\n \n What are you feeling?\n

\n \n

Peaceful

calm

content

satisfied

secure

centered

relieved

confident

comfortable

composed

fulfilled

Affectionate

warm

tender

appreciative

passionate

compassionate

loving

touched

Happy

glad

pleased

excited

joyful

delighted

amused

encouraged

grateful

hopeful

thrilled

moved

Playful

energetic

expansive

adventurous

mischievous

silly

light

hearted

enthusiastic

lively

optimistic

Interested

inspired

curious

surprised

stimulated

amazed

absorbed

fascinated

engaged

eager

enchanted

intrigued

motivated

Rested

alert

alive

invigorated

refreshed

rejuvenated

relaxed

renewed

Sad

lonely

hopeless

hurt

sorrowful

grief

despair

discouraged

disappointed

helpless

Confused

hesitant

indifferent

suspicious

puzzled

troubled

bewildered

baffled

conflicted

torn

uncertain

skeptical

Scared

terrified

startled

shocked

nervous

anxious

worried

desperate

afraid

cautious

insecure

Uncomfortable

uneasy

embarrassed

fragile

vulnerable

ashamed

distressed

disturbed

bored

restless

jealous

impatient

exasperated

stressed

envious

tense

concerned

tired

weary

exhausted

overwhelmed

Angry

irritable

annoyed

agitated

frustrated

disgusted

furious

enraged

mad

angry

bitter

\n \n \n What are you needing?\n \n \n

Subsistence

air

food

health

movement

safety

rest/sleep

shelter

touch

water

Security

consistency

efficiency

predictability

order

structure

protection

stability

accountability

trust

reassurance

Freedom

autonomy

choice

ease

independence

responsibility

space

spontaneity

empowerment

self-expression

Well-being

health

healing

rest

privacy

self-care

nurturing

Relaxation

humor

joy

play

fun

recreation

pleasure

rejuvenation

Connection

affection

appreciation

attention

closeness

companionship

harmony

intimacy

love

support

tenderness

warmth

To Matter

acceptance

care

compassion

consideration

empathy

kindness

respect

to be heard

to be seen

understanding

Community

belonging

communication

cooperation

equality

inclusion

mutuality

participation

partnership

shared reality

Awareness

authenticity

competence

dignity

growth

honesty

integrity

clarity

discovery

learning

Meaning

aliveness

challenge

consciousness

contribution

creativity

effectiveness

exploration

integration

purpose

Transcendence

beauty

balance

celebration

communion

faith

flow

hope

inspiration

mourning

peace

presence

wholeness

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`\\n ${escapeXml(p.description)}`\n : \"\"\n }\n `,\n )\n .join(\"\\n\");\n\n const xml = `\n\n \n Steve Krouse\n ${SITE_URL}\n Essays by Steve Krouse\n en-us\n \n${items}\n \n`;\n\n return new Response(xml, {\n headers: {\n \"Content-Type\": \"application/rss+xml; charset=utf-8\",\n },\n });\n}\n","children",[],[201],"ee41fb38-2abf-11f1-876b-42dde27851f2","post-helpers.tsx","019d3531-6d35-73dc-a4dd-387e9ff56f52",["D",1774713924926],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { renderToString } from \"https://esm.sh/react-dom@18.2.0/server\";\nimport {\n listFilesByPath,\n readFile,\n} from \"https://esm.town/v/std/utils/index.ts\";\nimport ReactMarkdown from \"https://esm.sh/react-markdown@9?deps=react@18.2.0\";\nimport rehypeSlug from \"https://esm.sh/rehype-slug@6?deps=react@18.2.0\";\nimport rehypeAutolinkHeadings from \"https://esm.sh/rehype-autolink-headings@7?deps=react@18.2.0\";\nimport rehypeRaw from \"https://esm.sh/rehype-raw@7?deps=react@18.2.0\";\nimport ValTown from \"npm:@valtown/sdk@1.9.0\";\nimport { PostTemplate } from \"./PostTemplate.tsx\";\n\nexport interface PostMeta {\n title: string;\n tags: string[];\n slug: string;\n date?: string;\n description?: string;\n}\n\nfunction parseFrontmatter(markdown: string): { meta: Record; content: string } {\n const match = markdown.match(/^---\\n([\\s\\S]*?)\\n---\\n([\\s\\S]*)$/);\n if (!match) return { meta: {}, content: markdown };\n const meta: Record = {};\n for (const line of match[1].split(\"\\n\")) {\n const idx = line.indexOf(\":\");\n if (idx > 0) {\n meta[line.slice(0, idx).trim()] = line.slice(idx + 1).trim();\n }\n }\n return { meta, content: match[2] };\n}\n\n// Shared metadata for all loaded posts\nlet postMetadata: PostMeta[] = [];\n\nexport function getPostMetadata(): PostMeta[] {\n return postMetadata;\n}\n\nasync function loadFile(file: ValTown.Vals.Files.FileRetrieveResponse) {\n if (file.name.endsWith(\".tsx\")) {\n return (await import(file.links.module)).default;\n } else if (file.name.endsWith(\".html\")) {\n const html = await readFile(file.path);\n return () =>\n new Response(html, { headers: { \"Content-Type\": \"text/html\" } });\n } else if (file.name.endsWith(\".md\")) {\n const raw = await readFile(file.path);\n const { meta, content } = parseFrontmatter(raw);\n\n // Title from frontmatter, or first h1, or filename\n const titleMatch = content.match(/^#\\s+(.+)$/m);\n const title = meta.title || (titleMatch ? titleMatch[1] : file.name.replace(\".md\", \"\"));\n\n // Tags from frontmatter (comma-separated)\n const tags = meta.tags\n ? meta.tags.split(\",\").map((t: string) => t.trim()).filter(Boolean)\n : [];\n\n const date = meta.date || undefined;\n const description = meta.description || undefined;\n\n // OG image: explicit frontmatter, or auto-detect first image in markdown\n const firstImageMatch = content.match(/!\\[.*?\\]\$(.*?)\$/);\n const ogImage = meta.ogImage || (firstImageMatch ? firstImageMatch[1] : undefined);\n\n const slug = file.name.split(\".\")[0].toLowerCase();\n\n // Store metadata\n postMetadata.push({ title, tags, slug, date, description });\n\n return function () {\n return new Response(\n renderToString(\n \n {content}\n {tags.length > 0 && (\n

