Recursive Coding Agents - Raymond Weitekamp, OpenProse
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AI Engineer
Author
AI Engineer
Date
Terms in this piece · Glossary
test-time compute — Spending more computation when the model answers — thinking longer, trying multiple attempts — to buy accuracy without training a bigger model.
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
Why it matters
If you're building coding agents, this maps the Recursive LLMA large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.Full definition → paradigm onto AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → orchestration, clarifying when sub-agents actually constitute recursion and how to structure declarable, recursively-solvable tasks via Claude Code Dynamic Workflows and OpenProse.
Key quotes
“the bottleneck to this is not intelligence. The models are intelligent enough.”
Raymond Weitekamp
“The next day, and I swear this actually happened, cloud code empties the entire contents of my Solana wallet.”
Raymond Weitekamp
“The thesis is today's agents are mismanaged geniuses.”
Raymond Weitekamp
“I don't care whether it's latent space or reasoning tokens or code execution. I want results.”
Raymond Weitekamp
“in an RLM, the context itself is the object of computation”
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