Markov Chains Are the Original Language Models

<h1>Hacker News, sans AI</h1>
I like Hacker News, but I do not love that so much of it has turned into dis­cus­sion of a sin­gle topic: AI. So, I have cre­ated my own ver­sion.
A ver­sion of Hacker News, with­out AI.
<a href="/hnsansai">HNSansAI</a> pulls from the of­ﬁ­cial Hacker News API, looks through the con­tent of each ar­ti­cle, and dis­cards any that men­tion a term re­lated to “AI”. That in­cludes stuff like:
<ul>
<li>“OpenAI”</li>
<li>“Anthropic”</li>
<li>“Copilot”</li>
<li>“LLM”</li>
<li>…and many more.</li>
</ul>

I like HackerNews, but I don't love that so much of it has turned into discussion of a single topic: AI. This is a version of HackerNews, filtered to remove any article focusing on __AI__. Refreshes about every ten minutes.

I like HackerNews, but I don’t love that so much of it has turned into dis­cus­sion of a sin­gle topic: AI. This is a ver­sion of HackerNews, ﬁl­tered to re­move any ar­ti­cle fo­cus­ing on AI. Refreshes about every ten min­utes.

Hacker News sans AI

<h1>Do Not Write with an LLM</h1>
<img src="/images/green_bird.webp" alt="A photo taken by myself of a green bird.">
<h2>A Growing Trend</h2>
I have been see­ing an in­creas­ingly preva­lent trend of peo­ple show­ing up in on­line spaces proudly ﬂaunt­ing that they are writ­ing with the as­sis­tance of AI.
I of­ten see them clar­ify that they are go­ing fur­ther than let­ting the model per­form gram­mar or fact-check­ing.
They are de­scrib­ing an idea to an LLM, and giv­ing it com­plete con­trol over the ﬁ­nal writ­ten doc­u­ment.
They seem to be proud of this. They should­n’t be.
<h2>What Does Not Work</h2>
Writing seems to be a shadow of a more fun­da­men­tal and use­ful process we like to call “thinking”.
There is a rea­son why LLMs, which are the clos­est thing we cur­rently have to “software that thinks” is trained to think through writ­ing.
It seems log­i­cal, then, that we can use this “software that writes” to help along our own think­ing process, right? Wrong.
Writing is one of the most cere­bral ac­tiv­i­ties that hu­mans do on a reg­u­lar ba­sis.
<a href="https://elijahpotter.dev/articles/why-i-talk-to-myself">I try to sit down and write about a com­plex topic at least once a week.</a>
There are a num­ber of rea­sons I do that per­tain­ing to my job in par­tic­u­lar, but there are more gen­er­ally ap­plic­a­ble rea­sons that can ap­ply to any pro­fes­sion.
When a math­e­mati­cian needs to think crit­i­cally about some the­o­rem or proof, they of­ten turn to a dry-erase board or a chalk­board.
The math­e­mati­cian then writes in clear no­ta­tion what they imag­ine the prob­lem to look like in their heads.
From there, they can ma­nip­u­late that no­ta­tion un­til they reach their de­sired out­come.
The English lan­guage is ex­tremely sim­i­lar, with a key dif­fer­ence.
Math­e­mat­i­cal no­ta­tion is specif­i­cally de­signed for a nar­row do­main.
Nat­ural lan­guages, on the other hand, can be ap­plied to any ﬁeld.
By writ­ing your idea down on pa­per (or in a Google Doc, it does not mat­ter), you give it sub­stance.
This sub­stance can then be shaped it­er­a­tively to­wards a goal of some kind.
No great ideas were writ­ten down on the ﬁrst try.
They started as a vague no­tion, and through writ­ing and rewrit­ing, they be­came some­thing con­crete and valu­able.
You can­not dic­tate a vague no­ta­tion to an LLM and ex­pect it to spit out some­thing tan­gi­bly valu­able.
Any at­tempt to do so is lazy, and it will re­sult in fail­ure.
I have seen it in the wild, and frankly, it is a lit­tle em­bar­rass­ing.
<a href="https://ammil.industries/i-know-you-didnt-write-this/">This ar­ti­cle</a> feels es­pe­cially rel­e­vant to­day.
<h2>What Does Work</h2>
Using an LLM for re­search can be very ef­fec­tive.
Searches to ChatGPT or Perplexity can sur­face in­for­ma­tion faster than dig­ging around in a book you read three months ago.
For lots of searches, these two sources have com­pletely re­placed Google and DuckDuckGo for me.
They’re also quite ex­cel­lent fact-check­ers.
I’ve seen that plenty of folks have re­ceived quite good re­sults by past­ing their work into an LLM with an in­ter­net tool (like ChatGPT with Thinking en­abled).
Finally, I’ve per­son­ally found that LLMs are quite good at ﬁnd­ing places where I sim­ply for­got to in­sert con­text.
Some­times I for­get to de­ﬁne a term or in­sert a rel­e­vant link.
Even small mod­els like <code>gemma3n:e2b</code> can catch me.
<h2>What You Should Be Doing</h2>
When you need to com­mu­ni­cate an idea in your head, sit down with a notepad and a key­board and ex­plain it.
I per­son­ally think you should use a gram­mar checker, since they are far less likely to im­pede your thought process, but if you need to, you can in­struct ChatGPT to cri­tique your work once it is ﬁn­ished.
If an idea de­serves an au­di­ence, you’re ca­pa­ble of writ­ing it out your­self.
In the same vein, if you can vaguely de­scribe it to ChatGPT, you can vaguely de­scribe it to your in­tended au­di­ence.
Do your­self a fa­vor and skip the mid­dle­man.
<h2>What We Should Be Building</h2>
Now, I’d like to en­ter the sec­tion where I talk specif­i­cally about what this all means for peo­ple who cre­ate tools for writ­ers.
That in­cludes both Harper and WordPress.
A tool that helps some­one write is a tool that di­rectly in­ter­faces with how that per­son thinks.
That might in­clude what they think about, but more con­cretely I am re­fer­ring to the ac­tual day-to-day process of think­ing through com­plex ideas.
If you don’t be­lieve me, it’s prob­a­bly be­cause you skipped ahead in­stead of read­ing this post from the be­gin­ning.
Most cru­cially, we can­not al­low our­selves to build tools that dis­suade peo­ple from ex­press­ing their ideas in the way they imag­ine.
This can take the form of fric­tion, like build­ing tools that are so cum­ber­some that one dreads to open them at the start of the work­day.
This can also take the form of a tool that crushes or over­writes an au­thor’s core mes­sage.
A com­mon com­plaint I hear about Grammarly (from peo­ple who have switched to Harper from Grammarly) is that it’s too de­mand­ing. When they write prose in a cre­ative or un­usual fash­ion, their ser­vice of­ten forces them back into a colder and more for­mal way of speak­ing.
We don’t want to be like them.
For Harper, that means we need to be di­verse in our train­ing datasets and mind­ful of feed­back from our users.
For WordPress, it means we need to en­cour­age our LLM in­te­gra­tions to tread lightly and re­spect­fully.
They need to ac­cept when they’re wrong.
Just as any good hu­man should.
<blockquote>
Months af­ter writ­ing this post, I came across an­other.
Au­thor Cynthia Dunlop gives <a href="https://writethatblog.substack.com/p/dev-reaction-to-ai-blog-posts">a great overview of how de­vel­op­ers re­act to blog posts writ­ten by AI</a>.
I highly sug­gest you take a look if you have more time.
</blockquote>

