Kilocode is developing a new command-line tool called "Roo" designed to encompass the functionalities of both traditional CLIs and modern interactive tools like Fig. Roo aims to provide a seamless experience, allowing users to fluidly transition between typing commands and utilizing interactive elements like autocomplete, suggestions, and visual aids. The goal is to combine the speed and scriptability of CLIs with the user-friendliness and discoverability of graphical interfaces, creating a more efficient and intuitive command-line experience that caters to both novice and expert users. They are building upon the foundation of existing tools, incorporating successful aspects of both paradigms, and plan to open-source Roo in the future.
The author details their evolving experience using AI coding tools, specifically Cline and large language models (LLMs), for professional software development. Initially skeptical, they've found LLMs invaluable for tasks like generating boilerplate, translating between languages, explaining code, and even creating simple functions from descriptions. While acknowledging limitations such as hallucinations and the need for careful review, they highlight the significant productivity boost and learning acceleration achieved through AI assistance. The author emphasizes treating LLMs as advanced coding partners, requiring human oversight and understanding, rather than complete replacements for developers. They also anticipate future advancements will further blur the lines between human and AI coding contributions.
HN commenters generally agree with the author's positive experience using LLMs for coding, particularly for boilerplate and repetitive tasks. Several highlight the importance of understanding the code generated, emphasizing that LLMs are tools to augment, not replace, developers. Some caution against over-reliance and the potential for hallucinations, especially with complex logic. A few discuss specific LLM tools and their strengths, and some mention the need for improved prompting skills to achieve better results. One commenter points out the value of LLMs for translating code between languages, which the author hadn't explicitly mentioned. Overall, the comments reflect a pragmatic optimism about LLMs in coding, acknowledging their current limitations while recognizing their potential to significantly boost productivity.
Summary of Comments ( 25 )
https://news.ycombinator.com/item?id=43642212
Hacker News users discuss the ambition of Roo and Cline, questioning the feasibility of creating a true "superset" of developer tools. Several commenters express skepticism about unifying diverse tools with vastly different functionalities and workflows. Some suggest focusing on specific niches or integrations rather than aiming for an all-encompassing solution. Concerns about vendor lock-in and the potential for a bloated, complex product are also raised. Others express interest in the project, particularly the proposed integration of static and dynamic analysis, and encourage the developers to prioritize a strong user experience. The need for clear differentiation from existing tools and demonstration of concrete benefits is highlighted as crucial for success.
The Hacker News post titled "Roo or Cline? We're building a superset" with the ID 43642212 has generated several comments discussing the proposed Roo programming language and its comparison to Cline.
Several commenters expressed skepticism about the value proposition of Roo. One commenter questioned the need for another language, especially one that seemed to be positioning itself as a "superset" of existing languages like Python and JavaScript. They argued that often such projects become overly complex and difficult to maintain, and wondered what specific problems Roo was trying to solve that couldn't be addressed by improving existing languages or tools. This sentiment was echoed by others who expressed a preference for focusing on improving existing ecosystems rather than creating new ones.
The maintainability of a language that combines Python, JavaScript and aims for native performance was also a concern. One commenter highlighted the difficulty of keeping such a project up-to-date with the evolution of its underlying components, suggesting it would be a significant ongoing effort.
Another point of discussion centered around the claimed performance benefits of Roo. Commenters requested benchmarks or more concrete evidence to support the claim of "native performance," especially given the complexity introduced by combining different language paradigms. The lack of open-sourcing also drew criticism, making it harder for the community to evaluate the claims and contribute.
Some commenters questioned the chosen name "Roo," finding it unmemorable or difficult to search for. Alternative suggestions were offered, highlighting the importance of a strong and easily searchable name for a new programming language.
There was interest in the potential of Roo, with some commenters appreciating the ambition of the project and expressing curiosity about its development. However, the overall sentiment leaned towards cautious skepticism, with many emphasizing the need for more concrete details and open-sourcing to gain wider community acceptance and support. The lack of specific use cases beyond general performance improvements also contributed to this skepticism.