2026: The Great Engineering Divergence
This article strongly resonates and has clear angles for your perspective
Quick Take
This perfectly aligns with Brian's experience building AI-powered dev workflows and his focus on automation/productivity. The idea that code generation speed creates new bottlenecks (rather than solving everything) is exactly the kind of nuanced take Brian would want to explore with concrete examples from his fintech work and side projects.
Relevant Domains
Blog Angles
"Why AI Made My Fintech Deployments Slower (And How We Fixed It)"
Faster coding with AI creates deployment pipeline bottlenecks that require rethinking your entire workflow, not just adding Copilot.
Specific metrics from his credit-card offers platform showing how AI-generated code volume impacted review/testing cycles.
"The Side Project Advantage in the AI Coding Era"
Solo developers building side projects can redesign their entire stack for AI-first workflows faster than enterprise teams stuck with legacy processes.
Contrasting his print-on-demand automation project (clean AI workflow) vs. constraints at his fintech job.
"From Webhook Hell to AI Heaven: Rebuilding Our Integration Pipeline"
AI code generation works best when you redesign your architecture to minimize the human review surface area.
Specific example of refactoring webhook integrations to be more AI-generation-friendly.
Key Quotes
Teams that redesign processes and tooling end-to-end will pull far ahead
Organizations that do not adapt will be stuck despite having more code
The Great Engineering Divergence