news.herich.cloud
Archived text mirror · columns · archive · trending · search
Hacker News November 9, 2026 15 min signal 2026-11-09

Writing as a thinking tool

Archived text mirror, captured for personal reading when the Signal ran. Formatting is approximate — read the original at the source.

### Writing as a thinking tool

-

Get link

-

Facebook

-

X

-

Pinterest

-

Email

-

Other Apps

-

November 07, 2026

In middle school I could not get through long passages no matter how hard I tried. I would read an entire page and find that nothing had registered, so I started taking notes out of desperation. This was the late 80s, and Tony Buzan's mind maps had just reached Turkey. This led me to produce pages and pages of notes that looked like spiderwebs. Creating those notes have helped me tremendously. I made sense of what I was reading by figuring out which branch they would hang off in my mind maps. I realized my pages were not for storing the information as much as they were for processing it.

It took me another ten years to understand why this works so well. During a stretch of PhD procrastination, I read Manuel Blum's advice to graduate students:

You are all computer scientists.

You know what FINITE AUTOMATA can do.

You know what TURING MACHINES can do.

For example, Finite Automata can add but not multiply.

Turing Machines can compute any computable function.

Turing machines are incredibly more powerful than Finite Automata.

Yet the only difference between a FA and a TM is that

the TM, unlike the FA, has paper and pencil.

Think about it.

It tells you something about the power of writing.

Without writing, you are reduced to a finite automaton.

With writing you have the extraordinary power of a Turing machine.

This is a crisp technical claim about which problems you can solve with writing. If you take the paper away, you downgrade yourself by an entire complexity class!

I think this explains a lot about human history as well. Language let us externalize some of our thinking, and our species got smarter. Writing let us externalize even more of it, and we got smarter again. I suspect this is also why LLMs are as capable as they are: so much of our intelligence is already deposited in language that a model trained on it inherits a good deal of intelligence for free.

Out-of-core execution

When we write, we are externalizing our thinking onto paper, and that is what raises our capability to think bigger thoughts. I liken this to out-of-core execution, or external memory algorithms.

A good example of this for me is reviewing a paper. When I read a paper, I think I understand it, and then I sit down to write the review and find out I understood maybe 60% of it. While writing the review, I end up contextualizing the paper better, and get to understand it fully. And sometimes I even realize the ideas are bigger than the authors noticed, and they connect to many other things.

Sometimes the unearthing goes further than understanding one paper. In 2018, I wrote a quick post about the anatomical similarities between Paxos and Nakamoto consensus. I had not started with that thesis originally. I started writing, and the connections got clearer as I went, and that post became the seed for one of our research papers. This is not uncommon, this is called freewriting. This is what happens when you give the machine a tape.

Writing is also the reason I remember anything. I refer back to my own blog constantly. Because I strained my brain writing those posts, rereading them re-fires the same neurons, and I reconstruct the understanding quickly. In this sense, the blog became my external memory. The thoughts I never wrote down do not stick well, because they were never fully thought.

If you think without writing, you only think you're thinking.

-- Leslie Lamport

Writing in the age of LLMs

Is writing for thinking getting obsolete now since you can now argue anything with a model that has read everything?

Well, the model has read everything except what is in your brain! It knows the literature, the standard framing, and the consensus. But it does not know your half-formed intuition about why the standard framing may be wrong for this particular case. AI made a lot of progress, but I don't trust an LLM to take the creative leap and make a new connection. I think that would require another AI breakthrough. So, if you open the chat immediately on anything, you lose the opportunity to write/think for yourself.

This is a real problem, and it seems to be spreading quickly. We have been celebrating Amazon's six-pager as a great example of writing-for-thinking. Bezos had said: "There is no way to write a six-page, narratively structured memo and not have clear thinking." Unfortunately, with LLMs, that sentence has stopped being true. You can now produce six pages with no thinking at all, and the six pages still look like evidence that the thinking happened.

A model optimizing next-token probability cannot do your thinking. If you trust it to hold the pen, no thinking would get done. As everyone turns their thinking down and becomes a meat-proxy for generated text, if you still keep writing yourself, you would still be thinking for yourself. So writing is now a comparative advantage, and a widening one!

