The Source of Knowledge
- Collect algorithm details at the time, before they are forgotten
- Influence to be an advancement of knowledge
    - 250 breasonings at each point of drilling down to get to the next level
    - Check whether the algorithm idea is a good idea
    - Writes a new predicate when no predicate descriptions match the requirement
    - A raw idea is articulated to be general enough (a label for the period of the ideas) and with specific enough reasons (radical in natural and secular ways) which match the general style of the author
    - New predicate combinations are bug checked for near misses
     - The user writes predicate descriptions when the predicates are written to find them when needed again
     - The algorithm writer should give the predicate an argument to call another predicate if necessary, which has another description/meaning
     - API calls, specific data in algorithms from mind reading and string transformation may be automated
	 
Mind reader and meaning consolidator and recorder
- The Mindreader and meaning consolidator and recorder is the LM chatbot
- (Precursor to computer) science dictionaries along the way collecting non-computable knowledge, e.g. the way a file synchroniser works
- Forgotten knowledge doesn't reappear
- Special knowledge - new (like a research conclusion)
- Natural law alignment, new algorithm term, technique or achieving an aim
- The lines of reasoning, higher up, verification by a lecturer of ideas and writing for and against columns when preparing a reason in a PhD are, in fact, the seen-as version and ten breasonings idea.  Finding fault is negative terms, but might not matter in computer science.
- A method of generating ideas
- An idea must be related to natural law or have a B to it