WRITING
The disruptive PDLC: the gap in our own numbers
Build speed rose about 30-fold against our 2022 baseline. Delivered output rose about four-fold. The seven-fold gap between them is the velocity wall, measured, and closing it means moving the day-to-day onto agents and the people to judgment. This is the forecast.
ReadOutcomes over output: bets until the problem is solved
The velocity wall starts upstream, in how the work gets chosen: when building gets cheap, a ranked list of requests stops being strategy. The scarce thing is a problem with a definition of done.
ReadDisruptive engineering: when PMs ship the code
In Q2, about half of our Product and Engineering contributors shipped production code on their own — including every PM and designer who took part. Christensen's framework is what convinced us to try.
ReadThe velocity wall: what happens after engineering gets fast
AI-first development compresses the PDLC from months to days. If the processes around delivery still run at the old speed, the gains pile up against a velocity wall — a coordination problem disguised as a technology problem.
ReadArtifacts aren't the job: PMs and designers after AI
If engineers no longer hand-write code that AI can generate from a spec, the same logic reaches PMs and designers: are you bringing knowledge, empathy, and common sense — or producing artifacts for handoffs that are disappearing?
ReadBuild to discover: what a one-day build does to a one-month discovery
If AI can co-create specs with you, what do you actually need before you start? Our answer turned out to be domain knowledge, empathy, and common sense — and it removed most of our discovery phase.
ReadAI-first: the bottleneck is the process, not the prompts
AI helps your engineers generate code quickly, but it keeps missing requirements, and stories close only a little faster. If that sounds familiar, you aren't operating AI-first — you got better at prompting.
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