Anyways, enough about why you should write. Here is my advice on how you should write.

Rule 1: Mess up

The first rule of writing club is to produce in bulk with no restraints at all. Don't criticize, don't fix the typos, don't write in full sentences if you don't feel like it. The goal in this phase is to just accumulate text and get to a zeroth draft you can work with.

McPhee argues best for why getting anything down matters so much. Even if you had a bad writing session, it gave your mind something to work with. After you get something down, you can spot problems with it and think of better ways of phrasing things. But none of that happens without the drafted version to react against.

This is also how research papers get written. Open a notes.org file and treat it as a lab notebook: write while you do the work, explore every tangent, produce without any pressure to be presentable. In the Köroğlu post I compared this to the foal fattened in a pitch-black stable before any training begins. The key part of that frame is the stable. During this phase you guard the idea from critics, including and especially yourself. Ideas start out fragile and easily squished. So suppress judgment for a while and see what the thing becomes.

Rule 2: Tidy up

Now you must become the critic, the editor. Forget that you wrote this. Imagine some other guy wrote it, and do a harsh review. Cut ruthlessly. Take delight in deleting text the way you would in deleting code. If you cannot bear to delete a good sentence, move it to a junk buffer at the bottom of the file so you can tell yourself you might bring it back. Spoiler: you won't.

Don't be discouraged by how bad the first draft was. McPhee says the way to do a piece of writing is three or four times over, never once. This is good news. Thinking in multiple drafts takes the pressure off: you don't have to be spontaneous, brilliant on the first pass, or finished today.

I think the reason writing works so well for thinking is that it slows you down while keeping you on the problem. In that extra time, the insights and connections get room to surface. Chunking)/abstracting happens in the background. Editing is then the magic trick where you pretend you had an organized thought all along. It is the packaging of the product.

Rule 3: Keep it simple, plain, and succinct

I am an Elements of Style guy. Strunk and White got it right, and their writing still reads fresh decades later. I adore Vonnegut too. His writing is simple as fuck and completely eloquent. It took a lot of balls to write that plainly. Complexity in prose is usually a place to hide sloppy thinking, or a way to weasel out of taking a stance. If you can't say it plainly, you probably haven't thought it through yet. And the way you think it through is by writing/editing.

Rule 4: Write without expectations

Write for yourself. The audience I have in mind is me. If others read it, that is a bonus, but the motivation has to be intrinsic, because the external rewards are far too delayed and too random to steer on. Writing like no one is watching also frees you up, and you can decide afterwards how much to share. Get your dopamine hit from the writing itself, not from people reading or sharing what you wrote, as that is very unreliable.

I have been writing and sharing on this blog since 2011, and around 2016 I started running into people at conferences who read it. I assumed it was a fluke, but it kept happening. Writing with a human voice turns out to get a lot of attention, and I am still surprised by how much. Paradoxically, you seem to get an audience only if you weren't doing it for the audience.

Rule 5: Put it on the schedule

You should stop trying to get inspiration to write and start scheduling it. Waiting for inspiration doesn't work, instead, putting your butt on seat and writing breeds good ideas for writing.

I find that keeping a posting schedule for the blog keeps me in "a writing frame of mind", which is really "a noticing frame of mind". Many weeks I tell myself a topic isn't interesting, but I start writing about it anyway, and then, what do you know, I am startled by the fount of interesting things that surfaces.

I also feel relieved after writing something as the thought is out of my system, I have closure on it, and I have room to think new thoughts. If a week goes by without a post, I feel clogged. So put writing on the calendar and keep it there until it no longer needs to be on the calendar.

my advice research-advice writing

-

Get link

-

Facebook

-

X

-

Pinterest

-

Email

-

Other Apps

Comments

Przemek said…

I just want to thank you for inspiration. Your post comes exactly at time I needed it.

Have a good day, best regards, Przemek

November 8, 2026 at 2:11 PM

Anonymous said…

Bookmarked. Now my favorite post on this topic. Had never put together the point made early about finite automata and Turing machines. Brilliant. The rest of the essay also beautifully delivered and full of great advice. You should add a link to Paul Graham's excellent essay: https://paulgraham.com/writes.html

November 8, 2026 at 3:00 PM

motion control ai said…

The point about LLMs not knowing your half-formed intuition is spot on. I've started drafting my own notes before opening ChatGPT, and the difference in what I actually learn is huge.

