Empathy driven development: The context engineer's best route to progress

Don't try to get every case. Imagine you're telling a smart, reasonable person a task they need to complete. Empathy, not raw engineering, is the key to LLM quality.

I've found the best way to understand how an AI works is to pretend you're working with a college student who is extremely capable, but inexperienced. Imagine you're giving an intern directions about how to complete a task. For them to do the baseline, you might want to start by giving them explicit instructions and examples. But in order to train them to do the right job, you need to help them understand the right mindset.

At Facebook, I worked with a lot of new grads and helped push them toward their potential. The thing I found always worked was asking them questions, not pushing them toward specific answers. I imagined, "how did i discover this topic?" and "how can I help Max discover this topic?"

The key was never giving a ton of context, it was giving the right context at the right time. It didn't matter how capable Max was at engineering, they wouldn't ever be able to do the thing they needed to do if I just overwhelmed them with everything possible.

So imagine you're talking to a friend, a new developer, or really anyone, and then try to give them the right amount of context to do the job. I've found the hourglass as a great framework to build context for LLMs (and people, to be frank) and try to get your LLM friend to do things one at a time.

Rather than create the biggest prompt, focus on making one task at a time work. Often times that's classification tasks, and then moving on from there to more complex tasks. You'll find a pipeline the best tool for the job generally, so getting familiar with job queues and distributed non-linear systems might also be great places to start.

But the first step, truly, is empathetic reasoning

.