Code Agent + Specialized Skills Is All You Need

Here's a simple idea: Code Agent + Skills = Any Task.

Not just software tasks. Any task. But there's a catch.

Code Agent: The Universal Problem Solver

A code agent is inherently generic. Give it any task, and it figures out how to solve it by writing and running code. Process a CSV? It writes a script. Call an API? It writes the integration. Generate a report? It builds the pipeline.

This universality is powerful. One agent can handle tasks that would normally require ten different tools. But generic also means starting from scratch every time. The agent doesn't know your company's data formats, your team's conventions, or your domain's edge cases.

Skills: Specialized Knowledge, Repeatable Results

A skill transforms a generic agent into a domain expert. It's a reusable prompt that encodes specialized knowledge - your proprietary data schemas, your company's workflows, your industry's best practices.

The more specialized the skill, the more useful it becomes. A generic "analyze data" prompt gives you generic results. A skill that knows your specific KPIs, your data sources, and your reporting format? That's a team member who never forgets.

Skills capture expertise without requiring you to maintain code. The agent does the work, the skill guides it with domain knowledge, and you get results tailored to your exact needs.

The Missing Piece: Runtime

You have the code agent. You have the skills. Now where do you run them?

Traditional infrastructure wasn't built for this. A runtime for code agents needs three things:

1. Run from Anywhere

Users should be able to run any agent and skill combination, from anywhere, at any time. Like serverless functions - you don't think about servers, you just invoke the agent and it runs. No setup, no provisioning, no waiting. The agent is always ready.

2. Isolation

Each agent needs its own isolated environment. When you run an agent, it shouldn't interfere with other agents - or be affected by them. Complete separation. Your agent's files, processes, and state are yours alone. This isn't just about security; it's about reliability. One agent crashing shouldn't take down another.

3. State Management

Here's where agents fundamentally differ from traditional services. A typical API request runs once and is destroyed. An agent? It might run for an hour. Or a day. Or a month.

Agents need to pause and resume. They need to survive disconnections. They need to pick up where they left off after a crash. The conversation history, the working files, the execution state - all of it needs to persist across sessions, not just within a single request.

This is the gap. We have frameworks to build agents, observability to trace them, evals to test them. But the infrastructure to actually run them at scale? That's been missing.

Code Agent + Skills + Runtime

That's what Rebyte provides. The runtime layer that turns code agents into production services.

• Run agents as APIs - HTTP endpoints, not terminal sessions
• State management - sessions persist, context survives restarts
• Streaming - durable streams that handle disconnects gracefully
• Isolation - every task runs in its own VM, guaranteed separation
• Recovery - agent crashes? State is checkpointed, conversation resumes

Code Agent + Skills tells you what's possible. The runtime makes it actually work.

Every task is a software task. Now you have the infrastructure to run it.