\n {tags.map((tag, i) => (\n \n {i > 0 && \" · \"}\n \n {tag}\n \n \n ))}\n

\n )}\n ,\n ),\n { headers: { \"Content-Type\": \"text/html\" } },\n );\n };\n }\n}\n\nasync function getPosts() {\n postMetadata = []; // reset on reload\n const posts = Object.fromEntries(\n await Promise.all(\n (await listFilesByPath(\"posts\"))\n .map(\n async (\n file,\n ) => [\n file.name.split(\".\")[0].toLowerCase(),\n await loadFile(file), // could defer this until someone wants this particular file\n ],\n ),\n ),\n );\n return posts;\n}\nasync function getPostsBounded() {\n const posts = await Promise.race([\n getPosts(),\n new Promise((resolve) => setTimeout(resolve, 5000)),\n ]);\n if (!posts) {\n console.error(\"Timeout fetching posts\");\n return [];\n }\n console.log(`Fetched ${Object.keys(posts).length} posts`);\n return posts;\n}\n\nlet posts;\nexport async function ensurePostsLoaded() {\n if (!posts) posts = await getPostsBounded();\n}\nexport async function renderPage(req: Request) {\n await ensurePostsLoaded();\n console.log(posts);\n\n // render /posts/* in this val\n const url = new URL(req.url);\n const name = url.pathname.slice(1);\n const post = posts[name.toLowerCase()];\n if (post) return post(req);\n\n // look up page on github pages\n const githubPagesUrl =\n `https://stevekrouse.github.io${url.pathname}${url.search}`;\n const response = await fetch(\n new Request(githubPagesUrl, {\n method: req.method,\n headers: new Headers({\n ...Object.fromEntries(req.headers),\n \"User-Agent\": \"Val Town\",\n }),\n }),\n );\n if (response.status !== 404) return response;\n\n // return 404\n return new Response(\n renderToString(

404: stevekrouse.com{url.pathname}{url.search}

),\n { status: 404, headers: { \"Content-Type\": \"text/html\" } },\n );\n}\n",[],[211],"ee41de5a-2abf-11f1-876b-42dde27851f2","main.tsx","019d3531-6d35-73dc-a4dd-3601f8159dfb",["D",1774713924926],"http","/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { renderToString } from \"https://esm.sh/react-dom@18.2.0/server\";\nimport { Homepage } from \"./index.tsx\";\nimport { Hono } from \"npm:hono@4.0.0\";\nimport { renderPage, getPostMetadata } from \"./post-helpers.tsx\";\nimport { generateRSSFeed } from \"./rss.tsx\";\nimport { listFilesByPath } from \"https://esm.town/v/std/utils/index.ts\";\nimport { PostTemplate } from \"./PostTemplate.tsx\";\n\nconst SOURCE = \"https://www.val.town/x/stevekrouse/stevekrouse_dot_com\";\n\n// Cache blog posts metadata for source links\nlet blogPostsCache: Map | null = null;\n\nasync function getBlogPostsMap() {\n if (blogPostsCache) return blogPostsCache;\n \n const files = await listFilesByPath(\"posts\");\n blogPostsCache = new Map(\n files.map(file => {\n const slug = file.name.split(\".\")[0].toLowerCase();\n const sourceUrl = `${SOURCE}/code/${file.path}`;\n return [slug, sourceUrl];\n })\n );\n \n return blogPostsCache;\n}\n\nfunction getBlogPostBySlug(slug: string, postsMap: Map) {\n const sourceUrl = postsMap.get(slug);\n if (!sourceUrl) return null;\n return { valSourceURL: sourceUrl };\n}\n\nfunction renderTagsPage(tag?: string) {\n const allPosts = getPostMetadata();\n\n // Build tag -> posts map\n const tagMap = new Map();\n for (const post of allPosts) {\n for (const t of post.tags) {\n if (!tagMap.has(t)) tagMap.set(t, []);\n tagMap.get(t)!.push({ title: post.title, slug: post.slug });\n }\n }\n\n // Sort tags alphabetically\n const sortedTags = [...tagMap.keys()].sort((a, b) => a.localeCompare(b));\n\n if (tag) {\n // Single tag page\n const decodedTag = decodeURIComponent(tag);\n const postsForTag = tagMap.get(decodedTag) || [];\n return new Response(\n renderToString(\n \n

Posts tagged \"{decodedTag}\"

\n ← All tags\n

\n {postsForTag.length === 0\n ?