November 8, 2026 at 10:13 PM

Post a Comment

### Popular posts from this blog

The Man from the Future: Why Johnny Can't Stop Abstracting

-

October 26, 2026

I have come to suspect that to most people thinking is painful. Some of us are addicted to thinking. Some of us find it a necessity. Johnny enjoyed it. I even have the suspicion that he enjoyed almost nothing else. -- Edward Teller, eulogizing John von Neumann I listened to Ananyo Bhattacharya's " The Man from the Future: The Visionary Life of John von Neumann " in my car during the many commute hours Bay Area traffic afforded me. I thought I should share the Johnny phenomena here. I knew about von Neumann being a very influential mathematician/scientist/engineer but the full list still left me bedazzled. In his 53 years of life (1903-1957), von Neumann seeded so many fields. Every time there was an important discovery in physics, mathematics or computation, John von Neumann was there. Set theory and the foundations of mathematics. The mathematical formulation of quantum mechanics. Operator algebras (still called von Neumann algebras). Ergodic theory. Game theory. Expect...

Read more >>

The Safest Job from AI may be Writing

-

August 31, 2026

Today, tech folk are scrambling to change their workflows to meet newly inflated 5X productivity quotas, while getting pummeled under the cognitive debt of agent-generated code. With every new model release, the gap is widening and humans are becoming more of a bottleneck in the loop, approaching closer to obsolescence as "coders". While the programmer's job description is getting completely refactored, writing remains surprisingly unaffected. LLMs have gotten very good at generating code, but I am appalled at the absolute shit they spew as prose. They always follow the same robotic cadence and cliches, and sprinkle the same tired vocabulary all around. They take my broken yet soulful writing and transform it into a plastic soulless word slop in the name of improving prose. Their writing communicates no actual understanding and insight. I think we are all developing a visceral ick reaction to AI writing. It is trapped in the uncanny valley, and it may be stuck there for ...

Read more >>

The Two Abstractions of System Design: Hide or Reduce

-

May 08, 2026

When talking about TLA+, I keep referring to "abstraction" as the most important thing to learn . And it is about the hardest to learn as well. But a contradiction has been bugging me. Aren't CS people already supposed to be good at abstraction? Isn't abstraction supposed to be at the root of OS, networking, software engineering? Abstract Data Types (ADTs) are a staple of every in CS curriculum. So why do I (and every other formal methods/modeling person) see such a large skill gap in abstraction, and flag it as the core, make-or-break skill for modeling? I think I finally get to the root of this cognitive disonance. There are two kinds of "abstraction" conflated under the same umbrella term. Modularity abstraction: This is the traditional abstraction taught in CS curricula as ADTs, APIs, layered design, etc. It is all about encapsulation, drawing boundaries, and hiding internals. Modeling abstraction: This is what I talk about when I talk about abstracti...

Read more >>

The Agentic Self: Parallels Between AI and Self-Improvement

-

January 02, 2026

2025 was the year of the agent. The goalposts for AGI shifted; we stopped asking AI to merely "talk" and demanded that it "act". As an outsider looking at the architecture of these new agents and agentic system, I noticed something strange. The engineering tricks used to make AI smarter felt oddly familiar. They read less like computer science and more like … self-help advice . The secret to agentic intelligence seems to lie in three very human habits: writing things down, talking to yourself, and pretending to be someone else. They are almost too simple. The Unreasonable Effectiveness of Writing One of the most profound pieces of advice I ever read as a PhD student came from Prof. Manuel Blum, a Turing Award winner. In his essay "Advice to a Beginning Graduate Student", he wrote: "Without writing, you are reduced to a finite automaton. With writing you have the extraordinary power of a Turing machine." If you try to hold a complex argument enti...

