When you see something absurd in the market, it’s helpful to ask, “What’s the trade?” How would you make money from it if it truly is absurd? Oftentimes, it’s not that straightforward and there is more to it than you think. This is a good check against biases and, if you truly believe that something is wrong, would you be willing to make the trade?

Read 15 Lessons From Newfound Research.

See also:

• Psychology overwhelms fundamentals in the short run
• Skepticism and optimism in markets shows us that there are cycles that occur but whether you can spot them is a different story

Every portfolio and every decision can be decomposed into being long something and short something. By weighting one area of the portfolio higher than another, you are short on the underweighted parts of the portfolio.

The same is true for decision-making at a startup. Scarce resources mean you can only invest in a certain number of things at any one time. This portfolio of decisions can be analyzed by thinking about what you are short and long on if that makes sense.

Read 15 Lessons From Newfound Research.

See also:

• What’s the trade?
• The focusing illusion shows us the natural bias towards overestimating the importance of what we pay attention to (being long on something)

Being able to programmatically generate content for search engine optimization is only useful if you have a lot of keywords you can target (thousands) and pages you can generate to rank for them.

For example, Zapier found that they could target long-tail of search engine keywords in the pattern of “{software 1} {software 2} integration”. This is tightly linked to their product which is important so they can convert visitors searching for it. It also means they can a high volume of clicks from each page. Let’s say they have 100 integrations, that means they can generate ~10,000 pages (each combination) and, if each page generates 100 clicks per month, that’s 1,000,000 clicks.

When choosing the best SEO strategy, you can do a Fermi estimate to figure out if your business is going to get enough clicks to make it worth investing in programmatic SEO.

See also:

• How to do keyword research which is important for setting the strategy and understanding if programmatic SEO will be worth it
• How to do SEO

You can use a watch with a dive bezel to track two timezones at onces without a GMT hand. This works because dive bezels typically have markers for every 5 minutes and, since time is base 12, you can calculate the second timezone with simple division.

How does it work?

Turn the dive bezel so that the nib is on the timezone offset hour marker. For example, if you are on Pacific time and you also want to track Eastern time, rotate the bezel so the nib so is on the 3 o’clock marker.

To read the time in the second timezone, look at the hour hand to find the hour marker (as usual), find the corresponding minute located on the dive bezel, then divide by 5. Read the minutes as normal and you have the hour and minutes of the second timezone!

In 2023, the average time between raising a Series A and Series B round increased to 31 months according to Crunchbase. With startup funding falling 67% in 2022, more startups could face a difficult time getting funding. Some predict startups will run out of cash in 2023 with the most fiscally conservative ones run out in 2025 unless conditions change.

See also:

• Running a startup during a recession means having enough runway to get through longer time periods between rounds and adapting to endure
• SaaS benchmarks for Series B
• Startup valution multiples fell from 100 to 39 times ARR in 2023

People tend to think impressive results must come from impressively complicated means and effort. We underestimate the power of simple ideas and overestimate complications.

From How to Take Smart Notes (literature notes).

See also:

• Elegance is a heuristic guide to truth
• Wealth-creation mechanisms are simple
• Clarity is one number
• When things are intensely themselves
• Compounding is simple but unintuitive
• Building high quality things comes from using the product

A book by Sönke Ahrens about taking notes to improve productivity and writing which is incredibly convincing but extremely impractical in describing what to actually do.

Writing smart notes explains a system for note taking using the following process:

1. Read and then rewrite the interesting parts of what you read as short literature notes (not quotes, highlights, or margin scribbling)
2. Write down ideas and short notes as fleeting notes and review them within a day (keep project notes separate)
3. Review and turn the literature notes and fleeting notes into permanent notes
   • Permanent notes should not be a reminder of the thoughts or ideas but the actual thing written down
   • The goal of a permanent not is to maximize the utility within your slip-box (the collection of other permanent notes)—doing this forces you to think about it in relation to other notes which further increases understanding and leads to new ideas or questions
4. Use the act of writing permanent notes to find interesting new questions to answer and to source material for writing new works

While it may sound like a lot, making a habit of writing permanent notes adds up. Luhmann’s slip-box contained 90,000 notes but that’s only six notes a day from when he started until the day he died.