No posts found with this tag.

\n : (\n

\n {p.title}\n

\n )}\n ,\n ),\n { headers: { \"Content-Type\": \"text/html\" } },\n );\n }\n\n // All tags page\n return new Response(\n renderToString(\n \n

\n Steve Krouse!!!!\n

\n 👋 Hi, I'm Steve. I live in Prospect Heights, Brooklyn.\n

\n I build{\" \"}\n Val Town, a collaborative\n website to code in the cloud.\n

\n I founded the Future of Coding podcast & community, and\n co-cofounded The Coding Space. I've worked at Looker, First Round\n Capital, and studied computer science at Penn.\n

\n To learn how to best work with me, read my{\" \"}\n README.\n

\n This site was{\" \"}\n \n built in Val Town\n .\n

Projects

\n 2022 Jul -\n Val Town\n
\n 2022 Sep -\n Date Me Directory\n
\n 2022 Jan -\n \n Zaplib\n \n
\n 2021 Mar -\n Compose\n
\n 2017 Jul -\n \n Future of Coding\n \n
\n 2016 May -\n \n WoofJS\n \n
\n 2015 Jul -\n The Coding Space\n

\n\n

Essays

\n 2026 Mar -\n \n steve-eval – getting AI to write like me\n \n
\n 2026 Mar -\n \n Reports of code's death are greatly exaggerated\n \n
\n 2026 Mar -\n \n What if you never had to get an API key ever again?\n \n
\n 2026 Mar -\n \n Personal Investor Relations\n \n
\n 2026 Feb -\n \n Intelligence Buying Intelligence\n \n
\n 2026 Jan -\n \n Advice to college students in 2026\n \n
\n 2025 Mar -\n \n Find a model\n \n
\n 2025 Feb -\n \n I proposed to my girlfriend in Quordle\n \n
\n 2022 Nov -\n \n End-programmer Programming\n \n
\n 2019 Apr -\n \n Lunch with Alan Kay: how to become educated enough to invent\n the future\n \n
\n 2018 Oct -\n \n The \"Next Big Thing\" is a Room\n \n
\n 2017 Oct -\n Life Plan\n
\n 2017 Oct -\n \n WoofJS.com One Year Later\n \n
\n 2017 Jul -\n \n The Coding Space: Two Year Update\n \n
\n 2017 Jul -\n \n Learn to code in two-player mode\n \n
\n 2017 May -\n \n The Rose Project (April 2017)\n \n
\n 2017 Mar -\n \n The Rose Project (March 2017)\n \n
\n 2017 Jan -\n \n Resources for creating front-end programming languages and\n frameworks in 2017\n \n
\n 2016 Nov -\n \n Types are shapes — a graphical programming exploration\n \n
\n 2016 Nov -\n \n TEDD — Technologically-Enabled Direct Democracy\n \n
\n 2016 Aug -\n \n Goodbye, Seymour\n \n
\n 2016 Jul -\n \n The Trick to Teach Anonymous Functions to 11-Year-Olds\n \n
\n 2016 Jul -\n \n Scratch Has a Marketing Problem\n \n
\n 2016 Jul -\n \n WoofJS — making JavaScript learnable\n \n
\n 2016 Jun -\n \n The Coding Space: A year in review\n \n
\n 2016 Feb -\n \n The 4 Steps to Giving Magical Praise\n \n
\n 2016 Jan -\n \n \"Why do we need to learn this?\"\n \n
\n 2015 Dec -\n The Lens Lens\n
\n 2015 Dec -\n \n The College of the Future\n \n
\n 2015 Dec -\n \n Stop Paying $250k for a Degree and a Network\n \n
\n 2015 Nov -\n \n Incidentally for machines\n \n
\n 2015 Jun -\n \n A Cursory Education On Education\n \n
\n 2014 Jun -\n \n One year ago today I blogged that I'd never drop out of\n college\n \n
\n 2013 Sep -\n \n Making friends at the world's largest hackathon\n \n
\n 2013 Jul -\n Be a quitter\n
\n 2013 Jun -\n \n What It Really Means To Drop Out\n \n
\n 2013 May -\n Paying it Forward\n
\n 2013 Mar -\n Being Nice Matters\n
\n 2013 Nov -\n \n When nobody's watching\n \n
\n 2013 Nov -\n \n Stuffed Animal Priorities\n \n
\n 2013 Feb -\n \n Medieval Luxury, Modern Torture, and Education 2.0\n \n
\n 2013 Jan -\n Theseus and The Minotaur\n
\n 2012 Dec -\n \n IP And Innovation: A Software Case Study\n \n
\n 2012 Dec -\n \n Scheming Sororities and the Gale-Shapley Algorithm\n \n
\n 2012 Dec -\n \n The Arbitrary and The Elegant\n \n
\n 2012 Nov -\n Start Small\n

