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My day-to-day coding looks very different from what it was a few years ago. Today, you'll learn about my voice-to-code workflow and how I leverage smart tools to have so much free time that I feel guilty for "not working enough." Seriously.
The blog post: https://thebootstrappedfounder.com/from-code-writer-to-code-editor-my-ai-assisted-development-workflow/The podcast episode: https://tbf.fm/episodes/395-from-code-writer-to-code-editor-my-ai-assisted-development-workflow
Check out Podscan, the Podcast database that transcribes every podcast episode out there minutes after it gets released: https://podscan.fmSend me a voicemail on Podline: https://podline.fm/arvid
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Here are a few tools I use. Using my affiliate links will support my work at no additional cost to you.- Notion (which I use to organize, write, coordinate, and archive my podcast + newsletter): https://affiliate.notion.so/465mv1536drx- Riverside.fm (that's what I recorded this episode with): https://riverside.fm/?via=arvid- TweetHunter (for speedy scheduling and writing Tweets): http://tweethunter.io/?via=arvid- HypeFury (for massive Twitter analytics and scheduling): https://hypefury.com/?via=arvid60- AudioPen (for taking voice notes and getting amazing summaries): https://audiopen.ai/?aff=PXErZ- Descript (for word-based video editing, subtitles, and clips): https://www.descript.com/?lmref=3cf39Q- ConvertKit (for email lists, newsletters, even finding sponsors): https://convertkit.com?lmref=bN9CZw
Arvid discusses the transformative journey from traditional code writing to a new workflow facilitated by AI tools. He emphasizes how AI empowers developers to act more as editors of code rather than writers, fundamentally changing their role in software development.
He outlines his day-to-day coding routine, detailing his voice-to-code workflow and how using tools like Whisperflow improves productivity by allowing him to dictate specifications instead of typing. Arvid explains the 40-20-40 time breakdown where 40% of the time is spent preparing prompts, 20% is waiting for AI code generation, and the last 40% is reviewing the code.
The importance of creating detailed prompts for AI coding assistants is stressed. Arvid explains that the more context provided in prompts, the better the results. He often repeats critical elements to ensure the AI understands vital aspects of the code, which results in fewer errors.
In discussing code output from AI, Arvid insists that every piece of generated code must be understood, showcasing the necessity of reviewing and verifying AI-generated content. He highlights the need to check for minor errors and emphasizes that understanding generated code is crucial.
Beyond coding, Arvid shares how he also employs conversational AI for handling operational challenges and non-coding tasks, illustrating the broad applicability of AI in software development.
Arvid concludes by likening today's AI-assisted coding to the early days of writing code and expresses optimism about future improvements. He encourages listeners to adapt to AI tools to stay competitive in software development.
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