However exciting all this may sound, the situation creates not only benefits but also new challenges peculiar to CCP4's role as a crystallographic knowledge keeper and software developer and maintainer. Now, probably, around 90% of the package will see a rather low (yet non-zero) use rate, which puts up a question of how economical it is to continue the support of old codes, their testing, adjustment to ever-evolving file formats, new types of data and so on. Likewise, should CCP4 invest in the future development of methods, alternative to MR, that are likely to see a drastically decreased (yet non-zero) interest? “The new way" is so much more robust and simpler (yet not a 100%-sure shot), that little prior knowledge is required from a molecular biologist to solve a structure – will this affect the level of relevant expertise in the field? Probably yes. And how CCP4 should now revise its extensive educational program, if only a rather thin slice of its functionality is expected to be used by 90% of researchers? Given a clear demonstration, by AlphaFold, of what AI technologies may achieve, is there a scope for a deep, AI-based revision of many other CCP4 components and structure solution methods?
We do not have answers to all these questions now, but they will surely come in the next few years at the latest. CCP4 has been delivering crystallographic software for more than 40 years now and has been through various challenges only to become better and stronger. One thing is clear, we are crossing a ridge at the moment, with a vision of new challenges and opportunities on the other side. CCP4 Project needs to change in the new “AlphaFold, AI, era", and it will do so.
*'CCP4 exists to produce and support a world-leading, integrated suite of programs that allows researchers to determine macromolecular structures by X-ray crystallography, and other biophysical techniques.'
 Jumper, J., Evans, R., Pritzel, A. et al. (2021) Nature 596, 583–589.
 Smith, T.F. & Waterman, M.S. (1981) J. Mol. Biol. 147(1) 195-197.
 Aloy, P., Stark, A., Hadley, C. & Russell, R.B. (2003) Proteins: Struct. Funct. Bioinf. 53(S6) 436-456.
 Yona, G. & Levitt, M. (2002) J. Mol. Biol. 315(5) 1257-1275.
 Söding, J. (2005) Bioinformatics 21, 951-960.
 Baek, M., DiMaio, F., Anishchenko, I. et al. (2021) Science 373(6557) 871-876.
 Winn, M. D., Ballard, C. C., Cowtan, K. D., Dodson, E. J., Emsley, P., Evans, P. R., Keegan, R. M., Krissinel, E. B., Leslie, A. G. W., McCoy, A., McNicholas, S. J., Murshudov, G. N., Pannu, N. S., Potterton, E. A., Powell, H. R., Read, R. J., Vagin, A. & Wilson, K. S. (2011). Acta Cryst. D67, 235-242.
 Liebschner, D., Afonine, P. V., Baker, M. L., Bunkoczi, G., Chen, V. B., Croll, T. I., Hintze, B., Hung, L.-W., Jain, S., McCoy, A. J., Moriarty, N. W., Oeffner, R. D., Poon, B. K., Prisant, M. G., Read, R. J., Richardson, J. S., Richardson, D. C., Sammito, M. D., Sobolev, O. V., Stockwell, D. H., Terwilliger, T. C., Urzhumtsev, A. G., Videau, L. L., Williams, C. J. & Adams, P. D. (2019). Acta Cryst. D75, 861-877.
 Krissinel, E., Lebedev, A., Uski, V., Ballard, C., Keegan, R., Kovalevskiy, O., Nicholls, R., Pannu, N., Skubák, P., Berrisford, J., Fando, M., Lohkamp, B., Wojdyr, M., Simpkin, A., Thomas, J., Oliver, C., Vonrhein, C., Chojnowski, G., Basle, A., Purkiss, A., Isupov, M., McNicholas, S., Lowe, E., Triviño, J., Cowtan, K., Agirre, J., Rigden, D., Uson, I., Lamzin, V., Tews, I., Bricogne, G., Leslie, A., & Brown, D. (2022), Acta Cryst. D, under review.