What Claude Fable Means for Coding Agents
About this episode
Nicolay Gerold discusses the intricacies of coding agents and the impact of the Fable model on AI engineering workflows.
Nicolay Gerold works all day and night on AMP, one of the most interesting coding-agent harnesses out there. If you’re building with coding agents, this conversation will help you understand: * when to trust the model, * when to build harnesses around it, * which model is worth paying for, * which programming languages gives the agent better feedback, and * when to take the keyboard back. Coding-agent products are living inside a blender. Opus 4.8 to Fable changes what the model can be trusted with, eats a workflow, and suddenly the best product decision is to delete code. AMP had handoff because long agent threads used to get messy. Compaction would lose the plot, the model would make worse decisions, and the product needed a way to move the work somewhere cleaner. Then compaction got better. The model ate the feature. AMP killed it. Builders inherit the annoying product test: does this harness code help inspect, verify, recover, or merge model work, or is it just babysitting yesterday’s model? Nico and Hugo riff on why loop engineering is overrated (and when to use it), why Fable is the first model with real engineering taste, and why you should stop writing Python code today…
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