\n\n

Podcasts

\n 2023 Aug -\n \n JSParty × val.town with Steve Krouse\n \n
\n 2023 Aug -\n \n Scaling Devtools × val.town with Steve Krouse\n \n
\n 2023 Jul -\n \n Supper Club × val.town with Steve Krouse\n \n
\n 2023 Jul -\n \n CS Primer – What makes programming fun?\n \n
\n 2023 Apr -\n \n Devtools.fm – val.town\n \n
\n 2017 Jul -\n \n Future of Coding Podcast\n \n
\n 2016 Oct -\n \n Off Trail Learning - Dropping Out of College & the Silicon\n Valley Dream\n \n

\n\n

\n Twitter |{\" \"}\n Github |{\" \"}\n LinkedIn |\n {\" \"}\n RSS\n

\n \n ,\n ),\n {\n headers: {\n \"Content-Type\": \"text/html\",\n // TODO only when on main - \"Cache-Control\": \"public, max-age=3600, stale-while-revalidate=0\",\n },\n },\n );\n}",[],[226],"ee418e50-2abf-11f1-876b-42dde27851f2","helpers.tsx","019d3531-6d35-73dc-a4dd-2ce9d6f2d3f3",["D",1774713924926],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nconst linkClass = \"text-blue-500 hover:underline\";\nexport const Link = (\n { children, href }: {\n children?: React.ReactNode;\n href: string;\n },\n) => {children};",[],[233],"ee41886a-2abf-11f1-876b-42dde27851f2","analytics.ts","019d3531-6d35-73dc-a4dd-28e2e7aa2d59",["D",1774713924926],"import { sqlite } from \"https://esm.town/v/std/sqlite\";\n\nexport async function getHits() {\n const winner = await Promise.race([\n _getHits(),\n new Promise((resolve) => setTimeout(resolve, 1000)),\n ]);\n if (!winner) throw new Error(\"Took longer than 1 second to get hits\");\n return winner;\n}\n\nasync function _getHits() {\n const [, { rows: [[monthHits]] }, { rows: [[todayHits]] }] = await sqlite\n .batch([\n \"INSERT INTO stevekrouse_com_hits DEFAULT VALUES\",\n \"SELECT COUNT(*) FROM stevekrouse_com_hits where strftime('%m', timestamp) = strftime('%m', 'now') AND strftime('%Y', timestamp) = strftime('%Y', 'now')\",\n \"SELECT COUNT(*) from stevekrouse_com_hits where strftime('%m', timestamp) = strftime('%m', 'now') AND strftime('%Y', timestamp) = strftime('%Y', 'now') AND strftime('%d', timestamp) = strftime('%d', 'now')\",\n ]);\n return { monthHits, todayHits };\n}",[],[240],"ee417910-2abf-11f1-876b-42dde27851f2","README.md","019d3531-6d35-73dc-a4dd-27b53bcdc46f",["D",1774713924926],"# stevekrouse.com - my personal website\n\nThis project hosts my personal website.\n\nIt used to [live on Github Pages](https://github.com/stevekrouse/stevekrouse.github.io), which is why I proxy over requests to certain blog posts over to the Github Pages site still.\n\n## Architecture\n\n```mermaid\ngraph TD\n A[Incoming Request] --> B[\"main.tsx (Hono Router)\"]\n\n B -->|\"GET /\"| C[\"index.tsx → Homepage()\"]\n C --> D[\"analytics.ts → getHits()\"]\n D --> E[(SQLite DB)]\n C --> F[Server-side rendered HTML with React]\n\n B -->|\"GET /source\"| G[Redirect to Val Town source code]\n\n B -->|\"GET /*\"| H[\"post-helpers.tsx → renderPage()\"]\n\n H --> I{Match slug in posts/?}\n I -->|Yes .tsx| J[Dynamic import → run as handler]\n I -->|Yes .md| K[Parse Markdown with react-markdown]\n I -->|Yes .html| L[Serve raw HTML]\n J --> M[\"PostTemplate.tsx (layout wrapper)\"]\n K --> M\n I -->|No match| N[Proxy to GitHub Pages]\n N --> O{GitHub Pages 404?}\n O -->|No| P[Return GitHub Pages response]\n O -->|Yes| Q[Return 404 page]\n\n style B fill:#f97316,color:#fff\n style E fill:#3b82f6,color:#fff\n style M fill:#10b981,color:#fff\n```\n\n### Key Files\n\n| File | Role |\n|------|------|\n| `main.tsx` | HTTP entry point — Hono router handling `/`, `/source`, and `/*` |\n| `index.tsx` | Renders the homepage with projects, essays, podcasts, and analytics |\n| `analytics.ts` | Tracks page hits in SQLite; returns today & monthly counts |\n| `post-helpers.tsx` | Loads posts from `posts/` dir (.tsx, .md, .html), falls back to GitHub Pages |\n| `PostTemplate.tsx` | Shared blog post layout with OG tags, water.css, and nav header |\n| `helpers.tsx` | Shared `` component |\n| `posts/` | Blog posts in .tsx, .md, or .html format |\n\n## Todos \n\n- [ ] Speed up page load by loading sqlite data later like in @healeycodes/steve_web\n- [ ] Store more (legally storable) analytics data, and maybe make a sparkline!\n- [ ] Add some sort of way to contact me\n- [ ] Move over all my blog posts from Github Pages (maybe into @std/blob as a CMS?)",[],[247],"ee41569c-2abf-11f1-876b-42dde27851f2","PostTemplate.tsx","019d3531-6d35-73dc-a4dd-2118ab621bf4",["D",1774713924926],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\n\ninterface PostTemplateProps {\n title?: string;\n description?: string;\n ogImage?: string;\n children: React.ReactNode;\n}\n\n/**\n * Template for blog posts with:\n * - Good OG meta tags\n * - Favicon (SK in orange)\n * - Header with link back to homepage\n * - View source link at the top\n * - Water.css styling\n */\nexport function PostTemplate({\n title = \"Steve Krouse\",\n description,\n ogImage,\n children,\n}: PostTemplateProps) {\n // Generate favicon SVG (orange SK on white)\n const faviconSvg = `data:image/svg+xml,${\n encodeURIComponent(`\n \n `)\n }`;\n\n return (\n \n \n {title}\n \n \n \n \n\n {/* OpenGraph meta tags */}\n \n \n {description && (\n <>\n \n \n \n \n )}\n {ogImage && (\n <>\n \n \n \n \n )}\n \n\n {/* Highlight.js for syntax highlighting (light + dark themes) */}\n \n \n \n \n\n {/* Mermaid for diagrams */}\n \n\n \n

