unfiltered

This morning, I was multitasking. I spent a few minutes making Claude Code go, and while it’s revving I’m writing in my paper notebook. Something catches the corner of my eye, I looked up and went to tend to the AI’s request. It whirls again, so it’s back to the notebook. Back and forth. As you can imagine, neither turned out particularly well, although if I were to be fair, the robot did a much better job than my writing. After all, I was only the one multitasking.

We have long known that multitasking reduces our cognitive abilities. There are numerous credible studies on this topic. Yet everyone is dual or triple wielding coding agents these days. Everyone feels more productive, and they are. They also say the work is not better ¹.

My observation is that the current crop of AI coding agents and models sit in the anti-flow zone of productivity: there is a little too much down time in between prompts, yet not enough to be able to effectively do something else. Once you hit enter on a prompt, a typical coding agent can take anywhere from minutes to tens of minutes, and while it’s doing its thing there is nothing much the human observer can do. We can try to follow along, but the terminal outputs are not really comprehension friendly. Of course we get bored and we multitask.

As a thought experiment, I wondered what would happen if coding agents are a magnitude faster². If we can get instant gratification it might solve the desire to let the attention wander. Yet at the same time, it raises an interesting question: if the robots can generate thousands of lines of code in a matter of seconds, then how are we able to really understand what’s going on? The temptation will be to do more and understand less since it’s the path of least resistance. Consequently, we will drown in systems that we do not understand.

When I ask people about this, everyone says that taste is going to be the thing that differentiates them. Make sense, since our perspective and judgement is what we really bring to the table and affect the world around us. That said, to be able to render accurate judgement requires us to understand the thing that we are judging. If our comprehension is being overwhelmed, then our judgement is what’s being overwhelmed.

I don’t know if there’s a neat little solution to this puzzle. My sense is that the status quo is not sustainable and things will need to change: either we develop tools to help us hold and understand more complexity, or we will have to delegate. Either the craft matters, or it becomes utilitarian.

• I love designing and building UIs. Like love, love. It is work that combines product thinking, UX, systems, and visuals all at the same time and it tickles every part of my brain. There are easily five iterations to get to a satisfying outcome: original idea, wireframes, implementation, iterating through the trough of disillusionment, and then the transcendence.
• I’ve gotten to a good state with the Sunnyday Agent configuration page. Good for now at least; and I don’t use the word good lightly. There are still rough edges, and aspects of the page which are candidates for a teardown and redo in the near future as my understanding evolves. But at least everything feels and works well within the constraints it’s supposed to right now.
• That’s one of the great things about working with coding AI agents. They give me higher degrees of freedom in working and can express in higher fidelity. If I were to put it in an analogy, it’s akin to the transition from 2d to 3d. We gain a new dimension that brings it closer to the real thing.
• After working on agents for the last few months, I have a lot of thoughts about performance. All the benchmarks tend to flatten them down to a single dimension, and to be fair that’s what benchmarks are supposed to do. However, agent performance is a much more nuanced, especially because there is the what is not said gap between the lines of the instruction prompt. I will have more to say about that as I collect my thoughts.

A lot of the discourse these days conflates what’s possible with what’s good. That’s understandable. Possibilities are exciting; they let us do things we couldn’t before, start new projects, and feel squarely in the driver’s seat.

But because it is possible doesn’t mean that it is good. Too often, we just let things happen. Our judgement gets fatigued when it takes more effort to understand and decide if they are worth our time and attention. And then we let them slip. The word slop encodes that energy.

I’m not here to gatekeep possibilities. I love possibilities, but I also care that things are good. Good can be achieved when we—the people who are involved in and affected by new possibilities—spend time poring over them and iterating on them. Extending our care and exercising taste.

Now that we know that things are possible, let’s spend time making them good.

I write this as a reminder while I reflect on the old year and look forward to the new. I have heard all the proverbs in this vein, and as I grow older they take on depth. Even as I yearn for the alternative.

It’s easy to be impatient. I secretly wish that building the next feature or dieting for 3 months will get me everything that I want. First, there is no magical destination that will solve the unease I expect it to cure. Second, if it is something I want, I should work toward it even when it’s slower than I’d like. More importantly, if the work is meaningful, I have to keep doing it.

In that perspective, a year is a mere segment in the marathon. That is the inch that I toil in.

I’m a firm believer that we, humans, are primarily preoccupied with what other people are up to. The social instinct is something that is hard-wired. Politics, alliances, rivalries, and gossip – all human drama –are part of that.

AI may become the best information retrieval and even information using machine in the world. But it remains a tool. Not even a peer. There is no real reason why humans should be concerned about the opinions of AI much less the edict from one.

If there comes a day where we would rather defer to AI, then we would have indeed done our worst harm.

I thought I would write more when I started “unfiltered”. But that wasn’t the case. The format was one challenge, but it wasn’t the main obstacle.

I realized I was missing two things.

First, the instinct to turn ideas into prose. A good writer acts while ideas are still alive. They fade for two reasons. Sometimes we take too much of an inside view and we underrate how compelling they are. Other times, we overwork them so much that it feels impossible to start.

