable state the agent can revise. The defining architectural choice is that **everything is programmatic**. A persistent IPython kernel is the built-in model tool, so file operations, shell commands, tool use, subagent spawning, and context management all happen as Python code rather than as separate hard-coded tool schemas. Subagents are a first-class primitive: calling `rlm(...)` spawns a real child agent for parallel or background work and returns its result programmatically, which lets an agent fan out and collect results without routing every step through the user. Self-improvement is scoped deliberately narrowly. The `/refine` command reviews the current trajectory and applies small, evidence-backed updates to supplemental harness state — it never rewrites the immutable base system prompt, and recorded snapshots support rollback. Refinements are local to the session by default. Skills are importable Python packages rather than prose files, and a built-in skill creator converts recurring workflows into project or personal skills. Continuity is the other half of the design. Daemon-backed sessions keep IPython state, schedules, and subagents alive when the terminal disconnects, and can be reattached later via `prime-agent attach`. Heartbeats, `prime-agent schedule`, persistent `/goal` objectives, automatic compaction, and a bounded `/autonomous` mode with turn, token, and time budgets are all aimed at evaluation and research workloads that outlive a chat window. The maintainers are explicit that the worker and kernel processes improve lifecycle isolation and recovery but are **not a security sandbox** — the agent executes model-generated Python with the user's own permissions. The TUI and agent core are built on top of the `pi` project, which the README credits directly. Released under MIT, the repository shipped **v0.7.1 on 2026-08-07** and gained roughly 2,500 stars in a single day during this scan.