Read more >>

In Search of a Compositional Theory of Self-Stabilization

-

September 21, 2026

My quest for a principled solution for metastable failures has taken me back to my roots on self-stabilization, as this recent paper related the problem to composition of self-stabilizing systems.  But, my literature search for recent work on composing self-stabilizing systems didn't yield anything useful. The layered stabilization idea was already in place by the early 2000s, and nothing fundamental seems to have been added since. Frustrating. So I decided to attack the problem using the concrete example I have. I had composed a rely-guarantee TLA+ model of a retry storm as two components with contracts . That model reproduces metastable failure because the composition that worked from good states failed to work when a large shock removes the base case that let the two conditions hold each other up. Searching for  rely-guarantee based composition from every state, turned up a 2017 control theory paper by Kim, Arcak and Seshia, "A Small Gain Theorem for Parametric Assume-Gua...

Read more >>

Learning about distributed systems: where to start?

-

June 10, 2020

This is definitely not a "learn distributed systems in 21 days" post. I recommend a principled, from the foundations-up, studying of distributed systems, which will take a good three months in the first pass, and many more months to build competence after that. If you are practical and coding oriented you may not like my advice much. You may object saying, "Shouldn't I learn distributed systems with coding and hands on? Why can I not get started by deploying a Hadoop cluster, or studying the Raft code." I think that is the wrong way to go about learning distributed systems, because seeing similar code and programming language constructs will make you think this is familiar territory, and will give you a false sense of security. But, nothing can be further from the truth. Distributed systems need radically different software than centralized systems do.  --A. Tannenbaum This quotation is literally the first sentence in my distributed systems syllabus. Inst...

Read more >>

Building a Database on S3

-

March 04, 2026

Hold your horses, though. I'm not unveiling a new S3-native database. This paper is from 2008. Many of its protocols feel clunky today. Yet it nails the core idea that defines modern cloud-native databases: separate storage from compute. The authors propose a shared-disk design over Amazon S3, with stateless clients executing transactions. The paper provides a blueprint for serverless before the term existed. SQS as WAL and S3 as Pagestore The 2008 S3 was painfully slow, and 100 ms reads weren't unusual. To hide that latency, the database separates "commit" from "apply". Clients write small, idempotent redo logs to Amazon Simple Queue Service (SQS) instead of touching S3 directly. An asynchronous checkpoint by a client applies those logs to B-tree pages on S3 later. This design shows strong parallels to modern disaggregated architectures . SQS becomes the write-ahead log (WAL) and logstore. S3 becomes the pagestore. Modern Aurora follows a similar logic : t...

Read more >>

Foundational distributed systems papers

-

February 27, 2021

I talked about the importance of reading foundational papers last week. To followup, here is my compilation of foundational papers in the distributed systems area. (I focused on the core distributed systems area, and did not cover networking, security, distributed ledgers, verification work etc. I even left out distributed transactions, I hope to cover them at a later date.)  I classified the papers by subject, and listed them in chronological order. I also listed expository papers and blog posts at the end of each section. Time and State in Distributed Systems Time, Clocks, and the Ordering of Events in a Distributed System. Leslie Lamport, Commn. of the ACM,  1978. Distributed Snapshots: Determining Global States of a Distributed System. K. Mani Chandy Leslie Lamport, ACM Transactions on Computer Systems, 1985. Virtual Time and Global States of Distributed Systems.  Mattern, F. 1988. Practical uses of synchronized clocks in distributed systems. B. Liskov, 1991. Exp...

Read more >>

What I'd do as a College Freshman in 2025

-

April 10, 2025

Do Computer Science Absolutely. Still would. Many are spooked by LLMs. Some, like Jensen Huang, argue that "nobody has to learn how to program."   I argue the opposite . And I double down.  Being supported by AI tools is not a substitute for mastery . You can’t borrow skills. You have to earn them.   Computer science builds vital skills : hacking, debugging, abstract thinking, and quick adaptation. These don’t go out of style.   Do STEM. It’s LLM-resistant. LLMs can retrieve and remix information, but do you know what to do with them? Like the dog chasing the car, what now? STEM teaches you that. It teaches you to think, to reason, to act. It gets you from information to wisdom. But only after you've mastered the foundations. We're heading into the age of π-shaped people: depth in two areas, and generalist across . Building depth first, and then ranging is good strategy .   So yes, I would learn the foundations of both CS and AI. And then do AI + X, where X is s...

Read more >>

← latest Signal