Pendiri Claude Code Mengungkap Prediksi Terbaru: Divisi Kerja Tim Dirombak di Era AI, "Lima Tipe Orang" Ini Paling Dibutuhkan

marsbitPublished on 2026-06-30Last updated on 2026-06-30

Abstract

Dengan maraknya Agent Coding yang membentuk ulang industri perangkat lunak, perubahan tidak hanya terjadi pada peran "insinyur" tradisional. Boris Cherny, pemimpin tim Claude Code di Anthropic, mengamati bahwa fungsi teknik, produk, desain, dan ilmu data semakin menyatu. Dia mengusulkan lima peran baru berbasis pola perilaku, tidak terikat pada jabatan tradisional: 1. **The Prototyper (Pembuat Prototipe):** Menghasilkan banyak ide dan konsep baru, fokus pada kuantitas dan disruptif. 2. **The Builder (Pembangun):** Mengubah prototipe kasar menjadi produk atau infrastruktur yang siap produksi dan dapat diskalakan. 3. **The Sweeper (Pembersih):** Menyederhanakan antarmuka, mengatur ulang kode, dan menghapus fitur berlebihan untuk meningkatkan kinerja dan kemampuan pemeliharaan. 4. **The Growth (Pertumbuhan):** Mengiterasi produk yang sudah jadi agar lebih dekat dengan pasar, meningkatkan retensi pengguna, dan mengubahnya dari "dapat digunakan" menjadi "diperlukan". 5. **The Maintainer (Pemelihara):** Memastikan keamanan, keandalan, efisiensi, dan ketahanan sistem yang matang dalam jangka panjang. Peran-peran ini tidak eksklusif. Satu orang dapat merangkul beberapa peran (misalnya, 1+3 atau 2+3) yang berubah sesuai tahap produk atau proyek. Tim yang sehat membutuhkan kombinasi peran yang berbeda bergantung pada kematangan produk: produk baru membutuhkan peran 1,2,3; produk yang sedang tumbuh membutuhkan 2,3,4 dengan beberapa 5; produk matang membutuhkan 3,4,5 dengan beberap...

Dalam situasi di mana Agent Coding tengah booming dan membentuk ulang industri perangkat lunak, dunia industri tampaknya telah mulai menerima fakta yang tak terbantahkan bahwa "insinyur" telah berubah. Namun kenyataannya, yang berubah mungkin bukan hanya posisi "insinyur" saja, perubahan yang lebih mendalam sedang terjadi secara diam-diam di balik struktur organisasi tim...

Baru-baru ini, Boris Cherny, kepala tim Claude Code di Anthropic, mengajukan sebuah pengamatan yang menarik di X.

Dia mencatat, seiring dengan semakin menyatunya fungsi-fungsi seperti teknik, produk, desain, dan ilmu data, dia terus berpikir, ke arah seperti apa peran-peran ini akan berkembang di masa depan? Mengambil tim Claude Code sebagai contoh, "label jabatan" tradisional di dalam tim sedang dihapus secara total, digantikan oleh 5 jenis peran baru "tanpa ikatan" yang didasarkan pada pola perilaku: Prototyper (Si Pembuat Purwarupa), Builder (Si Pembangun), Sweeper (Si Pembersih), Growth (Si Pertumbuhan), Maintainer (Si Pemelihara).

Prototyper (Si Pembuat Purwarupa): Bertanggung jawab utama untuk mengajukan ide-ide baru, terus menghasilkan banyak kreativitas, di mana sebagian besar pada akhirnya tidak akan diluncurkan. Dengan kata lain, mereka mengejar kuantitas dan sifat disruptif dari ide-ide, tanpa terjebak apakah setiap ide harus direalisasikan.

Builder (Si Pembangun): Bertangg jawab utama untuk mengubah ide-ide yang tersebar atau purwarupa kasar, dengan cepat menjadi produk atau infrastruktur berkinerja tinggi yang benar-benar dapat digunakan di lingkungan produksi dan dihadapan banyak pengguna. Singkatnya, mereka bertanggung jawab menyelesaikan lompatan sulit dari 0.1 ke 1.

Sweeper (Si Pembersih): Bertanggung jawab utama untuk "melakukan pengurangan". Efek samping paling menakutkan di era AI adalah pembengkakan kode dan fungsi yang berlebihan. Tugas Sweeper adalah membersihkan, menyederhanakan antarmuka pengguna, menyederhanakan, merefaktor kode dan arsitektur sistem yang berantakan, menghapus fungsi-fungsi berlebihan yang tidak perlu, untuk mendapatkan kinerja dan kemudahan pemeliharaan sistem yang tinggi.

Growth (Si Pertumbuhan): Mengambil alih produk yang sudah terbentuk dan dibangun. Saat produk memasuki pasar, Growth bertanggung jawab untuk iterasi berkelanjutan dengan langkah-langkah kecil dan cepat, harus peduli: Bagaimana agar produk lebih dekat dengan pasar? Bagaimana membuat pengguna lebih ingin bertahan? Bagaimana membuat produk dari "bisa digunakan" menjadi "dibutuhkan". Namun, peran ini tidak setara dengan operasi pertumbuhan tradisional, melainkan lebih mendekati kombinasi kemampuan produk, data, pemahaman pengguna, dan eksperimen.

