Its a cool tool, but right now it's more of a productivity aide for people who already understand Verilog/VHDL rather than an enabler for software engineers.
Here's the thing:
Knowing VHDL/Verilog will not:
- Get you a job with compensation on the same level as ML/Web Dev.
- Magically make your tech/startup work better
- Fulfill buzzword requirements for investors
These sort of low level tooling is tremendously difficult to make profitable unless you already have some sort of vendor lock-in i.e. silicon, or an application that is extremely demanding in terms of efficiency or speed e.g. High Frequency Trading, network switches, dot-product-machines (commonly known as ML) and crypto hardware. Unfortunately any other applications for FPGAs tend to closely related to the embedded space (robotics, aerospace) and again it's significantly more annoying to monetize compared to e.g. a SaaS oriented around ML. Especially so it you are not a massive corporation with deep pockets.
The closest we have come to a high level tool for FPGA synthesis is reconfigure.io but they got acquired and is now effectively dead.
CPUs and ASICs have become too powerful and too cheap. Even with Moore's law tapering off, the gains provided by FPGAs are still too narrows. Electrical engineers are cheap. Physics have not changed much in recent decades. A couple computer architecture courses is more than enough to bring an EE graduate up to speed (referring to FPGAs here, ASICs are another story)
[2] https://www.chisel-lang.org/
[3] https://www.chisel-lang.org/firrtl/
Also there's not necessarily much of a performance gain, some tasks are not good candidates for being implemented in hardware (as a general rule you need a lot of parallelism to make it worth it). As an overly simple example, implementing hardware RSA and hoping for a significant speedup doesn't make sense because there isn't really much parallelism and it's usually only used to encrypt keys, but something like AES or SHA might benefit from a good hardware implementation because there is much more parallelism to be had and they are used to encrypt much larger amounts of data.
To add even more complexity, the compilers can be obscenely finicky with optimizations.