I really like the way Paul Graham characterizes the difference between persistence and obstinance in his essay The Right Kind of Stubborn. Persistence is like a boat that can’t throttle back—it keeps going and gets around obstacles in it’s path at great speed. Obstinance however, is like a boat whose rudders can’t be turned so it keeps going and doesn’t change course despite obstacles i it’s path.

The difference comes down to the ability to learn and adjust. Persistence is very powerful as long as the one who wields it makes changes as they go, finding paths around new problems they encounter along the way to their destination.

See also:

• It’s easy to question if your persistence is actually obstinance but being a better judge of early work inoculates you from skepticism
• Similarly, there is a fine line in science between skepticism and dogmatism
• Another way founders handle this is a controlled form of self-deception

From a recent survey paper about associative thinking, the authors found that more creative people generate a broader set of associations compared to less creative people and tend to perceive distant associations as closer together. Researchers tested this using word associations games and measuring the vectorized distance which approximates the semantic distance between words.

This offers an interesting clue about where creativity comes from and ways to use this to your advantage. For example, having a wide range of experiences and knowledge in order to have a more “richly connected semantic memory network” to draw from. Similarly different tools and exercises that support goal-directed and free associations can help with generating new ideas and finding solutions to problems.

Read Associative thinking at the core of creativity.

One explanation for how creativity works is by a process called associative thinking. By linking ideas and information together in unique ways, people are able to come up with something new. This happens spontaneously (what’s the first word that pops into your head) and also in a directed way (what’s the connection between these two clues).

See also:

• Tools for networked thought attempt to model this directly
• Consciousness is categories and we think in categories and connections
• Human intelligence is a special case of artificial intelligence

A recent study measuring the effect of including the term “artificial intelligence” in the description of products and services decreases overall purchase intent. This is more pronounced in high-risk products (like financial products) than in low-risk products (like a vacuum cleaner).

Read Adverse impacts of revealing the presence of “Artificial Intelligence (AI)” technology in product and service descriptions on purchase intentions: the mediating role of emotional trust and the moderating role of perceived risk.

See also:

• Trust is an important factor of economic prosperity and if AI is going to increase prosperity, there needs to be higher trust in the results
• Since businesses are more trusted than government, if businesses can’t figure out the trust problem first, it’s unlikely we will see it used openly by governments
• Legal AI models hallucinate in 16% or more of queries

The essay Advantages of incompetent management by Yossi Kreinin, discusses how competent management isn’t always best and we overlook the desirable effects of incompetent management.

Competent management sets goals and achieves them. Incompetent management does not.

The problem with competent management is that it leads to perverse incentives. Each team is expected to do more and the optimal thing to do is always ask for more resources even if they are not needed. This in turn leads to bloat and sprawl in systems but little room for improvement (the author in particular is focused on code quality, optimization, and things working well).

This is a tidy explanation for what we see at some larger software companies that have seemingly infinite resources but operate poorly.

Incompetent management on the other hand has the virtue of laziness and slack. Because objectives aren’t set or don’t matter, it can be relied on that at least a few well-meaning workers will want to do the right thing. Without the constant haranguing of tightly-managed objectives of competent management, the well-meaning worker is free to pursue what is, in actuality, optimal.

See also:

• Interestingly, this explanation benefits nicely from a cynical world view
• Why there aren’t more engineering management blogs
• Eigenvector goals

I use a docker container to build a fairly large hugo static website and vite to build some javascript. The reload time from saving a file and vite reloading the browser was exceeding 8 seconds. Enabling VirtioFS as the file sharing service (Docker Desktop -> Settings -> “Choose file sharing implementation for your containers”) compared to gRPC FUSE, speeds up builds 2x for me. That’s because hugo rebuilds every file every time it’s run which needs to be sync’d to the container before it’s picked up by vite and reloading the browser.

Nice!

In Double your productivity without more work or stress, the author makes the argument that the way to increase overall velocity is to decrease the amount of low-velocity periods of work. That’s because high average velocity (e.g. being “more productive”) is bounded by low-velocity activities over time.

