Browse Comments — Clean (de-noised)
Close reading of the corpus at each pipeline stage: raw → clean → relevant → coded.
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Erik Fehn Game on!
Have u tried it yourself or just circulating marketing fluff Alvin Foo
Vijay Arora With AI you are not only solving business problems but creating more businesses with ease, It is a blessing for people who want to build but for engineers who were only looking to manage systems not so much
This is where AI is becoming really interesting. The shift is no longer just human → AI assistant, but human → AI teams. I think the biggest transition ahead isn't replacing developers — it's changing the role of developers. The future engineer may spend less time writing every line of code and more time defining goals, constraints, workflows, and orchestrating specialized agents. But there's also a second challenge: coordination. More agents don't automatically mean better outcomes. Memory, context sharing, decision quality, and execution consistency become critical. That's one of the ideas we're thinking about with Autoflowly: not just creating agents, but helping founders and teams orchestrate systems of agents that can collaborate around building products and businesses. Interesting times ahead. The question may no longer be: "How good is your AI?" It may become: "How well does your AI team work together?" 🚀
every time I see these posts about how an AI tool can work on its own for hours and produce something great I have to laugh. In my experience, it always makes some very bad decisions and needs a lot of hand holding. If you car about the result, you have to provide a lot more than a one page input, just like human developers. AI is a great accelerator, but it still requires a lot of review from a human developer. They simply have no common sense
The interesting shift is that engineering leverage is increasingly coming from coordination and system design, not just the amount of code one person can write.