On the contrary, not only is this planning step not impossible in current programming practice, it's universal, or very nearly so. Almost nobody programs by hex-editing machine code anymore. We just edit the design, often in a language like Golang or C++, and then tell the compiler to start "laying the bricks," which it finishes typically in a few seconds to a few minutes. If we don't like the result, we change the design and rebuild part or all of it according to the new design.

More modern systems like LuaJIT, SpiderMonkey, and HotSpot are even more radical, constantly tearing down and rebuilding parts of the machine code while the program is running. Programs built with them are more like living things than buildings, with osteoclasts constantly digesting bones while osteoblasts build them. In these systems we just send the plans—our source code, or a sparser form of it—to the end-user to be gardened and nurtured. Then, just as osteoblasts build denser bone where its strength is most needed, the JIT builds higher-performance code for the cases that automatic profiling shows are most performance-critical to that user.

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Soon architects will be able to do their work in the same way.

Like Microsoft programmers in the 01990s, they'll do a "nightly build" of the current design with a swarm of IoT 3-D printers. Consider the 10,000 tonnes of structural steel that make up the Walt Disney Concert Hall in Los Angeles, which seats 2265 people. After the 16-year construction project, it was discovered that reflection from the concave surface was creating deadly hot spots on the sidewalk and nearby condos, requiring some expensive rework.

If each assembler can bolt a kilogram of steel onto the growing structure every 8 seconds, then 2000 assemblers can rebuild it from source in a bit over 11 hours. In the morning, like programmers, the architects can walk through the structure, swing wrecking balls at it to verify their structural integrity calculations, and see how the light falls, and, importantly, notice the sidewalk hotspots. Perhaps another 2000 printers using other materials can add acoustic panels and glazing, so the architects can see how the acoustics of the space work. Perhaps they can try out smaller changes while inside the space using a direct-manipulation interface, changing the thickness of a wall or the angle of an overhang, while being careful not to stand underneath.

In the afternoon, when the architects have gone home, the assemblers begin the work of garbage collection of the parts of the structure whose design has been changed, so the next nightly build reflects the latest updates. As night falls, they begin to rebuild. The build engineer sings softly to them by the moonlight, alert for signs of trouble that could stall the build.

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Today that isn't practical—the nightly build machine for a single architectural firm would cost several billion dollars. But that machinery itself will come down in cost as we learn to bring the exuberant living abundance of software to other engineering disciplines.

To do ten "load builds" in the 16 years the Walt Disney Concert Hall took, you'd only need two assemblers, perhaps costing a couple million dollars at today's prices; they'd be able to complete each successive prototype building in 15 months.

Suppose prices come down and you can afford 32 assemblers, each placing a kilogram of steel every 8 seconds. Now you can do a "monthly build", which is roughly what I did when I joined a C++ project in 01996 as the build engineer. Or you can build 10:1 reduced scale models (big enough to fit 22 people, in this case) a thousand times as fast. Incremental recompilation on the C++ project allowed individual developers to test their incremental changes to the design, and similarly this kind of automation could allow individual architects to test their incremental changes to the building, though perhaps not all at the same time—the full-scale building would be like an "integration test server".

Suppose prices come down further and you can afford 512 such assemblers. Now you're not quite to the point of being able to do nightly builds, but you can do a couple of builds a week, and you can rebuild a fourth of the Walt Disney Concert Hall overnight.

Suppose prices come down further and you can afford 8192 assemblers. Now you can rebuild the building several times a day. You can totally remodel the concert hall between the morning concert and the afternoon concert.

Suppose prices come down further and you can afford 131072 assemblers. Now you can rebuild the concert hall in 10 minutes. There's no longer any need to leave it built; you can set it up in a park on a whim for a concert, or remodel it into a cruise ship.

Suppose prices come down further and you can afford 2097152 assemblers. Now totally rebuilding the concert hall takes about 30 seconds, and you can adapt it dynamically to the desires and practices of whoever is using it at the moment. This is where modern software development practice is: my browser spends 30 seconds recompiling Fecebutt's UI with SpiderMonkey every time I open the damn page. At this point the "assemblers" are the concert hall; they weigh 5 kg each and link their little hands together to form dynamic, ephemeral structures.

Suppose the assemblers singing kumbaya shrink further; now each weighs only 300 g, and they are capable of acrobatically catapulting one another into the shape of the Walt Disney Concert Hall, or any other ten-thousand-tonne steel structure you like, in a few seconds.

(Wouldn't this waste a lot of energy? Probably not, though it depends on the efficiency of the machinery; the energy cost of lifting ten thousand tonnes an average of ten meters off the ground is about a gigajoule, 270 kWh; at 4¢/kWh that's US$11. In theory you can recoup that energy when you bring the structure back down, but lots of existing technology loses a factor of 10 or 100 to friction. Even at a factor of 100, though, the energy cost is unlikely to be significant compared to construction costs today.)

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But tell me more about how programmers need to plan more to reduce the cost of construction mistakes?