Copy of Agents & Code Writing Tools
Recently, two frameworks introduced code writing tools for their AI Agents, does this mean AI Agents can to write code to execute tasks?
In principle, yes…but practically no…
Both OpenAI (free form functions) and xAI (code_execution) introduced AI Agent tools which can write code.
So when the AI Agent receives an instruction which it does not have an explicit tool to assigned to it, the AI Agent can use the code writing tool to write the code to achieve or fulfil the requirement.
The xAI code_execution tool is a prime example of how a model like Grok can autonomously generate code to achieve a specific goal, embodying what’s often called “agentic code generation” or “self-programming” in AI systems.
As I have mentioned, the xAI’s code writing functionality — via thecode_execution tool — bears strong similarities to OpenAI’s free-form function calling (also called freeform tool calling) in GPT-5, particularly in how both allows the model to dynamically generate raw code to solve unstructured problems or achieve specific goals.
At a high level, they’re both agentic features that let the LLM transcend simple text responses by creating executable content on the fly, turning the model into a proactive coder rather than a mere describer.
Agent tools like xAI’scode_execution (or OpenAI’s free-form function calling) move us toward fully autonomous agents — ones that can dynamically generate code to tackle novel goals without predefined tools or explicit programming for every scenario.
Moving from rigid toolkits to self-authoring executors, where the agent essentially invents its own sub-tools on the fly….
Why This Gets Us Closer to Autonomy
For example, the AI Agent reasons about a gap, generates bespoke Python, executes it in a sandbox and iterates based on outputs.
This mirrors how humans improvise — sketching a script to prototype a solution — rather than pulling from a static menu.
Why Not Fully Autonomous Yet
We’re close, but significant hurdles remain — mostly environmental and safety-related…
AI Agent tools like xAI’s code_execution mark a big step toward fully autonomous AI Agents, enabling custom code generation to fill predefined tool gaps…but
Current Limitations
Yet, key barriers keep them from complete independence…
Sandbox constraints for security limit them, no arbitrary installs or direct internet, sticking to pre-loaded libraries.
They improvise with proxies available, but can’t create truly novel tools needing unrestricted access, restricting adaptability to bounded tasks.
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Code iteration is error-prone too — the model can hallucinate bugs in complex logic, and finite token/cost limits hinder thorough debugging.
It nails 70–80% of simple goals but falters on edges, often requiring human fixes.
I have seen how AI Agents / models create seemingly perfect code, but trying to execute the code in a notebook or other environments takes multiple re-prompts.
The larger the chunk of code generated, the harder it is to get it working.
Goal alignment falters with ambiguous prompts, leading to misdirected code that chases sub-goals over the main intent. Thus, it’s not self-directed; it needs crisp instructions to stay on track.
I have found that you really need to break down the requirements in detail, step by step fashion. That is why I believe Gemini is so successful in Colab Notebook….
Because there is already a strong contextual reference win working code, and problems are addressed on a cell by cell basis.
Scalability and safety further constrain evolution because the REPL is session-only, blocking persistent tool-saving for cross-run reuse. This prevents rogue risks but stalls super intelligent growth.
Toward Self-Writing Agents
The trajectory — code-as-universal-adapter — echoes AGI visions from thinkers like Ilya Sutskever: Agents that “program the world” by generating tools for any gap.
In previous articles I walk through examples of code writing AI Agents.
OpenAI
GPT-5 Freeform Function Calling Enabling AI Agents To Write Code OpenAI’s GPT-5 introduces a set of developer features that deepen the integration between applications and the model.cobusgreyling.medium.com
xAI
xAI Introduced Agentic Server-Side Tool Calling xAI models can act as intelligent agents to handle complex queries by calling on tools where model knowledge is not…cobusgreyling.medium.com
Chief Evangelist @ Kore.ai | I’m passionate about exploring the intersection of AI and language. Language Models, AI Agents, Agentic Apps, Dev Frameworks & Data-Driven Tools shaping tomorrow.
