The articles example for this is Casgevy, a gene therapy that can mostly cure Sickle Cell. The problem is in order for that gene therapy to work it takes surgeons, full transplant teams, super-chillers, chemotherapy, and full hospitals to deliver it and for the patient to recover in while being carefully monitored. This is what drives the cost, and so it doesn't matter how cheap the actual gene sequencing or editing is, the rest of the costs dominate. This is Amdahl's law, but for costs- the costs are dominated by the non-gene editing part of the process and so that determines the improvement in cost you will see.
Also one of the benefits of cheap to produce unique gene therapies is once you figure out one treatment, similar treatments for slightly different genetic anomalies affecting the same tissues will become much easier to apply. In other words once you have a delivery mechanism down targeting something specific, the gene payload can be swapped at much lower incremental cost.
We are not yet at the point where we can effectively just substitute genes and everything works in vivo, and until we get to that point every fix requires its own Phase III trial, and that (both the costs and the chance of complete failure) is what drives the R&D expense through the roof, even if a single infusion could fix the problem, unlike the other examples I cited.
1: Existing gene editing platforms don't work well for large genes: there is an effective base pair limit for all existing techniques in vivo. Most Stargardt's genes, to pick another similar to Luxterna as an example, are above that limit, and will require new techniques not yet approved in vivo.
The first gene therapy approved for in vivo treatment by the FDA, Luxterna, was approved in 2017. It treated RPE65 associated Retinitis Pigmentosa (at an original list price of 425,000/eye). Just a few months ago, J&J's LUMEOS trial revealed that basically the same process but targeting a different gene (RPGR) failed to meet its primary endpoints in the Phase III clinical trial (only 22 of 55 patients treated showed improvement on at least two measures, and there was no statistically significant improvement on the main measure at all). At this point, we can't even reliably take a process that fixed one gene and apply it to another gene to treat the same disease, that's how far away we are from "some dude in a garage." Will we get there? Maybe, but the human body is far more complicated than software, and analogies based on how software work mislead more than they help.