For example, say you want to average 60 mph over a 60 mile journey. If the first 30 minutes you go 30 mph, it’s not possible to average 60 mph by going faster over the second half of the trip.

While working faster is a multiplier on the high-velocity work, the best bet is not to go faster but to eliminate low-velocity activity like email, meetings, scheduling, etc. that drag down your average velocity.

The annual percentage changes of the stock market go up and down more than the actual businesses in it. Similarly the profits of the businesses go up and down more than the economy of which it’s comprised.

40-year standard deviation of annual percentage changes

This can be explained by the role of emotion in investing and is a good reminder that we don’t know what the good news is and what the bad news is.

From Howard Marks' memo The Folly of Certainty.

We can’t go back in time so the only thing that can provide value is in the present and future.

If you evaluate a feature request based on the elapsed time since it was requested, it only serves to optimize for short-term frustration relief not truly optimizing one’s resources long-term. This can be difficult to avoid, but it’s important to resist arguments about priority that resolve to: “I told you about this {time unit} ago and it’s still not done.”

The longer something takes to deliver value, the less valuable it is. For example, when building a feature for a product, if it takes a year to build, it’s going to be less valuable than if it were to take a month because of the opportunity cost.

There are a few ways I’ve found to apply this principle. Time boxing work so that the total cost of time knowable. Make a rule that there are no “blank check” projects i.e. run on project that has no timeline or plan.

See also:

• Speed is undervalued
• This relationship is measured directly when it comes to interest rates
• Schedule time every day to work on your top goal

Today there is an abundance of everything. Shows to watch. Content to read. Products to buy. Pictures to like.

People don’t want more of everything they want better everything. This is where you can find a reliable way to bring value to people in a world of abundance.

See also:

• Search engines grind increasingly fine
• Even from the same company, permission to build new products is earned because people don’t necessarily want more from you when the main thing isn’t good enough
• Build a friend catcher to cut through the noise
• AI puts a higher premium on unique knowledge and will eventually increase the demand for better

Some anecdotes as I readjust to life on the east coast.

When moving from San Francisco to New York City, the difference between movers was distinct. The foreman in NYC was intense, highly caffeinated, freaked out about parking the truck, and repeated the same line about how I’m responsible for trash about ten times. The SF foreman…literally high.

The product or service in which, value goes to users first and then, upon capturing a mass audience of users, provides values to suppliers.

An AI agent is an intent-based abstraction that combines LLMs to plan and take action in order produce a desired goal.

Who is working on this?

• Sierra Agent OS is a framework for building AI agents
• Enso is a subscription to AI agents that perform various tasks

See also:

• AI employee

Several startups are touting AI employees that you can hire to perform a specific function. Itercom announce Fin, an AI customer service agent and so did Maven AGI. Piper is an AI sales development representative, so is Artisan and 11x. Devin is a software engineer.

Others want to provide the backbone to power AI employees. Lattice announced support to hire and onboard AI employees (then walked it back). Emergence AI and Enso are building a platform to orchestrate AI agents.

Is this a good idea?

Employment as applied to AI falls victim to reasoning by analogy and arbitrarily constrains artificial intelligence into preconceived constructs. AI agents can work 24/7, but many labor laws classify work around service time of a typical 40 hour work week. AI agents aren’t hired they are purchased, but many labor laws dictate hiring practices an employer must follow.

If you take the position of AI as employee, what follows is a debate about personhood. This is doomed to be an unproductive discussion because the capabilities of AI are not what people think they are.

See also:

• AI as employees stokes fears of job loss but automation doesn’t increase unemployment
• The labor market is merging with the SaaS market
• AI as tools is a simpler way to discuss implications of AI
• Another difference with employees and AI agents is how to get results e.g. replacing training with intent-based outcome specification

A common question in product management that always seems to come up is some flavor of: should product managers be technical?

