Entries for February 2025

If you are a developer, you are annoyed by this. If you are a user, you were most likely guilty of this. I am talking reporting that something is broken, AND deleting it.

This happened to me too many times: User experiences a bug with an object. Their first instinct is to delete it, and create a new one. They report it. I cannot reproduce and fix it.

If you have a car and it stops working, you don’t throw it in the trash and then call the service to fix it. But when it comes to software, which has virtually zero cost of creation, this behavior somehow becomes widespread.

This is similar to other user behavior like smashing the mouse and keys when a computer gets stuck. It is physically impossible for such an action to speed up a digital process, but many of us instinctively do it.¹ Deleting to fix is a similar behavior, which I suspect got ingrained by crappy Microsoft software. The default way of fixing Windows machines is to “format the disk”, and reinstalling Windows. Nobody asks, “why do I have to start from scratch?”. The “End User” deletes to fix by default, because the End User does not understand. “Have you tried turning it off and on again?”

The concept of “Mechanical Sympathy” is relevant: having an understanding of how a tool works, being able to feel inside the box. We can extend this to “Developer Sympathy”: having an understanding of how a software was developed, how it changes over time, how it can break, how it can be fixed.

Any troubleshooting must be done in a non-destructive way. When a user deletes an object, two things can happen: it is hard-deleted, which makes the issue impossible to reproduce. If it is instead soft-deleted, it might be restored, but developers will mostly not bother, depending on the issue.

The users cannot be expected to care either. Their time is valuable. They deserve things that “just work”. So we need to come up with other workarounds:

• Everything should be soft-deleted by default in non-sensitive contexts, and should be easy to restore.
• Any reporting form should include instructions to warn the user against deleting.
• Even better, the reporting should happen through an internal system, and should automatically block deletion once a ticket is created.

One common thing about sports noobs¹ is that they don’t warm up before and cool down after an exercise. They might be convinced that it is not necessary, and they also don’t know how to do it properly. They might complain from prolonged injuries, like joint pain.

The thing about serious exercise, be it strength training, running, stretching, and so on, is that you are pushing your body beyond its limits. This is called overload. If you do this over a long term period, it is called progressive overload. This is what gives you real power, real speed, ability to do middle splits, and so on.

When you start with an intention to do serious exercise, and you immediately start loading heavily without warming up, you will get injured very quickly and have to take days or weeks of break.

For example, if you directly jump at the heaviest dumbbells you can lift and start doing bicep curls the moment you get to the gym, you will destroy your wrists, elbows, and/or shoulders. You will not realize it immediately. After a few weeks or months, you will start feeling pain, and will have to stop training altogether.

A common thing about noobs who injure themselves early on is that they have fierce willpower, but they don’t listen to their bodies, and they don’t have a good understanding of their current capabilities. They have an idea of where they want to be, and they are prepared to push towards it. But because they are impatient, don’t have good mind-body connection, and don’t know how to plan for long-term progress, they push themselves too far too fast.²

Being able to sustain injury-free long-term practice is a skill in itself, and perhaps the most underrated among non-professional gym-goers and athletes. There is no fancy Latin/Greek name for it, like there is for other things like cardio, plyometrics, hypertrophy, and so on. A crucial idea is missing from mainstream fitness.

Therefore, I coin the term and define it here:

Parathletics: The practices that let you successfully sustain injury-free long-term practice of a physical activity.

The word comes from Greek παρά (para-) meaning “beside/alongside” and ἀθλητικός (athlētikós) meaning “athletic”, “relating to an athlete”³.

Two main parathletic practices are warmup and cooldown.

Before starting a workout, warm up your body by moving your every joint, from the neck to the toes, through its range of motion and increase the blood flow to your muscles. If you plan to do heavy loads, build up to them with lighter weights first.

After finishing a workout, cool down your body by stretching every joint and muscle group, and especially the ones you just trained. The more hardcore your workout, the more you need to stretch.

Skipping these will result in injury, decrease in mobility, and delay in reaching your goals.

Satya Nadella, shares his thinking on the future of knowledge work (link to YouTube for those who don’t want to read) on Dwarkesh Patel Podcast. He thinks that white collar work will become more like factory work, with AI agents used for end-to-end optimization.

