카카오 / agile

AI TOP 100이 우리에게 남긴 것들 (opens in new tab)

The Kakao AI Native Strategy team successfully developed a complex competition system for the "AI TOP 100" event in just two weeks by replacing traditional waterfall methodologies with an AI-centric approach. By utilizing tools like Cursor and Claude Code, the team shifted the developer’s role from manual coding to high-level orchestration and validation. This experiment demonstrates that AI does not replace developers but rather redefines the "standard" of productivity, moving the focus from execution speed to strategic decision-making. ### Rapid Prototyping as the New Specification * The team eliminated traditional, lengthy planning documents and functional specifications. * Every team member was tasked with creating a working prototype using AI based on their own interpretation of the project goals. * One developer produced six different versions of the system independently, allowing the team to "see" ideas rather than read about them. * Final requirements were established by reviewing and merging the best features of these functional prototypes, significantly reducing communication overhead. ### AI-Native Development and 99% Delegation * The majority of the codebase (over 99%) was generated by AI tools like Claude Code and Cursor, with developers focusing on intent and review. * One developer recorded an extreme usage of 200 million tokens in a single day to accelerate system completion. * The high productivity of AI allowed a single frontend developer to manage the entire UI for both the preliminary and main rounds, a task that typically requires a much larger team. * The development flow moved away from linear "think-code-test" patterns to a "dialogue-based" implementation where ideas were instantly turned into code. ### PoC-Driven Development (PDD) * The team adopted a "Proof of Concept (PoC) Driven Development" model to handle high uncertainty and tight deadlines. * Abstract concepts were immediately fed into AI to generate functional PoC code and architectural drafts. * The human role shifted from "writing from scratch" to "judging and selecting" the most viable outputs generated by the AI. * This approach allowed the team to bypass resource limitations by prioritizing speed and functional verification over perfectionist documentation. ### Human Governance and the Role of Experience * Internal conflicts occasionally arose when different AI models suggested equally "logical" but conflicting architectural solutions. * Senior developers played a critical role in breaking these deadlocks by applying real-world experience regarding long-term maintainability and system constraints. * While AI provided the "engine" for speed, human intuition remained the "steering wheel" to ensure the system met specific organizational standards. * The project highlighted that as AI handles more of the implementation, a developer’s ability to judge code quality and architectural fit becomes their most valuable asset. This project serves as a blueprint for the future of software engineering, where AI is treated as a peer programmer rather than a simple tool. To stay competitive, development teams should move away from rigid waterfall processes and embrace a PoC-centric workflow that leverages AI to collapse the distance between ideation and deployment.

POPM 과정은 어떻게 하나의 ‘제품’이 되었나 (opens in new tab)

Kakao developed its internal POPM (Product Owner/Product Manager) training program by treating the curriculum itself as an evolving product rather than a static lecture series. By applying agile methodologies such as data-driven prioritization and iterative versioning, the program successfully moved from a generic pilot to a structured framework that aligns teams through a shared language of problem-solving. This approach demonstrates that internal capability building is most effective when managed with the same rigor and experimentation used in software development. ## Strategic Motivation for POPM Training * Addressed the inherent ambiguity of the PO/PM role, where non-visible tasks often make it difficult for practitioners to define their own growth or impact. * Sought to resolve the disconnect between strategic problem definition (PO) and tactical execution (PM) within Kakao’s teams. * Prioritized the creation of a "common language" to allow cross-functional team members to define problems, analyze metrics, and design experiments under a unified structure. ## Iterative Design and Versioning * The program transitioned through multiple "versions," starting with an 8-session pilot that covered the entire lifecycle from bottleneck exploration to execution review. * Based on participant feedback regarding high fatigue and low efficiency in long presentations, the curriculum was condensed into 5 core modules: Strategy, Metrics, Experiment, Design, and Execution. * The instructional design shifted from "delivering information" to "designing a rhythm," utilizing a "one slide, one question, one example" rule to maintain engagement. ## Data-Driven Program Refinement * Applied a "Product Metaphor" to education by calculating "Opportunity Scores" using a matrix of Importance vs. Satisfaction for each session. * Identified "Data/Metrics" as the highest priority for redesign because it scored high in importance but low in satisfaction, indicating a structural gap in the teaching method. * Refined the "features" of the training by redesigning worksheets to focus on execution routines and converting mandatory practice tasks into selective, flexible modules. ## Structural Insights for Organizational Growth * Focused on accumulating "structure" rather than just training individuals, ensuring that even as participants change, the framework for defining problems remains consistent within the organization. * Designed practice sessions to function as "thinking structures" rather than "answer-seeking" exercises, encouraging teams to bring their training insights directly into actual team meetings. * Prioritized scalability and simplicity in the curriculum to ensure the structure can be adopted across different departments with varying product needs. To build effective internal capabilities, organizations should treat training as a product that requires constant maintenance and versioning. Instead of focusing on one-off lectures, leaders should design structural "rhythms" and feedback loops that allow the curriculum to evolve based on the actual pain points of the practitioners.