Productivity Requires Patience and Learning

The path to productivity with new tools is often misunderstood. Users must invest significant time and effort to learn and experiment with these tools rather than expect immediate results. Lack of comprehensive user guides or documentation contributes to a reliance on trial and error, leading to misconceptions and superstition around effective usage practices. Both the absence of structured guidance and the rapidly changing landscape of technology mean that much of the advice encountered can be misleading. There are valuable resources, however, such as the Claude Anthropic Prompting Guide, which stands out for its quality. Emerging features, such as those in tools like CodeInterpreter and Clord, offer innovative ways to create prototypes but still require a learning curve and have limitations that users must navigate.

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The first episode of The Pragmatic Engineer Podcast is out. Expect similar episodes every other Wednesday. You can add the podcast in your favorite podcast player, and have future episodes downloaded automatically.

Listen now on Apple, Spotify, and YouTube.

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On the first episode of the Pragmatic Engineer Podcast, I am joined by Simon Willison.

Simon is one of the best-known software engineers experimenting with LLMs to boost his own productivity: he’s been doing this for more than three years, blogging about it in the open.

Simon is the creator of Datasette, an open-source tool for exploring and publishing data. He works full-time developing open-source tools for data journalism, centered on Datasette and SQLite. Previously, he was an engineering director at Eventbrite, joining through the acquisition of Lanyrd, a Y Combinator startup he co-founded in 2010. Simon is also a co-creator of the Django Web Framework. He has been blogging about web development since the early 2000s.

In today’s conversation, we dive deep into the realm of Gen AI and talk about the following:

• Simon’s initial experiments with LLMs and coding tools

• Why fine-tuning is generally a waste of time—and when it’s not

• RAG: an overview

• Interacting with GPTs voice mode

• Simon’s day-to-day LLM stack

• Common misconceptions about LLMs and ethical gray areas

• How Simon’s productivity has increased and his generally optimistic view on these tools

• Tips, tricks, and hacks for interacting with GenAI tools

• And more!

I hope you enjoy this episode.

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