# My Research Process: Key Mindsets - Truth-Seeking, Prioritisation, Moving Fast - Neel Nanda (2025-04-27)

Source: https://www.lesswrong.com/s/5GT3yoYM9gRmMEKqL/p/cbBwwm4jW6AZctymL
Author: Neel Nanda
Date: 27th Apr 2025
Fetch-status: excerpted from LessWrong HTML via browser plus cross-checked against local shared draft.
Use: research-process evidence for truth-seeking, prioritization, speed, and action under uncertainty.

## Why this matters for agents

This is the most directly agent-steering post in the sequence. It says the research process needs active skepticism, explicit prioritization, fast feedback loops, and the ability to act under uncertainty without waiting for a perfect next step.

## Quotes

> I think the most important mindsets are:
> * Truth-seeking: By default, many research insights will be false - finding truth is hard. It’s not enough to just know this, you must put in active effort to be skeptical and resist bias, lest you risk your research being worthless.
> * Prioritisation: You have finite time, and a lot of possible actions. Your project will live or die according to whether you pick good ones.
> * Moving fast: You have finite time and a lot to do. This doesn’t just mean “push yourself to go faster” - there’s a lot of ways to eliminate inefficiency without sacrificing quality.

> Insufficient skepticism doesn't feel like insufficient skepticism from the inside. It just feels like doing research.

> This means that you must be putting in constant active effort into ensuring your results are robust. This must be integrated into part of your research process - if you’re not, then there’s a good chance your results are BS.

> The standard hypothesis testing framework can be misleading here, because it has an implicit frame of being able to list all the hypotheses. But actually, most of your probability mass should normally be on “something I haven’t thought of yet”.

> Here the Bayesian frame is often helpful. It’s generally overkill to put explicit numbers on everything, but it reminds me to ask the question “was this observation more likely under hypothesis A or B”, not just whether it was predicted by my favourite hypothesis.

> Fundamentally, good prioritisation is about having a clear goal (north star) in mind.

> The first step is just making time to stop and ask yourself “do I endorse what I’m doing, and could I be doing something better?”

> Prioritising and executing are different mental modes and should not be done simultaneously. Keep them separate, and make time to regularly reflect, and time to lock-in and execute on a plan without stressing about if it’s the best plan.

> Tight feedback loops are crucial: A key thing to track when doing research is your feedback loops.

> A corollary of this is that you should (often) do fast experiments first. It is far better to do a quick and dirty experiment to get some preliminary signs of life than an extremely long and expensive experiment that will produce conclusive data but only after weeks of work.

> Fail fast. One of the largest time sinks possible is investing weeks to months of effort into a failed research direction. Thus, a key question to ask yourself is: if this direction is doomed, how could I discover this as fast as humanly possible?

> A crucial mindset is being able to do something anyway, despite being so uncertain.

## Source graph

High-value links inside this post:
- Stop pressing the try-harder button: https://www.neelnanda.io/blog/mini-blog-post-6-stop-pressing-the-try-harder-button
- Negative results for SAEs on downstream tasks: https://www.alignmentforum.org/posts/4uXCAJNuPKtKBsi28/negative-results-for-saes-on-downstream-tasks
- Five-minute timers: https://www.neelnanda.io/blog/post-28-on-creativity-the-joys-of-5-minute-timers
- Weekly review / reflection: https://www.neelnanda.io/blog/39-reflection
- Jacob Steinhardt, Research as a Stochastic Decision Process: https://cs.stanford.edu/~jsteinhardt/ResearchasaStochasticDecisionProcess.html