\n \n

\n\nThe morning I decided to do it, we first started with her normal word games. Then I announced that I made her a word game. She was excited. She enjoyed the Quordle, but was a bit confused why all the words were so random. The only one that had any significance was \"meter\", because it ended in \"er\", but even that significance was weak. Safe to say she had no clue what was coming. She got to the win screen and was ready for the next level. The letters fell away and she turned to me and said, \"What?\"\n\nThe rest happened in a blur, but I did get down on one knee and pull out a ring. She said yes.\n\n

\n\nYou can play [Emilrdle here](https://stevekrouse-emilrdle.web.val.run/). The next level is reserved for Emily.\n",[],[163,296],"ee4038ca-2abf-11f1-876b-42dde27851f2","precision.md","019d3531-6d35-73dc-a4dd-037d89496730",["D",1774713924926],"---\ntitle: Reports of code's death are greatly exaggerated\ntags: precision, abstraction, ai, coding\ndate: 2026-03-21\n---\n\n# Reports of code's death are greatly exaggerated\n\nMarch, 21 2026\n\n[A sufficiently detailed spec is code](https://haskellforall.com/2026/03/a-sufficiently-detailed-spec-is-code)\nbegins with this lovely comic:\n\n![image.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/f7e9e621-0fad-4c3a-a65b-d16832c02b00/public)\n\nThere is a profound tension here: english specifications _intuitively feel_\nprecise until you learn better from bitter experience. (It's all in that facial\nexpression of the last frame.)\n\n> \"Everything is vague to a degree you do not realize till you have tried to\n> make it precise.\"\n>\n> – Bertrand Russel\n\nProgramming, like writing, is an activity, where one iteratively sharpens what\nthey're doing as they do it. (You wouldn't believe how many drafts I've written\nof this essay.)\n\nAI helps you with this, because it – increasingly instantly and well – turns\nEnglish into running code. You can then react to it – \"move the button there;\nmake it bluer\" – to get incrementally more precise about what you want.\n\nThis is why \"vibe coding\" is such a perfect phraseology: you stay operating at\nthe level of your English-level vibes while reacting to the AI-created artifacts\nthat help you sharpen your thinking.\n\nBut, vibe coding gives the illusion that your vibes are precise abstractions.\nThey will feel this way right up until they\n[leak](https://www.joelonsoftware.com/2002/11/11/the-law-of-leaky-abstractions/),\nwhich will happen when you add enough features or get enough scale. Unexpected\nbehaviors (bugs) that\n[emerge from lower levels of abstraction](https://worrydream.com/LadderOfAbstraction/)\nthat you don't understand will sneak up on you and wreck your whole day.\n\nThis was Dan Shipper's experience when his\n[vibe-coded text-editor app went viral, and then went down](https://every.to/chain-of-thought/when-your-vibe-coded-app-goes-viral-and-then-goes-down).\nAs it turns out, \"live collaboration is just insanely hard.\"\n\n

\n\n\"Live collaboration\" _intuitively feels_ like a perfectly precise specification.\nWe've all used Google Docs, Notion, etc so it _feels_ precisely spec'd. It's\nincredibly hard a priori to see what this is not the case.\n\nThe only reason that I personally know otherwise is that I tried to add a\ncollaborative text editor to a product I was working on 10 years ago, and it was\nan unexpected nightmare of complexity.\n\nWhat was hard about it? I don't remember! That's part of the problem! Complexity\ncan be incredibly boring, unpleasant to think about, and hard to remember all\nthe details and edge cases. For example, the classic flowchart of how Slack\ndecides when to send you a notification:\n\n![image.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/4370b0ce-5657-4edc-9077-25751bbdd500/public)\n\nBut, this isn't the end of the story either. We are blessed with an extremely\npowerful tool to master complexity.\n\n## Abstraction\n\nThere is a fundamental limit in the human brain. We can only think of 7 (plus or\nminus 2) things at a time. So the **only way** to think about more than 7 things\nis to _compress_ multiple things into a single thing. Happily, we can do this\nrecursively, indefinitely, which is why humans can master unlimited complexity.\nThat compression step is called _abstraction_.\n\n> The purpose of abstraction is not to be vague, but to create a new semantic\n> level in which one can be absolutely precise.\n>\n> — Edsger Dijkstra\n\nFor example, Sophie Alpert used clever abstraction to\n[refactor the Slack diagram to this much simpler one](https://sophiebits.com/2024/10/30/everyone-is-wrong-about-that-slack-flowchart):\n\n

