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Pernah minta AI membuat fitur sederhana, tapi yang keluar malah kode super kompleks yang merusak fitur lain? 🤯
Saat kita langsung melompat dari "Ide" ke "Kode" (vibe coding) dengan AI, ada dua musuh besar yang sering bikin proyek berantakan:
1️⃣ "Context Lost" (AI Lupa Ingatan)
Semakin panjang kodenya, AI sering kali "lupa" dengan aturan awal. Awalnya sepakat pakai Clean Architecture dan penamaan database tertentu, eh di tengah jalan AI malah bikin aturan sendiri. Hasilnya? Kode jadi inkonsisten dan susah di-maintain.
2️⃣ "Scope Creep" (Fitur Siluman)
Rencana awal di dokumen cuma minta dibikinkan tombol "Login Email". Tapi tiba-tiba AI berinisiatif menambahkan integrasi Google Login, Apple Login, sampai sistem caching pakai Redis. Kelihatannya keren, tapi ini bikin over-engineering, membengkakkan budget waktu, dan memicu bug baru yang tidak terprediksi!
Inilah kenapa kita harus memperlakukan AI bukan sekadar sebagai "mesin ketik", melainkan sebagai tim engineering yang butuh disiplin!
Sebagai solusinya, Anda dapat langsung mencoba metodologi SDLC menggunakan Custom Agent berbasis Spec Driven Development yang telah dirangkum secara komprehensif dalam repositori proyek Awesome Copilot Indonesia! 🚀
Di dalam metodologi ini, berbagai tugas diorkestrasi ke beberapa Agent spesifik untuk "menjaga kewarasan" proyek sebelum satu baris kode pun ditulis:
🕵️♂️ Clarification Analyst: Menginterogasi dokumen ide awal agar tidak ada celah ambiguitas.
🏛 Specification Architect: Mengunci desain arsitektur dan istilah baku (CONTEXT.md) agar AI Developer tidak "lupa ingatan".
📋 Planner Architect: Memecah desain menjadi rencana kerja yang konkret dan terukur.
⚖️ Artifact Consistency Checker: Bertindak sebagai "polisi" yang mengaudit dokumen agar tidak ada Scope Creep atau "fitur siluman" yang menyelinap masuk!
Dengan pendekatan ini, proses pengembangan software dengan AI menjadi jauh lebih aman, terprediksi, dan terstruktur.
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Semua prompt, alur kerja, dan metodologinya sudah terbuka secara open-source. Silakan pelajari dan coba terapkan di proyek Anda:
📖 Baca konsep lengkapnya di Medium: https://medium.com/javascript-indonesia-community/dari-ide-ke-kode-dengan-sdlc-2-0-mengorkestrasi-custom-agent-ai-dalam-metodologi-github-spec-kit-88861eccfa3e
🌐 Eksplorasi Web Repository: https://gulajavaministudio.github.io/awesome-copilot-id/
📦 Catatan Rilis di GitHub (Bantu berikan ⭐️ jika bermanfaat!): https://github.com/GulajavaMinistudio/awesome-copilot-id/releases
Menurut teman-teman, tantangan terbesar apa lagi yang sering kalian temui saat menggunakan AI untuk coding harian? Yuk diskusi di komentar! 👇
#SoftwareEngineering #SpecDrivenDevelopment #VibeCoding #ArtificialIntelligence #SDLC #GitHubCopilot #TechCommunityIndonesia #OpenSource
Have you ever asked an AI to build a simple feature, only to get an overly complex codebase that breaks everything else? 🤯
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When we jump straight from "Idea" to "Code" (aka vibe coding) with AI, we usually face two massive project-killers:
1️⃣ "Context Lost" (AI Amnesia)
As the codebase grows, AI often "forgets" the initial rules. You agreed on Clean Architecture and specific database conventions, but halfway through, the AI makes up its own rules. The result? Inconsistent, unmaintainable code.
2️⃣ "Scope Creep" (Stealth Features)
Your initial document just asked for an "Email Login" button. Suddenly, the AI takes the initiative to add Google Login, Apple Login, and even Redis caching. It looks cool, but it introduces over-engineering, bloats timelines, and triggers unpredictable bugs!
This is exactly why we need to stop treating AI as a mere "typewriter" and start treating it as an engineering team that requires strict discipline!
---
As a solution, you can now try the SDLC methodology using Custom Agents based on Spec-Driven Development, comprehensively packaged in the Awesome Copilot Indonesia project repository! 🚀
---
In this methodology, various tasks are orchestrated across specific Agents to "maintain project sanity" before a single line of code is written:
🕵️♂️ Clarification Analyst: Interrogates your initial product documents to eliminate any ambiguities.
🏛 Specification Architect: Locks down the architectural design and canonical terms (CONTEXT.md) so the AI Developer doesn't suffer from "amnesia".
📋 Planner Architect: Breaks down the design into a concrete, measurable implementation plan.
⚖️ Artifact Consistency Checker: Acts as the "police," auditing documents to ensure no Scope Creep or "stealth features" sneak in!
With this approach, AI-assisted software development becomes significantly safer, more predictable, and highly structured.
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All prompts, workflows, and methodologies are open-source. Feel free to explore and apply them to your projects:
📖 Read the full concept on Medium: https://medium.com/javascript-indonesia-community/dari-ide-ke-kode-dengan-sdlc-2-0-mengorkestrasi-custom-agent-ai-dalam-metodologi-github-spec-kit-88861eccfa3e
🌐 Explore the Web Repository: https://gulajavaministudio.github.io/awesome-copilot-id/
📦 GitHub Release Notes (Drop a ⭐️ if you find it helpful!): https://github.com/GulajavaMinistudio/awesome-copilot-id/releases
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What is the biggest challenge YOU face when using AI for your daily coding? Let’s discuss it in the comments! 👇
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#SoftwareEngineering #SpecDrivenDevelopment #VibeCoding #ArtificialIntelligence #SDLC #GitHubCopilot #TechCommunity #OpenSource
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15 Claude Code Features That Made Me 10x Faster
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Stop Installing Random MCP Servers. Start With These 10.
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GitHub Copilot Code Review: Guidelines, Best Practices, and How to Integrate It into Your PR Workflow
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I Made an AI Agent My Junior Partner and We Divided the Work
https://medium.com/lets-code-future/the-outer-loop-is-yours-74ae01447ce5
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What Is Hermes Agent and Why Is Everyone Talking About It?
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Hermes Agent Is Cool. Running It Safely 24/7 Is the Real Trick.
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OpenCode AI: The Open-Source Coding Agent Revolutionising AI-Assisted Development
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Claude Things Everyone Must Know
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