Solomonoff Induction is uncomputable, and implementing it will not be possible even in principle. It should be understood as an ideal which you should try to approximate, rather than something you can ever implement.
Solomonoff Induction is just bayesian epistemology with a prior determined by information theoretic complexity. As an imperfect agent trying to approximate it, you will get most of your value from simply grokking Bayesian epistemology. After you've done that, you may want to spend some time thinking about the philosophy of science of setting priors based on information theoretic complexity.
I read about a fascinating technique described on Wikipedia as a mathematically formalized combination of Occam's razor and the Principle of Multiple Explanations. I want to add this to my toolbox. I'm dreaming of a concise set of actionable instructions for using Solomonoff induction. I realize this wish might be overly idealistic. I'm willing to peruse a much more convoluted tome and will consider making time for any background knowledge or prerequisites involved.
If anyone knows of a good book on this, or can tell me what set of information I need to acquire, please let me know. It would be much appreciated!