I have been seeing an increasingly prevalent trend of people showing up in online spaces flaunting that they are writing with the assistance of AI. They seem to be proud of this. They shouldn't be.

I have been see­ing an in­creas­ingly preva­lent trend of peo­ple show­ing up in on­line spaces ﬂaunt­ing that they are writ­ing with the as­sis­tance of AI. They seem to be proud of this. They should­n’t be.

Do Not Write with an LLM

<h2>What We Can Learn from New York City</h2>
<img src="/images/nyc_from_a8c_noho_office.png" alt="The view from Automattic&#x27;s NoHo Office">
Today marks the end of my ﬁrst week in New York City. It is an ex­cep­tion­ally ac­tive place. Neither the hus­tle nor the bus­tle ever stops. Sirens sound at all hours of the day and you’re con­stantly smelling en­tirely new things. I’ve been told New York is an ac­quired taste. I can see why they might say that.
Back home, it’s rare I would walk down the street and over­hear a ran­dom founder talk about their lat­est Y Combinator fund­ing round. Here, it’s ap­par­ently com­mon enough to oc­cur at least once a week. Everywhere I look, I ﬁnd the head­quar­ters of multi­na­tional com­pa­nies and the of­ﬁces of ma­jor gov­ern­men­tal or­ga­ni­za­tions.
<h3>The City is Practical</h3>
If I were to de­scribe Portland, Oregon (which I vis­ited a few weeks ago to at­tend WordCamp US) in one word, it would be op­ti­mistic. If I were to de­scribe New York in one word, based on my in­cred­i­bly lim­ited ex­pe­ri­ence thus far, it would be prac­ti­cal.
The city and the peo­ple who re­side in­side take very lit­tle ﬂuff. They say things as they are, in the kind­est way pos­si­ble. If they don’t think your pro­posed route to a restau­rant will work, they stop you be­fore you ﬁn­ish ex­plain­ing and put you on the right track. It saves every­one time and en­ergy.
This is some­thing I per­son­ally need to prac­tice more of­ten in my work. It is com­mon for me to avoid pro­duc­tive con­ver­sa­tions or code re­views, only be­cause they might evoke a neg­a­tive emo­tion in the short-term. These same con­ver­sa­tions usu­ally pro­duce pos­i­tive emo­tions in the long term, so it is in my in­ter­est and in my col­league’s in­ter­est to have them. NYC is slowly train­ing a habit to rec­og­nize these sit­u­a­tions more of­ten and make the right de­ci­sion.
I don’t think I’m alone here. I think a plu­ral­ity of peo­ple in the mod­ern world could ben­e­ﬁt from a bolder mind­set that takes on tough con­ver­sa­tions, rather than shy­ing away.
<h3>We’re Not Done Yet</h3>
I’ll be in New York for an­other week. If all goes well, I’ll have more op­por­tu­ni­ties to learn from the other mem­bers of the AI group. It’s been great to hang out with James and the gang. The cul­ture here is in­cred­i­bly invit­ing. I am im­mensely grate­ful to be here.

I've been told New York is an acquired taste. I can see why they might say that.

I’ve been told New York is an ac­quired taste. I can see why they might say that.

Elijah Potter

What We Can Learn from New York City

The City is Practical

We’re Not Done Yet

Comments

Other Stuff

Markov Chains Are the Original Language Models

Hacker News sans AI

Do Not Write with an LLM