See also:

• Building a note-taking habit and my personal note taking practice
• Zettelkasten and a mind map where nodes are notes
• Tools for networked thought
• Emacs org-mode and org-roam

A blog post from GitHub says that their code assistance tool, Copilot, is behind 46% of developers' code, up from 27%. For Java, that number is 61%.

I might be missing something but this is an astonishing change. In two years, generative AI has fundamentally changed where code comes from. What does it mean if these numbers climb to 90%? Will it impact real productivity or merely shift the effort from writing to prompting and editing?

See also:

• AI multiplies the value of expertise
• AI is the next great interop layer
• Typing fast is thinking with your hands

When negotiating, it’s important to control the frame in which the conversation is happening. The frame constrains what kinds of ideas can be explored and the rules that govern evaluating them. When you step into someone else’s frame in a negotiation, you become bound to the constraints they set.

For example, in a sales call, you might be speaking with a customer about pricing. They might ask why you are charging per employee and what the value is. By responding directly to this question, you inadvertently accept it’s frame (incremental value per employee) and the ideas you share to justify value now need to fit within that frame or it won’t make sense.

In the example situation, if you feel like your position is weaker in that frame, it would be better to pop up a level and establish a new frame that plays to your strengths. “Pricing this way enables us to provide $THING_THEY_WANT for a fraction of the cost of $ALTERNATIVE”.

See also:

• Sometimes an answer is required, not necessarily a good one
• People respond in kind so if you are defensive the other party may press harder to push you into their frame

One of the keys to building great products is to regularly make contact with reality. Ideas rarely survive first contact with users—what we think is good might be completely useless to an actual potential customer. Regular contact with reality insulates you from the illusion of explanatory depth.

Founders tend to get so far ahead of themselves in company building that a popular piece of advice from Paul Graham is to build an initial product a small group of users love.

Product people get this wrong too. It’s easy to think we understand something we don’t and roadmaps/timelines don’t bake in time to be wrong.

See also:

• Good product engineers don’t outsource their thinking and talk to users directly
• Still conjecture is vital to product development and so is having good taste
• Have the willingness to pay conversation early

It’s useful to think about the underlying utilities that go into running one’s life and business with the same rigor used to build something significant. Afterall, the things we rely on every day can have an outsized impact on our own performance so why not treat it that way?

What’s important

If we are going to intentionally design personal infrastructure, we should be clear what it’s all for. For me, personal infrastructure is in service of a few top level priorities.

• Notes Creating bits of knowledge for myself through writing, journaling, and publishing.
• Work Building a business, focusing on the most important goals, recalling and sharing information, and solving problems.
• Personal Taking care of myself and my family, organizing projects, not forgetting something important.

Principles

Next, a set of principles to help guide choices and make it more obvious what the to priorities should be.

Below are the list of principles I keep in mind.

Centralized

Tools and systems should be as accretive as possible. Improvements to one area should improve many things at once. Everything should work coherently as a whole.

• Emacs and org-mode is the central interface to all information and systems
• Graft it together with reusable building materials (elisp)
• Either everything is run in Emacs or everything can be run in the browser (including emacs)
• Specialized OS tools notwithstanding (VPN, Screen caps, password manager, AV, etc.)

Portable

• Run everything locally with few exceptions
• I should be able to take the entire setup onto any machine within a day
• It should be possible to get work done without an internet connection
• It needs to work on mobile, with a form factor that makes sense (e.g. ssh’ing from a phone might work but doesn’t fit)

Open

Favor building in the open and using materials that are inspectable, changeable, and long lasting.

• Whatever I build does not intend to be commercialized
• Share knowledge with others by making it open-source to those who might try to solve similar problems

Secure

Security and privacy needs to be designed in. Sensitive information is constantly being created and shared—I want to be a good steward of that.

• Endpoint security controls with good defaults and practical
• Use a password manager and make it easy to use everywhere (1Password is still the go to)
• Privacy controls built into what information goes where

One of one

Built specifically for me and my workflows without consideration another user of the system.

• Favor application building over library building
• Optimize convenience in maintaining and running tools

What should I build?