Second, the habit itself. Turning thoughts into writing is a skill honed through repetition and practice. When I don’t write regularly, it starts to feel difficult. The longer I wait, the more daunting it becomes.

I’ve always want to write more. I would love to write more. Writing is the best way to wrestle with ideas and communicating them to others. Maybe it just comes down to making it a priority.

A few observations about complexity while working on my agent library.

1. One of the foundational decisions that we have to make when designing software is where to place complexity. In a way, designing is about discovering complexity and shifting it between the user and system. As designers, we are making assumptions and decisions about what to solicit from the user and what to bake into the design.
2. Complexity here refers to decisions or steps taken as part of accomplishing a task. An example of complexity is something as mundane as naming a file. They are often trivial as individual units, but when accumulated they can make a task feel complex and frustrating unless the user is well trained.
3. Software is excellent at encoding decisions programmatically and is thus great at removing these from the user. There was a movement around sensible defaults a decade ago or so that aimed to decrease the amount of decisions that needed to be made out of the box. The end result is perceived simplicity.
4. There is no free lunch however. By its nature, simplicity is diametrically opposed to control. What is made not explicit must be implicit, either in terms of effort required to discover them or the ability to access them in the first place. In the latter case, it will sometimes make a design awkward–that is, users will have to contort themselves to take advantage of it–or, a non-starter.
5. It is extremely difficult to hide complexity completely. If a choice can be completely removed without consequences, then it is either redundant or obsolete. The reason options exist and matter is because users are not a single homogenous bloc. People want to make use of technology to achieve certain means and the diversity in needs and preferences are as kaleidoscopic as people themselves.
6. Sometimes new technology can emerge that changes the landscape of complexity. Language models are a prime example of that. The ability to use language–one that is native to us–as the medium and interface opens up much more possibilities compared to the crude resolution of commands and GUIs. This introduces new possibilities and thus complexity into the system. Current AI apps punt them onto the users but as the field develops, we will start seeing the complexity shift again.

I recently purchased a Tanita scale, and it’s been a reminder that good products are delightful. It was an opportunistic purchase. Somehow I shattered the kitchen scale that I had for years and not too long ago I saw a chef’s recommendation on YouTube.

The thing about the Tanita is that it’s as if someone has thoroughly considered what makes for a good home kitchen scale and made the scale-iest home kitchen scale that they can make. The performance is impeccable; it displays weight changes instantly and there’s even a precise mode that goes down to 0.1g (fun fact: coffee beans are about 0.2g each on average). The controls are logical and satisfying. One of the problems I had with the previous scale is that it did not have an off button - it turns off automatically and frequently when I’m in the middle of using it. Lastly, it feels good in the hand, a hefty enough chunk but small enough to stow away. Also, the raised platform separate the weighed to the weight display and that’s a nice touch.

I expected to like the scale but I didn’t expect to love it. I find so much joy in weighing things and knowing how heavy they are that I’m constantly finding excuses to use it. Everything from weighing out my morning coffee beans to pasta servings. Good products should make you want to use it more, find new ways of using it, and just shout it’s virtues from the rooftop. That’s the standard I need to hold myself to when building new products.

I love learning. It often involves looking for new sources of information to drink from. There is an exhilaration from discovering the untapped land of knowledge and a rush from venturing through it.

Yet to my recent surprise I discovered that the once topic of my disdain, repetition, is an equally great teacher. Through the integration of a few daily practices I have found them to be a profound source of satisfaction. Repetition is the king of compounding effects. Inches accumulated over time paves major new thoroughfares.

Doing a thing, whether it is a movement, technique, or habit, over and over again yields insights and opens up new areas of exploration. Maybe it is the small adjustments that repetition demands, the continual solving of micro problems, or simply the comfort of familiarity that frees the mind to wander. Whatever the reason, repetition fosters mastery and creativity.

It’s very hard to do a thing over and over without becoming skilled or without eventually getting inventive. Moreover, this knowledge can only be gained through repetition. The insights are embodied and ingrained in the motion–not something one can read or listen to.

I used to dread practice. Now, I look forward to it.

Recently, I have taken back to sketching out ideas by hand again. To achieve a neater and more compelling final composition, I found it really useful to work in layers.

The first layer is always a rough placement of where things go. Subsequently, I will refine content and details, ink the outlines, and finally add color and shadow. Every pass is an attempt at both fleshing out the idea itself and achieving balance between the elements. Finally, the pencil lines are erased, the scaffolds taken down, and what is left is the final polished composition.

This is going to sound profound and basic at the same time: iteration isn’t optional – it’s essential. Good design demands iterations because it only emerges from progressively refining ideas from rough concepts to detailed compositions. No one, no matter how talented, can do it all in a single pass.

Product design mirrors this truth. Understanding a problem thoroughly demands multiple iterations. Every pass is an opportunity to uncover new insights to elevate the status quo towards something better. Unlike paper and pencil, modern tools often err on the side of too much gloss. This is a reminder to myself that at the fundamental level iteration, more than any tool, is how we get to great products.