Source URL: https://simonwillison.net/2025/Jun/18/coding-agents/#atom-everything
Source: Simon Willison’s Weblog
Title: Coding agents require skilled operators
Feedly Summary: I wrote this recently in a conversation about whether coding agents can work as a replacement for human programmers.
The “agentic" coding tools we have right now work like this:
A skilled individual with both deep domain understanding and deep understanding of the capabilities of the agent (including understanding what tools are available to that agent) poses a clear task to it.
The agent writes some code relating to that task. It runs a tool to execute and test that code. It inspects the result, and if there are errors it edits the code and tries again.
It may call other tools as well, for example a search tool to find related code or even to look up API documentation elsewhere (including via web search).
It continues like this until it hits a loosely defined “done” state or gets stuck.
The skilled individual then reviews what it has done and almost always finds that it has not solved the problem to their satisfaction… so they apply their expertise and domain understanding to prompt it again to try and get to that desired state.
Without the skilled individual, the “agent” is useless. It may as well not exist.
Tags: coding-agents, ai-assisted-programming, generative-ai, ai-agents, ai, llms
AI Summary and Description: Yes
Summary: The text discusses the limitations of current coding agents in the context of AI-assisted programming, emphasizing the necessity of human expertise for effective problem-solving. It highlights the interplay between human programmers and AI tools.
Detailed Description:
The content explores the functionality and effectiveness of agentic coding tools, emphasizing that while these AI agents can aid in programming tasks, they remain largely dependent on skilled human input to achieve satisfactory outcomes. The following points summarize the major insights from the text:
– **Agentic Coding Tools**: These AI-driven coding solutions operate under the premise that a skilled programmer interacts with the agent by providing clear tasks.
– **Process Breakdown**:
– The agent composes code based on the task provided.
– It executes and tests the code through various tools.
– The agent inspects outcomes and iteratively edits the code when errors arise.
– It may utilize external resources, such as searches for related code or API documentation.
– **Limitations**:
– Agents often reach a point of incomplete task satisfaction, necessitating human intervention.
– The role of the skilled individual is crucial; without it, the AI agent falls short of being effective.
– **Skill Requirement**: The continual dependence on human input underscores that AI coding agents are not autonomous and require deep domain expertise to guide them.
In essence, this analysis of coding agents illustrates the current state of AI in programming, indicating that while there are advancements in AI capabilities, the synergy between human expertise and AI tools is fundamental for successful outcomes in development projects. This has implications for stakeholders in AI and software security sectors, as it highlights important human-AI collaboration dynamics that should be factored into security protocols and compliance frameworks.