Finally, with a more clear understanding what it’s all for and the principles behind it, what should I actually build?

• Chat with org-roam notes
• Publishing pipeline
• Export backend for org-mode to notion
• Grammar and spelling linting in org-mode
• Search (tasks, notes, documents, email)
• Indexing content and sync’ing updates across multiple sources
• Web agents to crawl the internet to get an answer (research this topic, check for changes)
• Schedule a meeting consistently across calendars (sales, recruiting, other)
• A recurring task template for weekly review
• HubSpot AI question and answer (what tickets were over SLA last week)
• Auto follow-up emails
• Social media asset card builder (for posting notes)
• Mobile org agenda (org-roam projects in Beorg)
• Emacs config reproducibility (GitHub build)
• Browser in Emacs (xwidget browser that is scriptable)
• Tools to review someday and waiting tasks in org-agenda
• Fix syncing issues with Beorg and mobile capture (iOS Shortcuts to Beorg should sync first to avoid conflicts)

I started building AI for notes to help me chat with my library of notes. The result of that exploration is org-ai—my one of one software that helps me remember what I’ve previously written, summarize information. Under the hood it uses vector-based similarity search and LLMs and agent-based AI to extract useful information from my zettelkasten in a chat-based interface.

See also:

• Context is needed for practical LLM applications
• How langchain works
• Why vector databases are important to AI

I built org-ai using Python which exposes an AI chat interface through a simple CLI. This makes it a bit clunky when using it from Emacs—I would need to open up an instance of a terminal, activate the virtual environment, and execute the program to start the chat.

Luckily, Emacs is the ultimate editor building material and has a simple way of creating a shell called comint (command interpreter). Following the guide from Comint: Writing your own Command Interpreter, I was able to put together a simple integration that makes interacting with the python-based chat application more native feeling to emacs.

Checkout org-ai-shell

Sometimes I want to see how many headings are in an org-mode file I’m working in. For example, I like to know the number of items I have to refile.

This function will count the headings in a marked region:

(defun count-headings-in-region (start end)
  "Count the number of level 1 headings in the region."
  (interactive "r")
  (save-excursion
    (save-restriction
      (narrow-to-region start end)
      (goto-char (point-min))
      (let ((count 0))
        (while (re-search-forward "^\\* " nil t)
          (setq count (1+ count)))
        (message "Number of level 1 headings: %d" count)))))

This code was generated using ChatGPT with Emacs.

I tested my internet connection with and without NordLayer VPN to compare speed using Cloudflare’s new tool. Here are the results.

There’s quite a large drop in download speed and increase in latency when using the VPN which is to be expected.

Physically making progress on a project makes it much harder to undo due to loss aversion and the sunk cost fallacy.

In The Power Broker, we see an example where Robert Moses learns that by intentionally underfunding a large scale project to make it easy to pass but taking the first steps to physically build it, officials had no choice but to continue to support it financially. Officials facing elections would need to stand before the electorate and undo what was already done (not just on paper) and therefore take an unfavorable position that could cause them to lose their place. Essentially this would force officials to go against building parks which would be hugely unpopular.

Once you sink that first stake they’ll never make you pull it back up.

See also:

• Building incrementally is a technique for dealing with skepticism
• Robert Moses intentially utilizes chunking to create a physical void to encourage officials to complete a project

A survey by Greenhouse found that 76% of workers would look for another job if their company rolled back flexible work policies. It also found that 42% of job candidates won’t apply if their preferred working method isn’t available (hybrid, remote, etc.).

See also:

• Despite this, quit rates declined to pre-pandemic levels
• 54% percent of unemployed job hunters are looking to work from home
• 45% of jobs can be done remotely

When I first started programming, I thought everyone else was better than me at coding. I read about something new and thought I should do that too because they must know better.

Then my skills improved a little bit. I wrote my own solutions and rejected what others said because I knew better.

Then I gained experience. I trusted my judgement and realized I don’t always know better, but sometimes I do.

