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sklinkert

100%. The 'sunk cost fallacy' was my biggest blocker. When the agent flagged 1,500 articles for deletion, my immediate human reaction was, 'But I paid freelancers $X,XXX for those!'

The AI just looked at the data: Traffic = 0. Authority = Diluted. Action = Delete.

It decoupled the execution from the sentiment. I think that's the killer feature of agentic workflows because it forces you to argue with logic rather than anxiety.

Show HN: Go-DDD: Production-ready DDD patterns and clean architecture in Go

https://github.com/sklinkert/go-ddd

Hey HN! I've been working on a comprehensive example of Domain-Driven Design implementation in Go that demonstrates clean architecture principles in practice.The repo includes:Hexagonal architecture with clear separation of concerns - CQRS (Command Query Responsibility Segregation) patterns for scalability & reliability - Event sourcing examples - Operating only on validated domain...

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Show HN: Domain Driven Design Template in Golang

https://github.com/sklinkert/go-ddd

go-ddd is a reference implementation/template repository demonstrating the Domain Driven Design (DDD) approach in Golang.This project aims to help developers and architects understand the DDD structure, especially in the context of Go, and how it can lead to cleaner, more maintainable, and scalable codebases.It's an opinionated approach, influenced by other patterns like CQRS.

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Re:Show HN: AI for researching personal health issues on Saturday March 30, 2024 @04:41AM (#39872976)
Yeah, a preliminary check that asks GPT if the request is about a medical issue might prevent it