With over 77,000 GitHub stars accumulated in under five months since its March 2026 launch, Paperclip has become the default control plane for teams running multiple AI agents in production. Rather than juggling dozens of terminal tabs with Claude Code sessions, Codex instances, and Gemini CLI workers, Paperclip organizes all agents into a company structure with org charts, reporting lines, role-based permissions, and per-agent monthly budgets that trigger hard-stops when exceeded. The platform supports any runtime through its adapter system — Process adapters manage local CLI agents like Claude Code, Codex, Cursor, Pi, and OpenCode as child processes, while HTTP adapters trigger remote agents via webhooks to OpenClaw, serverless platforms, or custom endpoints. Heartbeat-based execution wakes agents on configurable schedules, injecting goal context, budget state, and workspace paths directly into the invocation payload. The Work and Task System provides atomic checkout with execution locks, first-class blocker dependencies, and structured work products to eliminate duplicate effort. Governance features include approval workflows, decision tracking, emergency stops, and full audit trails tracing every mutation to an actor. Deployment runs as a single Node.js process with embedded PostgreSQL locally or scales to external Postgres for production, installable in one command via npx paperclipai onboard. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Processing over one billion tasks per month on Hatchet Cloud and holding 7,600+ GitHub stars, Hatchet is the open-source orchestration engine that replaces fragile legacy queues with durable, fault-tolerant task execution built entirely on PostgreSQL — no Redis, RabbitMQ, or Kafka required. Born from the creators' experience scaling Uber's Cadence-inspired patterns, the v1 engine achieves 10,000 tasks per second sustained throughput with 20ms average queue latency through dynamic buffer flushing and batch insert optimization. Define tasks, durable workflows, and DAG pipelines as code using native SDKs for Python, TypeScript, Go, and Ruby — every function gets automatic retries with configurable backoff, concurrency control with group round robin or cancellation policies, priority queuing, and dynamic rate limiting for third-party API protection. Durable execution persists the complete history of every task and state transition, enabling replay from failure, debugging via full event timelines, and complex pause/resume conditions using durable sleep and event waits. The real-time web dashboard provides workflow run visualization with DAG timeline rendering, worker health monitoring with slot utilization, queue depth metrics, task throughput charts, and error rate tracking — all filterable by status, workflow, or time window. OpenTelemetry integration and Prometheus metrics export enable advanced observability. Multi-tenant by default with users, roles, and namespace isolation. Self-host via Docker Compose with PostgreSQL and optional RabbitMQ, or use the single-container Hatchet Lite image for development. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Powering mission-critical infrastructure at OpenAI, Cursor, Replit, Lovable, Retool, and Snap with over 22,000 GitHub stars, Temporal is the durable execution platform that originated from Uber's Cadence project — built by the creators of AWS SQS, AWS SWF, and Azure Durable Functions with nine years of production-proven reliability. The workflow-as-code model lets developers write business logic in Go, Java, Python, TypeScript, .NET, PHP, or Ruby using native SDKs, while the Temporal Server automatically persists state at every step, replays from failures, retries activities with configurable backoff policies, and manages task queues without developers writing reconciliation logic. Workflows support signals for external event injection, timers for scheduled delays, child workflows for decomposition, and queries for real-time state inspection — all backed by deterministic replay over an event-sourced history that guarantees exactly-once semantics. The Web UI provides visual workflow execution inspection with event timelines, pending activity monitoring, namespace management, and worker health dashboards. Persistence supports PostgreSQL, MySQL, or Apache Cassandra for horizontal scalability, with Elasticsearch or OpenSearch for advanced workflow visibility queries. Multi-cluster replication enables global failover across data centers. The self-hosted stack deploys via Docker Compose with the auto-setup image, PostgreSQL, Web UI, and admin tools — operational within 30 minutes. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.