\n\nThis is the best part of programming: coming up with increasingly good\nabstractions to help us master complexities. My favorite examples of this are\nfunctional programming concepts, like functional reactive programming, which\n[I wrote a wonderful essay on](https://futureofcoding.github.io/futureofcoding.org/essays/dctp).\n\nSo yes, collaborative text editors are fundamentally complex, but that just\nmeans that we're continually in search of better abstractions to help us master\ncomplexities, like ReactJS or TailwindCSS did in their respective domains.\n\n## AGI\n\nBut let's play this out 1, 2, 5, 10, 100 years. AI is getting\nbetter/faster/cheaper at incredible rates, but regardless of _when_, unless you\nbelieve in magic, it's only a matter of time until we reach the point at which\nmachine intelligence is indistinguishable from human intelligence. We call that\npoint AGI.\n\nIt may seem like an AGI world is a vibe world. If anyone can afford 100\nKarpathy-level geniuses for $1000 / month, why ever trouble yourself with any\ntroublesome details? Just have your army of Karpathys handle them for you.\n\nThis is such a joke to me. This is _clearly_ only something you'd think in the\nabstract, before this technology arrived.\n\nIf you told me that I had access to that level of intelligence, there is zero\npart of me that is going to use it to ship _more_ slop. Are you freaking\nkidding?? Of course not.\n\nI think we're confused because we (incorrectly) think that code is only for the\nsoftware it produces. It's only partly about that. The code itself is also a\ncentrally important artifact. When done right, it's poetry. And I'm not just\nsaying this because I have Stockholmn Syndrome or a vested interest in it – like\na horse jockey might in the face of cars being invented.\n\nI think this is a lot clearer if you make an analogy to writing. Isn't it\nfucking telling that nobody is talking about \"vibe writing\"?\n\nWe're not confused with writing because there's nothing mystical about\nsyntactically correct sentences in the same way there is about running code.\nNobody is out there claiming that ChatGPT is putting the great novelists or\njournalists out of jobs. We all know that's nonsense.\n\nUntil we get AGI. Then, by definition, machines will write amazing non-slop and\nit'll be glorious.\n\nThe same exact situation is true for coding. AI produces (increasingly less)\nshitty code. We all know this. We all work around this limitation. We use AI\nin spite of the bad code.\n\nAs Simon Willison says,\n[AI should help us produce better code](https://simonwillison.net/guides/agentic-engineering-patterns/better-code/).\nAnd when we have AGI this will be easy.\n\nWhen we have AGI, the _very first_ things we will use it on will be our hardest\nabstraction problems. We will use it to help us make better abstractions so that\nwe can better understand and master complexity.\n\nYou might think the need for good code goes away as AIs get smarter, but that's\nlike using ChatGPT to write more slop. When we get AGI, we will use them to make\nbetter abstractions, better collaborative text editor libraries, etc.\n\nFor example, my favorite success story with Opus 4.6 was that it helped\nme with my dream full-stack react framework for Val Town. It one-shot solved\n[my list of unsolved problems](https://www.val.town/x/stevekrouse/reactRouter7Example/branch/main/version/164/code/react-router-questions.md)\nthat I had with getting React Router 7 to work full-stack in Val Town. The\nresult is my nascent [vtrr](https://www.val.town/x/stevekrouse/vtrr) framework.\nI'm particularly proud of this 50 line full-stack react app demo in\n[a single file](https://www.val.town/x/stevekrouse/vtrr/code/demos/hello-world.tsx):\n\n![Screenshot 2026-03-21 at 18.48.14@2x.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/448cbc3e-a196-4d2f-7f96-6b0dcf822200/public)\n\nIf you know of any other snippet of code that can master all that complexity as\nbeautifully, I'd love to see it.\n\n## Reports of code's death are greatly exaggerated\n\nIt seems like 99% of society has agreed that code is dead. Just yesterday I was\nlistening to podcaster Sam Harris of all people confidently talking about how everyone agrees\ncoding is dead, and that nobody should learn to code anymore.\n\nThis is so sad. It's the same as thinking storytelling is dead at the invention\nof the printing press. No you dummies, code is just getting started. AI is going\nto be such a boon for coding.\n\nI have so much more to say on this topic, but this essay is already 3x longer\nthan I wanted it to be. I'll stop here and leave you with some of my favorite\nquotes on formalism.\n\n> Instead of regarding the obligation to use formal symbols as a burden, we\n> should regard the convenience of using them as a privilege: thanks to them,\n> school children can learn to do what in earlier days only genius could\n> achieve.\n>\n> When all is said and told, the \"naturalness\" with which we use our native\n> tongues boils down to the ease with which we can use them for making\n> statements the nonsense of which is not obvious.\n>\n> – Edsger W.Dijkstra,\n> [On the foolishness of \"natural language programming\"](https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667.html)\n\n> There are two ways of constructing a software design: One way is to make it so\n> simple that there are obviously no deficiencies, and the other way is to make\n> it so complicated that there are no obvious deficiencies.\n>\n> –\n> [Tony Hoare](https://cs.stanford.edu/people/eroberts/courses/soco/projects/2008-09/tony-hoare/index.html),\n> [h/t Paul Buchheit](https://news.ycombinator.com/item?id=47325225)\n\n> The quantity of meaning compressed into a small space by algebraic signs, is\n> another circumstance that facilitates the reasonings we are accustomed to\n> carry on by their aid.