My first job out of college was as a product manager working on B2B software. I was not technical. If you asked me back then, I would say it wasn’t an impedement.

Along the way I changed my mind.

I learned to code and that made me better at product. I started a company and that made me better at product. I did sales and that made me better at product.

It’s not the technical bit that makes you better—there are plenty of engineers that are not good at product!

Learning new areas like engineering, sales, operations etc. makes you more efffective. It increases your ability to reason about different problems. It’s increases your ability to work with different people, customers, and teams. It increases the set of solutions you can apply that is calibrated to reality.

So, should product managers be technical? Yes, but I think we get too caught up in the coding part that we forget it’s really about growing knowledge.

Notes on the video 13 Years of Brutally Honest Business Advice. I reworded and modified things to make sense to me.

1. Sell to the rich Don’t sell to the poor because you need to deliver a very large ratio of value to money. Rich people spend more to get less value. Start with the rich and then, eventually when the product/service is so good, sell to the mass market (poor).

2. Priorities make problems easy Most entrepreneurs don’t run their business without priorities and so they have make very little progress. Setting good priorities makes the most important problems to solve obvious and helps others get things done.

3. Raise your standards You need to be aware of what the best looks like and continue to raise the bar. For example, always hire someone better than you at the job will ensure the company gets better with each new person not worse (Peter Principle).

4. Lots of rules means you have dumb people This one is really a sub-item of the previous. A sign you have the wrong people is you have to write down obvious rules for people to follow. You shouldn’t be spending your time doing that and should instead hire better people.

   (I dislike the oversimplification of “dumb” vs “smart”. It’s much better to think about this as “skill fit” rather than a judgment of intelligence.)

5. Get better not bigger Getting bigger, hiring more, spending more, etc. can cover up many problems. Focus should actually be on getting better and constantly learning and adjusting. You’ll get bigger as a result.

6. Let fires burn You need to spend you time on the things that move the business forward and that’s impossible to do if you have to be the one to always solve every problem.

7. Brand is the most valuable thing you can own Brand is the durable way to get more out of all your marketing efforts. It’s built over a long period of time by making good associations between ideas and companies. Most of what we see this days is personal brand bootstrapping a company brand.

8. Understand inputs and outputs of your business Get to the lowest level of detail about what is holding back the business and fix that then the next thing.

9. Stop looking for hacks The problem with hacks is that they work for a time and then they don’t so you have to find the next thing and the next. The best strategies often don’t change like having really valuable content and product.

10. The best people cost more but are worth it Good people pay for themselves in the amount of impact they have. There are many arbitrage opportunities with talent but people don’t recognize it because they cost more.

11. The obvious thing is the main problem The main problem with the business is often the work you are avoiding not the hundred other things you think you need to do. Usually it’s the thing isn’t good enough.

Writing is like taking an idea and turning it into a rigid object. When ideas are fluid they become flexible and imprecise, able to fill into whatever context is needed—those “that’s not what I meant” moments and contradictions others allow us to have in conversations.

Writing demands the opposite. As you add sentences to the page, ideas takes shape and solidify, and so do the cracks. It becomes more obvious what you don’t know and your arguments fall apart under closer inspection. Cracking can lead to outright breaking of the idea, leading you to disagree with the original premise altogether.

From Writing to Think by Henrik Karlsson.

See also

• The easiest person to fool is yourself
• The illusion of explanatory depth is another way of seeing how flimsy your understanding is
• Thinking better thoughts

According to the Bureau of Economic Analysis, the contribution to US GDP in Q1 2024 of professional services industries was more than double that of information industries (which includes softare publishing).

That means, technological advancements in artificial intelligence could be a larger disruption than the entire SaaS industry. At least Bessemer seems to think so in their State of Cloud 2024.

From the report BEA report:

In 2024Q1, Professional and business services nominal value added was 12.9 percent of GDP and increased to $3,654.1 billion.

Professional and business services (PROF) is an aggregate of professional, scientific, and technical services (54); management of companies and enterprises (55); and administrative and waste management services (56).

