- Raise your standards as high as you can live with, avoid wasting your time on routine problems, and always try to work as closely as possible at the boundary of your abilities. Do this because it is the only way of discovering how that boundary should be moved forward
- We all like our work to be socially relevant and scientifically sound. If we can find a topic satisfying both desires, we are lucky; if the two targets are in conflict with each other, let the requirement of scientific soundness prevail.
- Never tackle a problem of which you can be pretty sure that (now or in the near future) it will be tackled by others who are, in relation to that problem, at least as competent and well-equipped as you are.
- Write as if your work is going to be studied by a thousand people.
- Don’t get enamored with the complexities you have learned to live with (be they of your own making or imported). The lurking suspicion that something could be simplified is the world’s richest source of rewarding challenges.
- Before embarking on an ambitious project, try to kill it.
- Remember that research with a big R is rarely mission-oriented and plan in terms of decades, not years. Resist all pressure —be it financial or cultural— to do work that is of ephemeral significance at best.
- Don’t strive for recognition (in whatever form): recognition should not be your goal, but a symptom that your work has been worthwhile.
- Avoid involvement in projects so vague that their failure could remain invisible: such involvement tends to corrupt one’s scientific integrity.
- Striving for perfection is ultimately the only justification for the academic enterprise; if you don’t feel comfortable with this goal —e.g. because you think it too presumptuous—stay out!
I like some of these more than others: #1 and #6 are great, but I’m not so crazy about perfectionism #10 (“Done is better than perfect“). I wish this list of commandments was more actionable, but I won’t criticize because his other manuscripts may contain other advice. Please leave your thoughts in the comments (or better yet – links to other Dijkstra manuscripts!)