How to Let Your Coding Agent Run Loose? The Rise of 'Smart Proxies'

Imagine this: Before leaving work, you tell your AI agent, “Fix the three bugs I found today and update the relevant documentation,” and then you close your laptop. The next morning, before you even start your day, the agent has perfectly finished all the tasks and is waiting for your review. This scene is no longer a story from a science fiction movie; it is gradually becoming a reality on the coding front.

However, there has been a significant stumbling block in this process: “security” and “control.” Allowing AI to freely modify important files on your computer is as unsettling as giving your home front door password to a total stranger. Recently, agent-specific control technologies, such as “smart proxies,” have emerged to solve this problem.

Why are they attracting attention?

Until now, AI coding tools required users to provide instructions step-by-step right beside them or get permission for every single file modification. This has been the biggest cause of breaking a developer’s focus, or “Flow.” Now, thanks to technological advancements, we are moving into a stage where agents can freely modify files, execute commands, and check logs in a local environment, just like a real fellow developer [Source 1].

These changes go beyond simple speed improvements, ushering in an entirely new era of “autonomous development.” Developers are now free from menial tasks like bug fixes or repetitive environment setup, allowing them to focus on more creative and design-oriented problem solving.

In simple terms

Let’s use an analogy to make it easier to understand. If previous AI coding tools were like “diligent secretaries,” the agents appearing now are closer to “self-driving cars.”

Secretaries needed their owner, the developer, right beside them to give specific instructions: “Turn right here,” or “Stop there.” But self-driving cars find their own routes and avoid obstacles once the destination is set. In this context, technologies like “smart proxies” act as “safe road infrastructure” for self-driving cars.

For example, Trollbridge chooses to control network connections rather than blocking the file system itself [Source 1]. This is similar to leaving the boundaries of the road the car can drive on free, but controlling the entry points so it cannot enter dangerous zones. Thanks to this, agents can freely read, write, build, and check logs on local machines in the same way you work, activity without restriction [Source 1].

How far have we come?

Many platforms are currently trying to catch two rabbits—”autonomy” and “safety”—in their own ways.

• Jules (Autonomous Coding Agent): Scales according to the user’s development flow and can handle up to 15 tasks in parallel at once [Source 8]. With the performance to perform up to 100 tasks a day, it is a tool expected to be deployed in practical use.
• OpenHands (Cloud-based Coding Agent Platform): It is not just tied to a local laptop. Because it works in an isolated sandbox within the cloud (a secure space thoroughly separated from other parts of the computer), the agent can perform tasks even when your computer is turned off [Source 9].
• ClaudeCode: An agent tool created by Anthropic that is deeply integrated with the terminal, allowing it to directly understand the codebase and modify files or execute commands, dramatically increasing development speed [Source 10].
• Open Design: Equipped with 21 coding agents and 151 design systems, it possesses terminal execution permissions that can read not only local files but also exported materials from the design tool Figma [Source 11].

Future outlook

Agents will now go beyond just writing code and begin to breathe closely with the entire development ecosystem. An era is rapidly approaching where agents automatically handle work flows by linking with collaboration tools such as GitHub, Slack, and PagerDuty [Source 9].

In the future, the core competence of a developer will shift from “who writes code faster” to “who can entrust tasks to smarter agents and review the results well.” The current movement of these agents is significant. It is as if agents who have just earned their driver’s licenses are pouring onto the road. We need to prepare to be smart passengers who help these agents drive safely and accurately.

MindTickleBytes AI Reporter’s View

While it is certainly fantastic that an agent can resolve bugs and succeed in builds while the developer is asleep, the fear of “completely losing control” also coexists. What matters is not how many agents you run, but how much you supervise the agent’s behavior in a way that humans can trust. The technology is already here with us. Now is the time to cultivate our “supervision skills.”

References

1. trollbridge — let your agents run amok
2. Cursor CLI — Run Agents in Terminal, GitHub Actions and…
3. GitHub - salarcode/SmartProxy: Firefox/Chrome browser extension.
4. I Built an AI Agent That Made $2,345 in a Day - YouTube
5. SmartProxy

6. [Zencoder

   The AI Coding Agent](https://zencoder.ai/)

7. Jules - An Autonomous Coding Agent

8. [OpenHands

   The Open Platform for Cloud Coding Agents](https://www.openhands.dev/)

9. [ClaudeCode by Anthropic

   AI Coding Agent, Terminal, IDE](https://claude.com/product/claude-code)

10. Open Design — Best Open Source Claude Design Alternative
11. I Built a Secret Room in the MALL! Ft/ Ben Azelart - YouTube

12. [DESIGN.md Examples for AI Agents

    Refero Styles](https://styles.refero.design/)

13. [Running a local coding agent with LM Studio and OpenCode

    ~/adi](https://adim.in/p/local-coding-agent/)

14. [VueHN 2.0

    Show HN: Grinta – a local-first coding agent built for…](https://vue-hackernews-ssr-5cavbdjcta-ew.a.run.app/item/48879730)

15. LangChain: Observe, Evaluate, and Deploy Reliable AI Agents