Context graphs should store product decisions, not generic options
EyalToledano · x · 2026-07-20
A note on context graphs in production work: the most valuable thing they store is why the product ended up this way.
The post argues that LLMs naturally drift toward generic, average-looking choices. That can work for exploratory tasks, but in production it leaves subtle wrong decisions that surface later during debugging. The better approach is to record actual decisions and use them as context, rather than asking the AI to generate four generic options up front.
The attached screenshot shows a Hamster CLI brief/refinement flow: plans, context, syncing initiatives, and structured questions about data modeling. The point is that the graph should surface decisions that already mattered, not re-hash generic documentation.
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