Maintainer (Si Pemelihara): Bertanggung jawab atas operasional jangka panjang dari sistem yang sudah matang. Mereka belum tentu terlibat dalam mengejar fitur baru yang cemerlang, tetapi sangat memperhatikan keamanan, keandalan, efisiensi operasional yang ekstrem, dan ketahanan sistem, memastikan layanan tetap stabil seperti batu karang dalam kondisi lalu lintas ekstrem apa pun.

Namun perlu diperhatikan, kelima peran ini tidak sesuai dengan jabatan tradisional. Artinya, mereka tidak seperti dalam manajemen organisasi tradisional, di mana peran seseorang tetap pada gelar jabatannya.

Boris Cherny percaya, banyak orang mungkin menjangkau dua peran, bahkan terkadang menjangkau tiga peran.

"Saya juga menyadari bahwa peran-peran ini tidak benar-benar terikat pada jabatan spesifik. Misalnya, di dalam Anthropic, beberapa desainer lebih sesuai dengan tipe 1, beberapa lebih sesuai dengan tipe 2, dan beberapa lebih sesuai dengan tipe 3; begitu pula dengan insinyur, manajer produk, ilmuwan data."

Ini berarti, dalam tim yang diperkuat AI yang efisien, banyak anggota bukan lagi "sekrup tunggal". Seorang desainer bisa menjadi Prototyper, juga bisa menjadi Sweeper; seorang insinyur bisa menjadi Builder, juga bisa menjadi Maintainer; seorang manajer produk bisa mengambil peran Growth, juga bisa menjadi Prototyper; seorang ilmuwan data mungkin tidak hanya melakukan analisis, tetapi juga bisa langsung terlibat dalam pertumbuhan produk dan optimisasi sistem...

Dengan kata lain, cara tim melihat seseorang di masa depan mungkin akan berubah. Pertanyaan di masa lalu mungkin terutama "Anda di posisi apa"? Sedangkan di masa depan atau sekarang sedang berubah menjadi "Anda dapat mendorong tahap mana dalam siklus hidup produk"?

Boris Cherny menganalisis, cara kombinasi peran yang dibutuhkan oleh tim yang sehat ini tergantung pada tahap di mana produk berada:

Sebuah produk yang benar-benar baru, belum menemukan kesesuaian dengan pasar, membutuhkan orang yang ahli dalam peran tipe 1, 2, 3;

Sebuah produk yang sedang tumbuh, telah menemukan kesesuaian dengan pasar, membutuhkan peran tipe 2, 3, 4, dan dilengkapi dengan beberapa peran tipe 5;

Sebuah produk yang sudah memiliki kesesuaian pasar yang kuat, membutuhkan peran tipe 3, 4, 5, dan mempertahankan beberapa peran tipe 2.

"Mungkin peran produk di masa depan akan lebih seperti ini, bukan pembagian jabatan berdasarkan bidang keahlian seperti saat ini."

Dan begitu postingan ini diterbitkan, segera menimbulkan diskusi hangat di antara netizen, mayoritas menyetujui.

"Ini sangat sesuai dengan keadaan kerja orang yang sebenarnya. Di beberapa proyek, saya benar-benar kombinasi 1+3, dan di proyek lain, saya hampir murni 4. Nama jabatan tidak pernah benar-benar merangkum ini."

Seorang ilmuwan data juga "memberi kesaksian", mengatakan bahwa sebagai ilmuwan data, dia sering menemukan dirinya melakukan pekerjaan tipe Sweeper, sambil membangun produk dengan selera ilmu data. "Jadi, apakah ini berarti saya tipe 2+3?"

Netizen Kun Chen@kunchenguid mengatakan, merasakan hal yang sama. Dia mengatakan bahwa dirinya selalu tidak terlalu suka mendefinisikan "prototipe peran" ini, karena orang mudah melihatnya dan berpikir: "Oh, ternyata inilah saya", lalu berhenti merefleksikan diri. Sedangkan dalam kenyataannya, "Peran seseorang seringkali perlu berubah bersama proyek."

Dia memberi contoh, misalnya saat memulai proyek baru, dia biasanya akan menjadi Prototyper dan Builder; tetapi dengan cepat, ketika hal-hal yang kasar dan tidak sempurna mulai menjadi hambatan, dia akan berubah menjadi Sweeper. Dan seiring proyek semakin matang, dia akan beralih ke Growth dan Maintainer... "Jika saya membatasi diri pada satu peran tertentu, maka saat proyek mencapai tahap tertentu, saya harus melepaskannya."

