I'll expand a bit on what mattmullaney said.
Once you have established a gradient range that elutes all your peaks and a steepness that gives you a reasonable k*, the rest of systematic method development consists of optimizing the selectivity (and then tweaking the efficiency if necessary). In that respect, gradient and isocratic behave the same way. There are six parameters that can change selectivity (move peaks around relative to one another):
- Solvent strength (isocratic) or gradient steepness (gradient). As suggested by mattmullaney, this is probably the first thing you should look at.
- Temperature
- Organic solvent type (acetonitrile / methanol / THF)
- pH (if your analytes have weak acid / base functionality
- buffer concentration
- column chemistry
In a pharmaceutical company, you would turn to "Quality by Design" or "Design of Experiments" ("QbD" or "DOE") to set up experimental matrices to evaluate the combined effects of the different paramters. In many cases it's easier and equally effective to use the "OFAT" ("One Factor At a Time") approach. Take your initial method and make a big change in each parameter in turn (changing only one parameter at a time!). If/when you see the peak spacing change, you focus on optimizing that parameter until you get the resolution you need. If you're lucky, the first parameter you look at (usually gradient steepness) will do the trick. If you're not lucky, you'll be in for a lot of work.