\"\n>\n> – Charles Babbage, quoted in Iverson's Turing Award Lecture, quoted in\n> [Succinctness is Power by Paul Graham](https://paulgraham.com/power.html)",[],[163,303],["D",1774713924926],[],[163,68],"ee3fec58-2abf-11f1-876b-42dde27851f2","model.md","019d3531-6d35-73dc-a4dc-f973252d84ee",["D",1774713924926],"---\ntitle: Find a model\ntags: advice, creativity\ndate: 2025-03-24\n---\n\n# Find a model\n\n![a woman painting a landscape](https://stevekrouse-blob_admin.web.val.run/api/public/model.jpeg)\n*\"a woman painting a landscape\" by [Fal Demo App](https://www.val.town/v/stevekrouse/falDemoApp)*\n\nOne of the most common pieces of advice I give to mentees is to \"find a model.\" It's a stupid-simple technique, but can transform how you work. It will let you do things faster, better, and with more confidence. It's a mystery that everybody doesn't use it all the time.\n\nThe core of the technique is to find a model artifact to keep an eye on while you work on your artifact, which could be a coding project, a song, a painting, an email, a social media post, an essay like this one, etc.\n\nThe are three important benefits to this technique.\n\n## A north star\n\nA model gives you a north star; something to shoot to; something you can visually compare your work to, and see what's missing; a yardstick by which you can measure how \"done\" your artifact is. Without a model, how do you even know what kind of thing you're making? How can you tell its shape? A model is like a hyper-specific template that lets you stay focused on the end goal.\n\nThere are many related principles: [Backward Chaining](https://en.wikipedia.org/wiki/Backward_chaining), [Top-down design](https://en.wikipedia.org/wiki/Bottom-up_and_top-down_design), [The XY Problem](https://en.wikipedia.org/wiki/XY_problem), and Amazon's principle to \"Write the Press Release First\". These all get at the idea that you don't want to lose sight of the end goal. Without a model, you risk getting lost in the details. Losing the forest for the trees. A model helps you keep the whole forest in sight, so you actually create what you set out to.\n\nHowever, it's important to remember that \"Plans are useless, but planning is indispensable.\" In other words, you shouldn't feel compelled to stick to your model so closely. Use the parts that you want, and forget about the rest. A model is high up on [The Ladder of Abstraction](), but that doesn't mean you can't change it. If you realize that you chose the wrong model or that your goals have changed, excellent. Time to find a better model.\n\nThe fact that you have a model is what allows you to realize when you have the wrong model. Imagine you're a ship captain navigating by a star that you thought was the north star, but then later realized was just Venus. The time you wasted navigating by Venus would've been equally wasted if you were navigating without reference to any star. At least when you're navigating by Venus one of your fellow sailors can come over your shoulder and say, \"Hey captain, I think that's Venus.\" If you're navigating by nothing, then you're truly lost at sea.\n\n## Un-stuck-ing yourself\n\nAnother reason to have model is that it's very helpful when you get stuck. Don't know how to do something? See how your model does it.\n\nFor this essay I felt stuck on the first line. This essay's model is [Do things that don't scale](https://www.paulgraham.com/ds.html), because it's an essay that explains a cognitive technique. Its first sentence isn't the prettiest, but it gets the idea across and it's a hook: \"One of the most common types of advice we give at Y Combinator is to do things that don't scale.\"\n\nNow go back and read my first line. Is it deritive? Yes. Would literally anyone have noticed if I didn't draw your attention to it? No. There's something profoundly true about the line oft-attributed to Picasso, \"Good artists borrow. Great artists steal.\" I didn't truly believe this quote until I read [The Elements of Eloquence](https://en.wikipedia.org/wiki/The_Elements_of_Eloquence), wherein he shows examples of Shakespeare lifting whole sentences out of other books and plays, only changing a couple words.\n\nIn school, they call this behavior cheating, which is probably why this technique isn't practiced more often. I think it's an important lesson to unlearn. Why reinvent the wheel? Save time so you can focus on your unique contribution. Just be sure to give attribution and credit where it's due.\n\n## Maybe someone already did it, so you don't have to\n\nHow many times have you built something only later to realize someone else already built it? Chances are that if an idea occurs to you, likely it has occured to someone like you. So many people don't even take a second to google around before embarking on a project. Instead of wasting your time reinventing the wheel, see if someone already invented it. Then stop. Just use their thing.\n\n## How to find a model\n\nOne reason \"finding a model\" isn't more common is that it can be quite difficult to find a good model. I call that technique [\"surveying the space\"](./survey).\n",[],[163,313],"ee3fc5fc-2abf-11f1-876b-42dde27851f2","ir.md","019d3531-6d35-73dc-a4dc-f4dc7352cf93",["D",1774713924926],"---\ntitle: Personal Investor Relations\ntags: legibility, investor letters\ndate: 2026-03-03\n---\n\n# Personal Investor Relations\n\nFor most companies, investor relations and communication are unpleasant hygiene, like a dental cleaning, something to get through as fast and painlessly as possible, often delegated to automations, ops, finance, or IR. The way some founders do it, it's a beautiful art form all unto itself: clear, plain-spoken prose, minimal corporate-ese doublespeak, humor, often self-deprecating, lessons learned, and plans for the future.