See also:

• People sometimes conflate programming with being smart
• The grug brained developer shares lessons from real world experience but we’re destined to repeat it due to the Dunning-Kruger effect
• Chesterton’s fence shows us that we can’t always know better

It takes four to six months to start seeing any results from SEO work. First you’ll see content getting indexed by Google which will result in more impressions. Next, you’ll see the site start to rank for more keywords. If all goes well, you’ll then see clicks to your website. If the site gains authority and content is actually helpful (bounce rate is sufficiently low), it will get ranked higher and drive more clicks.

See also:

• How to do SEO
• Effects of note blogging on SEO

When you have multiple Google workspace accounts with calendars, it makes scheduling difficult (e.g. an external account and an internal working account). Others can’t see your overall availability without knowing to check both calendars. Tools that don’t support multiple account calendars for one person (like Ashby) will end up scheduling conflicts.

How do you fix that?

The easiest way I’ve found is to sign up for a free account from Reclaim AI. There you can sync multiple calendars into one so that anyone looking at your main calendar can see the aggregate of all the calendars.

Now you can still have multiple accounts and calendars for different purposes (I have a sales account and a internal account) without disrupting others or scheduling conflicts.

See also:

• Convenience is king so the better strategy is not to educate people about your multiple calendars but to combine it into one they already know to check
• How to not be rude when sending a calendly link

All working knowledge has a decay curve of usefulness. If you rely on having up-to-date, deep technical knowledge as a manager, you will eventually lose the thing that makes you effective. From personal experience, this happens after 6 to 12 months from when your primary activity becomes managing people.

This is especially bad for managers that try to make technical decisions themselves—it works until it doesn’t. The results can be truly bad when the manager doesn’t know they are far out on the decay curve.

What can you do about it?

For managers, it’s a lesson in delegation and leadership. Support others with the right depth of technical knowledge to drive the decision and manage through them. Stay involved but moreso to apply good judgement—delegation not abdication. It’s possible to stay close to the details but try not to fool yourself into thinking it is at the same level of proficiency.

Personhood of self-driving cars and autonomouse vehicles might matter much more than we expect for everyone’s safety. By treating them as soulless objects, people are making roads more dangerous.

The other day I was in a dangerous situation. At an intersection I was about to walk through, a Cruise autonomous vehicle was waiting to turn right. A Tesla behind the Cruise got frustrated and went around it by going into the other lane, turning right and cutting off the Cruise. I was in the middle of the crosswalk and I got mad for the Cruise.

I suspect the Tesla driver cut off the Cruise because it was an autonomous vehicle. The annoyance I had was due to the Tesla driver not respecting the personhood of the Cruise.

Clearly this situation was more dangerous because of the interaction of a human and autonomous vehicle. This isn’t the only time this has happened and I’m sure we will see more examples.

See also:

• Am I internalizing an AI’s interiority and does that already indicate self-hood?
• Human intelligence is a special case of artificial intelligence

There is tremendous power in being able to simultaneously hold two ideas in one’s head that appear to be in opposition. Contradictions can create boundaries on thoughts—it’s usually unpleasant to have cognitive dissonance—and can lead to dogma. I’ve found that being able to stick with it, despite the discomfort, can be very powerful.

Here are a few examples:

Controlled self-deception where it’s optimal to be overconfident while fully aware of the role of luck plays in being successful.

A strange loop gives rise to human selfhood which is so powerful it is the thing we find to be the most real. Mindfulness shows us that the self is an illusion. Holding both ideas gives a much greater understanding of human nature.

Optimism that there is something new to find while also knowing there is pre-existing effort you will duplicate and trying to know the unknowable will lead to pessimism.

By combining headless browser automation tools with LLMs, you can create an agent that can navigate to websites. This opens up all sorts of new capabilities like scraping and summarizing web content.

What works well?

• Going to a news website and extracting a list of articles
• OpenAI gpt-4 works better than gpt-3 when using langchain to prompt to get headlines (e.g. asking for the top headlines on HackerNews gpt-3 fails without some hints about the HTML structure while gpt-4 works in one shot)

What doesn’t work well?

• Large web pages will hit the context limit for language models
• Logging into a website doesn’t work because OpenAI will reject completion requests that contain sensitive data

What else have others tried?

• AI browser automation
• Connecting Vimium (keyboard shortcut based browsing) to OpenAI Vision API
• Screen sharing with the Vision API