# Roadmap This document expands the roadmap preview in `README.md`. Paperclip is still moving quickly. The list below is directional, not promised, and priorities may shift as we learn from users and from operating real AI companies with the product. We value community involvement and want to make sure contributor energy goes toward areas where it can land. We may accept contributions in the areas below, but if you want to work on roadmap-level core features, please coordinate with us first in Discord (`#dev`) before writing code. Bugs, docs, polish, and tightly scoped improvements are still the easiest contributions to merge. If you want to extend Paperclip today, the best path is often the [plugin system](doc/plugins/PLUGIN_SPEC.md). Community reference implementations are also useful feedback even when they are not merged directly into core. ## Milestones ### ✅ Plugin system Paperclip should keep a thin core and rich edges. Plugins are the path for optional capabilities like knowledge bases, custom tracing, queues, doc editors, and other product-specific surfaces that do not need to live in the control plane itself. ### ✅ Get OpenClaw / claw-style agent employees Paperclip should be able to hire and manage real claw-style agent workers, not just a narrow built-in runtime. This is part of the larger "bring your own agent" story and keeps the control plane useful across different agent ecosystems. ### ✅ companies.sh - import and export entire organizations Reusable companies matter. Import/export is the foundation for moving org structures, agent definitions, and reusable company setups between environments and eventually for broader company-template distribution. ### ✅ Easy AGENTS.md configurations Agent setup should feel repo-native and legible. Simple `AGENTS.md`-style configuration lowers the barrier to getting an agent team running and makes it easier for contributors to understand how a company is wired together. ### ✅ Skills Manager Agents need a practical way to discover, install, and use skills without every setup becoming bespoke. The skills layer is part of making Paperclip companies more reusable and easier to operate. ### ✅ Scheduled Routines Recurring work should be native. Routine tasks like reports, reviews, and other periodic work need first-class scheduling so the company keeps operating even when no human is manually kicking work off. ### ✅ Better Budgeting Budgets are a core control-plane feature, not an afterthought. Better budgeting means clearer spend visibility, safer hard stops, and better operator control over how autonomy turns into real cost. ### ✅ Agent Reviews and Approvals Paperclip should support explicit review and approval stages as first-class workflow steps, not just ad hoc comments. That means reviewer routing, approval gates, change requests, and durable audit trails that fit the same task model as the rest of the control plane. ### ⚪ Multiple Human Users Paperclip needs a clearer path from solo operator to real human teams. That means shared board access, safer collaboration, and a better model for several humans supervising the same autonomous company. ### ⚪ Cloud / Sandbox agents (e.g. Cursor / e2b agents) We want agents to run in more remote and sandboxed environments while preserving the same Paperclip control-plane model. This makes the system safer, more flexible, and more useful outside a single trusted local machine. ### ⚪ Artifacts & Work Products Paperclip should make outputs first-class. That means generated artifacts, previews, deployable outputs, and the handoff from "agent did work" to "here is the result" should become more visible and easier to operate. ### ⚪ Memory / Knowledge We want a stronger memory and knowledge surface for companies, agents, and projects. That includes durable memory, better recall of prior decisions and context, and a clearer path for knowledge-style capabilities without turning Paperclip into a generic chat app. ### ⚪ Enforced Outcomes Paperclip should get stricter about what counts as finished work. Tasks, approvals, and execution flows should resolve to clear outcomes like merged code, published artifacts, shipped docs, or explicit decisions instead of stopping at vague status updates. ### ⚪ MAXIMIZER MODE This is the direction for higher-autonomy execution: more aggressive delegation, deeper follow-through, and stronger operating loops with clear budgets, visibility, and governance. The point is not hidden autonomy; the point is more output per human supervisor. ### ⚪ Deep Planning Some work needs more than a task description before execution starts. Deeper planning means stronger issue documents, revisionable plans, and clearer review loops for strategy-heavy work before agents begin execution. ### ⚪ Work Queues Paperclip should support queue-style work streams for repeatable inputs like support, triage, review, and backlog intake. That would make it easier to route work continuously without turning every system into a one-off workflow. ### ⚪ Self-Organization As companies grow, agents should be able to propose useful structural changes such as role adjustments, delegation changes, and new recurring routines. The goal is adaptive organizations that still stay within governance and approval boundaries. ### ⚪ Automatic Organizational Learning Paperclip should get better at turning completed work into reusable organizational knowledge. That includes capturing playbooks, recurring fixes, and decision patterns so future work starts from what the company has already learned. ### ⚪ CEO Chat We want a lighter-weight way to talk to leadership agents, but those conversations should still resolve to real work objects like plans, issues, approvals, or decisions. This should improve interaction without changing the core task-and-comments model. ### ⚪ Cloud deployments Local-first remains important, but Paperclip also needs a cleaner shared deployment story. Teams should be able to run the same product in hosted or semi-hosted environments without changing the mental model. ### ⚪ Desktop App A desktop app can make Paperclip feel more accessible and persistent for day-to-day operators. The goal is easier access, better local ergonomics, and a smoother default experience for users who want the control plane always close at hand.