Starting in early 2026, feature branch throughput skyrocketed while the main branch remained stagnant. Why is code generated by agents harder to review than code written by humans? How are spec-driven processes and sandboxes taking shape? And what has the unit cost of software evolved into?
When code generation is practically free, what’s scarce is the confidence that the code is correct. Why have strict typing and finicky compilers suddenly become an advantage? Why does Python still dominate, and what is the true cost of each faulty loop?
This debate often devolves into an emotional one. When viewed from the perspective of the cost of fixing errors, things become much clearer.
Every approach to the problem of memory deallocation comes at the cost of something else: latency, throughput, or the programmer’s effort.
All assignments are explicit; there is no operator overloading and no hidden control flow. This is an approach that goes against the prevailing trend.
Although it was created for the web, WebAssembly is currently most useful on servers and in plugin systems.
It's not about speed. The key is to catch an entire class of errors at once during compilation.
Most critical kernel vulnerabilities stem from memory errors. Introducing a memory-safe language addresses the root cause.
Both compile to machine code and are suitable for the service. The key difference lies in tail latency and the speed at which new users can get started.
A modern project brings with it thousands of indirect dependencies. Each one is a gateway you’ve never considered.
Software composition inventories are becoming mandatory in many places. They are not just paperwork—they are incident response tools.
