SaaS versions of automation platforms often have usage-based pricing that becomes expensive. By using a virtual private server (VPS) from a provider like Hostinger, you can install the open-source version of the tool for a low, fixed monthly fee, enabling unlimited workflow executions and significant cost savings.

By running development and knowledge tools like Claude Code on a home server and accessing them via a secure personal VPN like Tailscale, you can transform a mobile phone into a powerful terminal for deep work, including coding and research, from anywhere.

Use an AI assistant like Claude Code to create a persistent corporate memory. Instruct it to save valuable artifacts like customer quotes, analyses, and complex SQL queries into a dedicated Git repository. This makes critical, unstructured information easily searchable and reusable for future AI-driven tasks.

Ben Tossel, a non-technical person, codes from his phone by using a GitHub app to manage pull requests and a Telegram bot to trigger his AI agent to make fixes or add features. This creates a powerful mobile coding workflow, treating the AI like a remote human programmer.

Tools like Git were designed for human-paced development. AI agents, which can make thousands of changes in parallel, require a new infrastructure layer—real-time repositories, coordination mechanisms, and shared memory—that traditional systems cannot support.

For a coding agent to be genuinely autonomous, it cannot just run in a user's local workspace. Google's Jules agent is designed with its own dedicated cloud environment. This architecture allows it to execute complex, multi-day tasks independently, a key differentiator from agents that require a user's machine to be active.

Instead of using siloed note-taking apps, structure all your knowledge—code, writing, proposals, notes—into a single GitHub monorepo. This creates a unified, context-rich environment that any AI coding assistant can access. This approach avoids vendor lock-in and provides the AI with a comprehensive "second brain" to work from.

Moving PRDs and other product artifacts from Confluence or Notion directly into the codebase's repository gives AI coding assistants persistent, local context. This adjacency means the AI doesn't need external tool access (like an MCP) to understand the 'why' behind the code, leading to better suggestions and iterations.

Instead of becoming obsolete, IDEs like IntelliJ will be repurposed as highly efficient, background services for AI agents. Their fast indexing and incremental rebuild capabilities will be leveraged by AIs, while the human engineer works through a separate agent-native interface.