It doesn't really make sense to talk about DNA as source code vs object code vs whatever.
Biology doesn't have the same clean levels of abstraction that we've developed in computer science. DNA functionally operates at many levels. It long term storage, local working storage, and it is used to compute. It's a single molecule that does everything.
Then you have to throw in all the secondary processes that modulate and regulate DNA replication, transcription, as well as activation/deactivation.
While it can be useful to lean on the abstractions we've developed to try to understand what DNA is doing those abstractions can only be taken so far.
Yeah, I was kind of making a joke. But to stretch the analogy...
Maybe there is a common source that is cross compiled to different chemistries producing a seed object code cell.
Indeed, I classify the main difference between life (biological systems) and technology (civilization engineered systems) is about the structure of complexity.
Human civilization is severely time-limited (or just time-pressed). We can't wait millions of years running a simulation to optimize a little widget. We need to rely very much on high level design and comparatively little on efficiency and optimization. On the other hand, life cannot afford huge DNA (very costly), or energy waste (generally disfavorable from evolution). So human built systems tend to be of a low "Compute complexity": the computational complexity of obtaining solutions and solving problems themselves (like civil engineering structure problems, or design of objects) must be fairly low. For life, systems can be amazingly intricate, every tiniest cell a wonder that would probably take thousands of years for civilization to maybe be able to replicate. But it all ranges from about 130kbp to 8Mbp[1], which would be around 16Mbit/2Mbytes at most. So it fits (uncompressed) in a diskette (floppy).
Even now with powerful computers, we're still mostly constrained by cognition (specially human), you see simplicity all around you.
So if you look at the human world, you see (computational) simplicity everywhere, but the natural world has undergone trillions of generations of optimization to arrive at almost perfect (in an almost literal way) little machines, complicated but with a hidden amazing (size) simplicity.
I think there's a connection to be made to algorithmic inference as well. Originally we came up with ideas for Universal Inference (from ideas from by Solomonoff, Kolmogorov among others) [2][3], the most glaring candidate was the "size prior": evidence explainable by the least algorithmic information ought to be most likely (Solomonoff inference). Later, there were promissing ideas around an additional term: the "speed prior" (from Schmidhuber[4]) -- the biological word is one where the "size prior" (simplicity is most likely) works almost perfectly, and human civilization is one where the "speed prior" (computationally easy is most likely) is helpful.
Side note: I think intellectually one of the ways we're really far behind is recognizing Algorithmic Information theory as a foundation for statistics and metaphysics. We're very stuck making little progress on the metaphysical realm (which physics is advancing more into) because of a lack of widespread acceptance of those advanced tools for science. Algorithmic inference gives a solid basis for comparing metaphysical models and deep questions about the cosmos.
embryology made me realize that there's also an inherited context in how genes control development, IIRC the womb triggers some key structural changes in the very first days.
Biologist performed so many crazy experiment on fruit fly, development biology is very interesting for reading: what happen in each stage and all of mechanism we can understand.
I would disagree, we see the object code. If we had the source, with comments, genetic engineering would be much easier