Dwarkesh: Even when you have working agents, even when you have things that can do remote work for you, with all the compliance and with all the inherent bottlenecks, is that going to be a big bottleneck, or is that going to move past pretty fast?

Satya: It is going to be a real challenge because the real issue is change management or process change. Here’s an interesting thing: one of the analogies I use is, just imagine how a multinational corporation like us did forecasts pre-PC, and email, and spreadsheets. Faxes went around. Somebody then got those faxes and did an interoffice memo that then went around, and people entered numbers, and then ultimately a forecast came, maybe just in time for the next quarter.

Then somebody said, “Hey, I’m just going to take an Excel spreadsheet, put it in email, send it around. People will go edit it, and I’ll have a forecast.” So, the entire forecasting business process changed because the work artifact and the workflow changed.

That is what needs to happen with AI being introduced into knowledge work. In fact, when we think about all these agents, the fundamental thing is there’s a new work and workflow.

For example, even prepping for our podcast, I go to my copilot and I say, “Hey, I’m going to talk to Dwarkesh about our quantum announcement and this new model that we built for game generation. Give me a summary of all the stuff that I should read up on before going.” It knew the two Nature papers, it took that. I even said, “Hey, go give it to me in a podcast format.” And so, it even did a nice job of two of us chatting about it.

So that became—and in fact, then I shared it with my team. I took it and put it into Pages, which is our artifact, and then shared. So the new workflow for me is I think with AI and work with my colleagues.

That’s a fundamental change management of everyone who’s doing knowledge work, suddenly figuring out these new patterns of “How am I going to get my knowledge work done in new ways?” That is going to take time. It’s going to be something like in sales, and in finance, and supply chain.

For an incumbent, I think that this is going to be one of those things where—you know, let’s take one of the analogies I like to use is what manufacturers did with Lean. I love that because, in some sense, if you look at it, Lean became a methodology of how one could take an end-to-end process in manufacturing and become more efficient. It’s that continuous improvement, which is reduce waste and increase value.

That’s what’s going to come to knowledge. This is like Lean for knowledge work, in particular. And that’s going to be the hard work of management teams and individuals who are doing knowledge work, and that’s going to take its time.

Dwarkesh: Can I ask you just briefly about that analogy? One of the things Lean did is physically transform what a factory floor looks like. It revealed bottlenecks that people didn’t realize until you’re really paying attention to the processes and workflows.

You mentioned briefly what your own workflow—how your own workflow has changed as a result of AIs. I’m curious if we can add more color to what will it be like to run a big company when you have these AI agents that are getting smarter and smarter over time?

Satya: It’s interesting you ask that. I was thinking, for example, today if I look at it, we are very email heavy. I get in in the morning, and I’m like, man my inbox is full, and I’m responding, and so I can’t wait for some of these Copilot agents to automatically populate my drafts so that I can start reviewing and sending.

But I already have in Copilot at least ten agents, which I query them different things for different tasks. I feel like there’s a new inbox that’s going to get created, which is my millions of agents that I’m working with will have to invoke some exceptions to me, notifications to me, ask for instructions.

So at least what I’m thinking is that there’s a new scaffolding, which is the agent manager. It’s not just a chat interface. I need a smarter thing than a chat interface to manage all the agents and their dialogue.

That’s why I think of this Copilot, as the UI for AI, is a big, big deal. Each of us is going to have it. So basically, think of it as: there is knowledge work, and there’s a knowledge worker. The knowledge work may be done by many, many agents, but you still have a knowledge worker who is dealing with all the knowledge workers. And that, I think, is the interface that one has to build.

If you got confused for a second there like me, Lean here is not referring to the open source proof assistant but lean manufacturing.

Whereas it is nice to dream, the actual sentiment on Microsoft Copilot and AI integration in Microsoft Office is along the following lines:

I have written about this in a previous post:

There is going to be an AI-native “Microsoft Office”, and it will not be created by Microsoft. Copilot is not it, and Microsoft knows it. Boiling tar won’t turn it into sugar.