Mike Fishbein on X: "This is my personal software factory. It turns ideas into working products while I sleep. No babysitting coding agents with prompts all day. Cursor and Claude Code made writing code way easier. The harder problem is building a system that can context engineer and manage itself. My factory starts with a Skill called `/factory`. It's the foreman that remembers where the project stands and sends in the right worker for the job. Factory runs this assembly line: 1. `/factory-plan` - the interviewer Reads the existing codebase (if there is one), extracts missing context from me via interview, and writes a product brief. 2. `/factory-plan` - the planner The same skill turns the approved brief into small, testable features and development tasks. 3. `/factory-tests` - the professor Before anyone writes code, every task gets an exam. This skill defines the success criteria for each task, and how the coding agent can prove to itself that what it built works or needs iteration. 4. `/factory-explain` - the presenter Explains the plan to me like I'm 10, with visual metaphor and mermaid charts. Now that coding agents can write more code, faster than any human ever could, the new bottleneck is human understanding of the code. This skill solves that. 5. `/factory-handoff` - from CTO to SWE This packages the brief, plan, tests, safety rails, and stop conditions into one work order. Factory uses the best models for the planning in the previous steps above, then hands the work order to a lower token usage model like Grok 4.5 for execution. 6. Cursor or Claude Code `/loop` - the coffee The night shift picks one task, builds it, takes its exam, records what happened, iterates if needed, then moves onto the next task. If it gets stuck, circuit breakers stop it from confidently digging a deeper hole while I sleep. 7. `/factory-review` - the teacher grades the homework The student doesn't grade it's own homework. A fresh agent that never met the builder tries to break the result. The reviewer rereads the original plan, reruns tests, and finds anything that's broken. 8. `/auto-loom-proof` - shows the evidence Uses browser use and screen records itself performing the tests and adds an 11labs voiceover explaining what's being proven. It sends me the narrated demo video. 9. `/factory-explain` - the code The factory updates a plain-language owner's manual explaining what actually got built. I understand my own codebase, so I can make decisions without becoming the bottleneck or outsourcing my thinking to AI. NOTE ON BUILDING AI Cursor and Claude Code have made writing code dramatically easier. But getting AI to work reliably and at scale for you can't be fully automated. LLM-as-judge helps, but a judge needs a rubric, examples, and input from someone with subject matter expertise. You still need a human reviewing the work and teaching the system how to perform better. You can check out my factory on github in the post below." / X
Mike Fishbein (@mfishbein) on X
Mike Fishbein介绍了一套“个人软件工厂”，通过多个AI技能将创意自动转化为可运行产品，减少持续提示和监督编程代理的需要。该流程涵盖需求访谈、产品规划、测试标准制定、通俗解释、任务交接、自动编码迭代、独立审查、视频验证及文档更新，并通过熔断机制避免代理在受阻时持续犯错。系统在规划阶段使用高能力模型，在执行阶段使用成本更低的模型，同时由独立代理重新测试和审查成果。尽管AI显著提升了编码效率，作者强调可靠规模化仍离不开专家制定评估标准、人工审核，以及持续教导系统改进。