产品构建、开源、增长和开发者商业化
This collection features articles and community discussions in the 独立开发 space, focusing on real-world engineering scenarios, tool selection, practical paths, and risk boundaries.
The page is continuously updated and serves as a learning roadmap, technology selection reference, and technical review entry point.
The hardest part of indie development is not coding, but validating an idea at the lowest possible cost. AI has driven that cost to an unprecedented low. This article presents a closed-loop workflow from a one-sentence idea to the first real user feedback, showing what AI can handle at every step.
Centered on independent development, Next.js technology trends, engineering practices, and the indie developer perspective.
Technical trends, engineering practices, and an independent developer's perspective on independent development and open source.
Centered on indie development and AI—technical trends, engineering practices, and the indie-developer perspective.
Covers tech trends, engineering practices, and indie developer perspectives around indie development and Next.js.
Centered on the technical trends, engineering practices, and indie developer perspectives of indie development and AI.
Centered on the technical trends, engineering practices, and indie developer perspectives of indie development and open source.
Neither bot visits nor traditional impressions directly prove a page is cited in AI answers. This article establishes a repeatable question panel, citation normalization, and intervention records to avoid manufacturing GEO conclusions from scattered screenshots.
A concierge pilot isn't pretending the product is done; with explicit disclosure of human involvement, it uses a few real customers to validate inputs, delivery standards, exception handling, repeat purchases, and unit economics, then progressively automates stable steps.
A single robots.txt Allow or Disallow can simultaneously affect different kinds of automated access. This article uses a versioned agent registry, policy compilation, and real-log testing to avoid blocking search or exposing sensitive paths.
Interviews are a technical discipline, and grinding coding problems is not enough. This guide covers algorithms and system design, project experience, behavioral interviews with STAR, questions for the interviewer, common traps, and an end-to-end checklist from resume to offer.
Feature voting and customer volume easily mislead a roadmap. This article builds an auditable AI feature evidence scorecard that puts problem frequency, outcome value, real commitment, reachable users, delivery capability, and risk into one decision record.