In 2024Q1, Information nominal value added was 5.4 percent of GDP and increased to $1,523.9 billion.

Information (51) includes publishing industries, except internet (includes software) (511); motion picture and sound recording industries (512); broadcasting and telecommunications (513); and data processing, internet publishing, and other information services (514). Establishments produce and distribute information and cultural products, as well as data or communications, and process data.

Using org-mode and org-roam can make a rudimentary CRM system for logging interactions with people, companies, or any other contact.

Capturing associations

1. Create a file for each entity (use org-roam and a capture template to automate it)
2. Insert a link to the entity (org-roam-node-insert) in tasks, meetings, or any other notes to make the association with that entity
3. Visit the entity file and view backlinks (org-roam-buffer-toggle) to see all related items

Adding more CRM functionality to org-mode

Now that there is a rudimentary CRM, we can use org-roam’s database to build more functionality.

• Check-in with contacts: Use the list of backlinks sorted by date to see who you haven’t talked to in awhile.
• Get a list of tasks waiting on a contact: Use backlinks that have a status of WAITING to bring up at the next meeting.
• Adapt at mentions for org-mode to quickly tag contacts to make associations
• Create a capture template for each kind of contact (company, person, etc.) to store standardized properties like company name and website

See also:

• Personal CRM
• Start a personal CRM as early as possible, though LinkedIn is a pretty good place to start

Software abstractions save us time doing work by not having to write programs from lower level building blocks. Programming languages like Python provide an easier way to write general purpose software than say, assembly language.

However, abstractions don’t absolve us from having to learn about lower level building blocks because they always seem to leak through to higher levels. For example, you can’t build a web app using React without debugging an issue with hooks that have to do with async JavaScript once in awhile. Eventually, we all need to learn what lies beneath!

From The Law of Leaky Abstractions.

See also:

• Abstractions are real
• Choosing boring technology can help find higher quality abstractions but the same laws apply, just less frequently
• Good magic and bad magic
• TypeScript undermines the value of the JavaScript ecosystem and static typing

A problem that crops up often in web design is centering. No not how to center a div, but how to visually center an element vertically. This is different than merely centering vertically using flex or grid because when you have elements like a top nav that takes up space, the vertically centered element will appear too low on the screen even though it is technically correct (50% of the parent element).

Is there a reliable way to solve this problem without having to remember to offset everything by some amount?

Working asynchronously is an important reason why remote teams work. However, it can devolve into anti-patterns.

For example, writing a brief and then sharing it for review but not waiting for all feedback will over-emphasize comments by the first to review (an organizational availability bias?). Sometimes the mere presence of other comments in a document is enough to disuade someone from adding their feedback, incorrectly assuming someone else already covered what they would have said.

What can remote teams do about this?

There are a few practices async teams can adopt to avoid these pitfalls.

First-to-review bias can be mitigated by seeking targeted feedback at the same time as sharing it broadly.

For example, in Slack say:

“Here is the brief on {THING AND LINK} for review.

{LIST OF PEOPLE} can you please provide feedback on {LIST OF AREAS ACCEPTABLE FOR FEEDBACK} by {WHEN YOU NEED IT}?”

Organizationally, help people understand that async means more work gets done in parallel but more slowly. It can take time to wait for the right collaborators and to get the right feedback. Asnyc should not be used as a shortcut to speed things up (like accepting the first feedback and moving on as in the earlier example).

(This idea was borrowed from something I heard Alex Norcliffe said.)

See also:

• Another example of how remote teams need to be more deliberate about everything
• The best way to speed up gathering feedback is to make sure briefs always answer a key question
• Automating cooperation decreases the cost of coordination

Low bitrate audio codecs are primarily used for downscaling audio for slower internet connection speeds and supporting older devices. They can handle high rates of packet loss while still sounding natural. For example, Opus 1.5 still sounds good at 6 kb/s and narrowband sampling rate (8 kHz compared to 48 kHz).