Dan realitas lainnya adalah, sekarang orang semakin sering mengerjakan banyak proyek secara bersamaan, yang menuntut orang dapat memainkan peran berbeda di proyek yang berbeda. "Mengelompokkan diri ke dalam prototipe tetap tertentu, seringkali membatasi seseorang untuk memperluas ambisi."

Jadi sarannya adalah: Tetap fleksibel, fokus pada hal terpenting yang dibutuhkan untuk mencapai tujuan, jangan terlalu memikirkan batasan peran. Karena batasan ini hanya akan terus kabur seiring waktu.

Boris Cherny menanggapi hal ini, ini benar-benar sesuai dengan perasaannya: "Sepenuhnya setuju. Peran seringkali terus berubah seiring waktu dan tahap proyek."

Ada juga netizen yang menyatakan keraguan, "Mengingat masalah AI menulis kode pada dasarnya sudah terpecahkan, mengapa masih membutuhkan peran seperti Builder dan Sweeper? Tidakkah kita bisa langsung meminta Claude untuk menjalankan siklus berulang?"

Menanggapi hal ini, penjelasan Boris Cherny adalah, Claude dapat membantu menyelesaikan hal-hal ini dalam berbagai tingkat, dan akan semakin kuat seiring waktu. Dan saat ini, Claude hari ini sudah cukup baik dalam menangani dua jenis pekerjaan Sweeper dan Builder.

Lalu bagaimana dengan Anda, bagaimana melihat perubahan peran jabatan ini? Selamat berkomentar dan berdiskusi di kolom komentar!

Referensi link:

https://x.com/bcherny/status/2071379474277613732

https://x.com/kunchenguid/status/2071382977628795289

Artikel ini berasal dari akun WeChat publik "Machine Heart" (ID:almosthuman2014), penulis: yang memperhatikan AI

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Related Questions

QMenurut Boris Cherny, apa saja lima peran 'non-label' baru yang muncul dalam tim yang diubah oleh AI, dan apa fokus utama masing-masing?

ALima peran tersebut adalah: 1) The Prototyper (Prototiper): fokus menghasilkan banyak ide dan konsep baru, tidak semua harus diluncurkan. 2) The Builder (Pembangun): mengubah prototipe kasar menjadi produk atau infrastruktur yang siap produksi. 3) The Sweeper (Pembersih): menyederhanakan antarmuka, kode, dan arsitektur, menghapus redundansi untuk kinerja dan pemeliharaan yang lebih baik. 4) The Growth (Pendorong Pertumbuhan): mengiterasi produk yang sudah jadi untuk mendekatkannya ke pasar dan meningkatkan retensi pengguna. 5) The Maintainer (Pemelihara): memastikan keamanan, keandalan, efisiensi, dan ketahanan sistem yang matang.

QBagaimana Boris Cherny menjelaskan bahwa peran-peran baru ini berbeda dari jabatan atau posisi tradisional dalam sebuah tim?

ABoris Cherny menjelaskan bahwa kelima peran ini tidak terikat pada jabatan tradisional seperti insinyur, manajer produk, atau desainer. Seseorang dapat menjalani beberapa peran sekaligus (misalnya, seorang desainer bisa menjadi Prototyper dan Sweeper), dan peran seseorang dapat berubah sesuai dengan tahap produk atau proyek yang sedang dikerjakan.

QMenurut analisis Boris Cherny, bagaimana komposisi peran yang dibutuhkan oleh sebuah tim yang sehat berubah sesuai dengan tahapan produk?

AKomposisinya bergantung pada tahap produk: 1) Produk baru yang belum menemukan product-market fit membutuhkan orang yang ahli dalam peran Prototyper, Builder, dan Sweeper. 2) Produk yang sedang tumbuh dan telah menemukan product-market fit membutuhkan Builder, Sweeper, Growth, dengan beberapa Maintainer. 3) Produk yang sudah memiliki product-market fit kuat membutuhkan Sweeper, Growth, dan Maintainer, dengan tetap mempertahankan beberapa Builder.

QApa tanggapan dan contoh nyata dari seorang ilmuwan data yang dikutip dalam artikel terkait dengan peran-peran baru ini?

ASeorang ilmuwan data yang dikutip mengatakan bahwa dia sering menemukan diri melakukan pekerjaan seperti Sweeper (membersihkan dan menyederhanakan), sambil juga membangun produk dengan pendekatan khas ilmu data. Dia bertanya-tanya apakah ini menjadikannya kombinasi peran Builder dan Sweeper (tipe 2+3).

QBagaimana Boris Cherny menanggapi keraguan bahwa AI (seperti Claude) dapat sepenuhnya menggantikan peran seperti Builder dan Sweeper?

ABoris Cherny menjawab bahwa Claude memang dapat membantu dalam berbagai tingkat untuk semua peran tersebut dan kemampuannya akan terus meningkat. Saat ini, Claude sudah cukup baik dalam membantu tugas-tugas peran Sweeper dan Builder, tetapi peran manusia tetap diperlukan dalam ekosistem tim yang diubah oleh AI.

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What is $S$

What is AGENT S

Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

753 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

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