Further ReadingI’m not gonna pretend to be an expert here (any more than I’m an expert Obsidian plugin developer :p) but here are some resources that helped me figure out Claude CodeKent writes a lot about how he uses Obsidian with Claude Code.This is an incredible hub of resources for using Claude Code for project management, by someone who also uses Obsidian.This take on Claude Code for non-developers helped solidify my understanding of how it all works; it hallucinates less, for one thing.Eleanor Berger has fantastic tips for working with asynchronous coding agents and is incredibly level-headed about the LLM landscape.This article does a great job of breaking down all the nitty-gritty of how Claude Code works.Damian Player has a step-by-step guide on using Claude Code as a non-technical person that goes into more depth.Here’s a tutorial from a pro that breaks down best practices for using Claude Code, like the importance of planning and thinking things through, and exactly why a good CLAUDE.md file matters.

and I don’t need to bother my friends to get stuff done.

Suddenly, I can actually make use of the APIs I’ve always known existed.

I’m already finding better ways to batch my tasks. Making smarter to-do lists that include more context

f you define agents as LLM systems that can perform useful work via tool calls over multiple steps then agents are here and they are proving to be extraordinarily useful. The two breakout categories for agents have been for coding and for search.

Virtual shopping agent technology combines natural language processing with predictive analytics. This combination allows such systems to understand customer queries in natural languages while predicting future purchasing behaviour. The result is a more intuitive and efficient shopping experience that feels personal and responsive. Intelligent shopping bots represent the most advanced form of these systems. They can handle complex customer interactions, process multiple data points simultaneously, and learn from every interaction.

In today’s fast-moving, AI-powered era, autonomous agents are playing a bigger role than ever. They are helping businesses run smoother and making decisions affecting millions of lives every day. While these systems are designed to make our lives easier and unlock new opportunities, we can’t get carried away—we need to implement proper AI Agent Evaluation frameworks and best practices to ensure these systems actually work as intended and follow ethical AI principles.

Most legacy apps that aren’t putting efforts into modernization or AI integration are either breaking even, or nearing their demise due to the inability to deliver personalized experiences and use data-driven insights that define market leaders in artificial intelligence legacy systems implementations.

The seamless running of an eCommerce company depends on effective control of stock levels. Through demand prediction, stock level optimization, and reordering process automation, artificial intelligence streamlines inventory control. AI-driven inventory systems examine consumer preferences, seasonal variations, and sales trends to guarantee that you always have the appropriate level of supply.

in 2018 you know it was around four percent of papers were based on Foundation models in 2020 90 were and 00:27:13 that number has continued to shoot up into 2023 and at the same time in the non-human domain it's essentially been zero and actually it went up in 2022 because we've 00:27:25 published the first one and the goal here is hey if we can make these kinds of large-scale models for the rest of nature then we should expect a kind of broad scale 00:27:38 acceleration

Nonetheless, Claude is first AI tool that has really made me pause and think. Because, I’ve got to admit, Claude is a useful tool to think with—especially if I’m thinking about, and then writing about, another text.

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