--- > To make AI good, get good yourself. AI is a multiplier. If you are a small coefficient, you won’t see much gain. If you are a negative coefficient, expect negative gains. - [View Highlight](https://read.readwise.io/read/01k0a7fjym1tc6dm13892fpzc5) --- > AI is still sensitive to language and style and will often mirror the tastes and sensibilities of the prompter. Highly skilled engineers have really sharpened taste and instinct for what works and what doesn’t. - [View Highlight](https://read.readwise.io/read/01k0a7gm1g4p83zswtfj4kxhrj) --- > Therefore, embody the care of a craftperson. At the end of the day, you should produce artifacts you are proud of, even if the AI assisted in making it. - [View Highlight](https://read.readwise.io/read/01k0a7h2kk3cnc634c3g8t5dam) --- > A technique that has worked well for us is *metaprompting*. I prompt the model with a simple task and ask it to help surface tradeoffs and edge cases. Then I turn it into a tech spec and hand it off to another LLM agent to execute. - [View Highlight](https://read.readwise.io/read/01k0a7k2n9m6h6vqy34zytzazv) --- > The mechanics of what works for these tools are in flux, but one robust principle is to really work on yourself to be a good engineer. Your habits will quickly pass on to the AI systems you work with. The reason this works is because what helps the human helps the AI. - [View Highlight](https://read.readwise.io/read/01k0a7kskeb30nfkrnrqe4wvk0) --- > software engineering is the art and science of maintaining a large body of well-defined mental models that achieve a business or economic need. Much of the work is around crafting and curating these large, complex sociotechnical systems, and code is just one representation of these systems. - [View Highlight](https://read.readwise.io/read/01k0a7mmpydsk90rbee4texfy9) --- > The effectiveness of AI-assisted coding is strongly dependent on how skillfully you can provide the right context to the LLM. - [View Highlight](https://read.readwise.io/read/01k0a7r5hkg0y1fx883n06qfqn) --- > Encode coding standards and practices in a [RULES.md](http://rules.md/) file. Symlink this file to agent specific rules files such as `.cursorrules`, `.windsurfrules`, [`claude.md`](http://claude.md/), [`agents.md`](http://agents.md/) etc - [View Highlight](https://read.readwise.io/read/01k0a7s4ryrq7mdjsc2v04d04m) --- > If you are working on a big feature, break it down into small tasks, and feed the tasks one by one, making a commit at the end of each task. If you do these with your stories, the story card description with the task list is often a very helpful description for the AI. - [View Highlight](https://read.readwise.io/read/01k0a7vngb0zmg6nwjkeykhak6) --- > Do not take AI suggestions for granted. Ask it to justify its choices, present alternatives and think about advantages and drawbacks. - [View Highlight](https://read.readwise.io/read/01k0a7xa4qa2a2avywcck5y5sa) --- > LLMs are an infinitely patient teacher with massive world knowledge (and more recently, ability to research effectively). Aggressively use them to learn things and demystify any new code or stack. Relentlessly dig. Figure out the best practices. Ensure you are learning correctly by getting the LLM to cite high quality sources. - [View Highlight](https://read.readwise.io/read/01k0a7yer8msrpq9j9v5tz66r1) --- > It’s less valuable to spend too much time looking for and building sophisticated abstractions. DRY is useful for ensuring patterns in the code don’t go out of sync, but there are costs to implementing and maintaining an abstraction to handle changing requirements. LLMs make some repetition palatable and allow you to wait a bit more and avoid premature abstraction. - [View Highlight](https://read.readwise.io/read/01k0a830keqs85t2f5p5fq3g4j) --- > Redoing work is now extremely cheap. Code in the small is less important than structural patterns and organisation of the code in the large. You can also build lots of prototypes to test an idea out. - [View Highlight](https://read.readwise.io/read/01k0a83dq7t3fptsj4hshp5vkn) --- > Tests are non-negotiable, and AI removes all excuses to not write them because of how fast they can belt them out. But always review the assertions! - [View Highlight](https://read.readwise.io/read/01k0a84ak39gxxz5hd60wmd4hk) ---