u/Noone-chat

We have a large monolith in fintech to re-work and recently started using xerj as AST and semantic search for Claude code instead of grep/sed waste. After a month we estimated that we saved tokens a few times over for the same refactoring work and visually much “better” (means more like our previous coding style) code.

Recently xerj.org changed their llms.txt promoting reference coding and our harness clones dozens of relevant OSS repos from GitHub using them as a coding corpus for references coding. But the question how is it legal? From one hand OSS licenses allows to reused their code and most likely all of these were in Anthropic datasets anyways.

Anyone have a clear answer?

Which licenses allow that, and how exactly? I mean the approach of reference coding / semantic retrieval like xerj not just using GitHub as a training set (we know it was used heavily to train all of them).

Say you think hard for 5 minutes: 100 W × 5 min ≈ 8 Wh metabolic → ~80 Wh of food-production energy → ~2.5¢ of food. The LLM’s ~0.3 Wh (maybe ~1 Wh counting power-plant and datacenter losses) costs ~0.004¢. So the machine brain is roughly 50–80x cheaper in energy and ~500x cheaper in money per answer.

Human (your assumption: all food powers the brain)

**•**	Intake: \~2,000 kcal/day = **2.3 kWh/day** ≈ a 100 W machine running 24/7  
**•**	Production side: industrial farming burns roughly 10 calories of fuel per food calorie → **\~23 kWh/day** of primary energy to feed you  
**•**	Fuel price: $5–15/day of food = **$2–7 per kWh** of body energy

Top LLM (inference)

**•**	Google reports a median Gemini text prompt uses 0.24 Wh,  and Sam Altman put the average ChatGPT query at about 0.34 Wh.  Depending on query length, most estimates fall in the 0.1–0.6 Wh range.   
**•**	At $0.12/kWh electricity, that’s **\~$0.00004 per answer**.