1. Goals setting, decomposition, tracking, potentially with the integration with the data sources (like healthcare data, education data, career data, finance data, carbon footprint data, etc) so that the system will automatically upload the data from the data sources and highlight whether the goals are being accomplished or not

2. Uploading the catalogue of the measures to reach the goal (in perspective with an AI recommendation tool – like, what other people usually use as a measure, what pace do they usually choose, what pace is needed on a quarterly basis to reach the target in a year or in 5 years (including the calculation of the compound interest when you want to reach some goal (like +100% (ie of money) or minus 30% (of weight) or minus 80% of the carbon footprint - how much should you do on a yearly basis to reach that target

3. Appoints the reviewer in a random, non-repeating manner every 3 months, so that the reviewer and the reviewed don’t review each other this time or even in the nearest term

4. Enables the reviewer to evaluate the ambitiousness of the goals (again with the help of AI, so that at some point it can be done automatically by the system, especially with the integration with the data sources)

5. Enables the reviewer to evaluate the fulfillment of goals (where there is yet no transparently calculated mechanism to do that automatically, so that “AI” will evaluate that in a more objective manner; probably it could be a reviewer AI-assisted measurement, where the AI sets the boundaries of the measure, and the reviewer picks the measure within those boundaries. Or the reviewer assigns the measure and then the system calculates the average between the reviewer’s measure and the AI’s, etc.

1. So that each member can suggest a new member

2. So that that new member can sign the code online (consent to comply with it)

3. So that a system could pick randomly the interviewers (3), so that each interviewer would keep up with quota 9 interviews per year

4. Calculates the number of recruited by each member (to meet the target (3 per year))

5. So that each new member will be able to invite new recruits only after having fulfilled certain criteria (ie presenting the research on a meeting)

6. Basically, the system should make the recruit a member only after filling the SIDP (so somehow, probably, there should be a check that the SIDP has been correctly composed and filled out)

7. Maybe in the future even there would be a mechanism of making the recruit - the member not only after correctly filling out the SIDP, but also after meeting 80% of the targets set in that SIDP for 3 months in the period of 3 months

8. Maybe the interviewing process will become obsolete then

9. Maybe there could be a self-application process even. And the system can assign you “a buddy” / first interviewer

1. It provides the list of the aspects of the SDG+ (Live to Learn (L2L)) methodology that are ready to be updated (for instance there is no science base enough for this or that target, whether it leads to the subsequent level of target (goal) or not; or this target / measure to achieve it hasn’t been updated for a long time (because the evidence always changes), or the target correlates with the experience / background of the member / recruit, so it helps him / her choose the area of the research

1. Methodologically (like change the structure and intercorrelations of the goals, the weights, the measures, etc) - so there should be an easy to use Zero-code / No-code constructor / toolkit to do that, to review the changes by others

2. Maybe even in a programming way (making it an open platform, open to the updates from the community of developers, that all are the members of the club of course and have the goals to update the code in their SIDPs as well)