\n\nI am thinking first and foremost of [Warren Buffett](https://www.berkshirehathaway.com/letters/letters.html), but this would also include [Jeff Bezos & Amazon](https://www.aboutamazon.com/about-us/shareholder-letters). For example:\n\n> “Mistakes — yes, we make them at Berkshire… Don’t beat yourself up over past mistakes — learn at least a little from them and move on.”\n> — [Warren Buffett](https://www.berkshirehathaway.com/letters/letters.html)\n\n> “I believe we are the best place in the world to fail (we have plenty of practice!), and failure and invention are inseparable twins.”\n> — [Jeff Bezos](https://www.aboutamazon.com/news/company-news/amazons-original-1997-letter-to-shareholders)\n\nMore recently, I've discovered that [Patrick and Jon of Stripe](https://stripe.com/annual-updates/2025) and [Immad of Mercury](https://mercury.com/blog/annual-letter-2025) also publish lovely letters. What they share is a willingness to explain how they think, what they got wrong, and what they plan to do next, in their own voices.\n\nTo me, these kinds of investor letters fit into the broader legible universe that includes [Date Me Docs](https://dateme.directory/) (which I am proudly the world's leading advocate for), beautifully written job postings, and founder-written blogs, like [Paul Graham's](https://www.paulgraham.com/). In all of these, the common thread is creators speaking plainly and directly to the world.\n\nThe are big benefits to taking investor relations and communications seriously. First, it helps you build trust:\n\n1. **Build trust with capital markets.** Over time, they learn how you think, act, and allocate capital. That earns you a longer leash to make long-term investments, more grace when you have missteps, and often higher multiples than competitors who stay opaque. Something that surprises many people is that public markets actually include plenty of extremely long-term oriented investors. Buffett talks about this a lot, and I have many investor friends who think the same way.\n\n2. **Build trust with labor markets.** Employees, who are always implicit underwriters of a business and often shareholders themselves, see that you are trustworthy stewards of their careers, livelihoods, and reputations.\n\n3. **Build trust with customers.** They can see more behind the curtain how you are trying to serve them, not trick or exploit them.\n\n4. **Build trust with the public.** You explain why your company exists, what purpose it serves, and how you try to be a good community member. In this anti-business and anti-billionaire climate, some scorn is earned, but some of it comes from a lack of transparency that leads people to assume the worst. I’ve never heard anyone say anything bad about Warren Buffett, and there’s some public relations genius there worth studying.\n\nThere are also a couple benefits that don’t quite fit under “trust,” but matter just as much:\n\n1. **Attract the partners you want and repel the ones you don’t.** Buffett talks a lot about the importance of aligned partners for the long term. The last thing I want is an investor looking to make a quick buck or take the company in a different direction, or a customer or employee who wants us to be something we don’t want to be.\n\n2. **Better internal decision making and alignment.** Spending time on investor communications makes oneself and one’s company more legible internally. (Sometimes I joke that the Date Me Directory is a dating app whose best feature is that it \"tricks\" people to be more thoughtful about who they are and who they want to be in a relationship with. Internal legibility, aka clarity, is worth the all by itself.)\n\nBut from an efficiency perspective, publishing thoughtful investor letters is a worthwhile use of time simply because you should be doing this reflective thinking anyway. And if you are going to spend the time reflecting, you might as well publish it and kill many birds with one stone: clarity for yourself, and legibility to everyone else. Often the only thing stopping you is a vague fear or making things more public than you need to. In my calculations, the benefits way exceed the costs for me, especially for the long-term, positive-sum games I intend to play for my career. Increased public legiblity helps others fit you into their stories where appropriate, increasing your “[luck surface area](https://www.codusoperandi.com/posts/increasing-your-luck-surface-area).”\n\nThis is why I plan to start publishing Val Town's Monthly Investor Updates. My very next Val Town investor update, which I’m writing now, is intended to be public, so hopefully within a few days folks can read it.",[],[163,320],"ee3f62c4-2abf-11f1-876b-42dde27851f2","intelligence.md","019d3531-6d35-73dc-a4dc-f2a14f06bf6c",["D",1774713924926],"---\ntitle: Intelligence Buying Intelligence\ntags: ai, startups, philosophy\ndate: 2026-02-01\n---\n\n# Intelligence Buying Intelligence\n\n[Nnamdi Iregbulem recently wrote](https://whoisnnamdi.substack.com/p/tokens-arent-fungible)\nabout how users stick with expensive and slow closed models (ie Opus 4.6)\ndespite cheaper OSS alternatives.\n\nWhy aren't we using cheaper models?\n\nSonnet 4.6 is right there, faster, almost 2x cheaper, and about as good as Opus\n4.5, which we were all obsessed with five minutes ago – not to mention OSS\nmodels which are 10x cheaper. It's crazy that I'm always reaching for the\nslowest and most expensive model!\n\nFor me, there's extra cognitive dissonance, because not only do I care (like\neveryone else) about saving money, but I care especially about being in a flow\nstate. Waiting longer for a maybe-smarter response is the opposite of that. Back\nwhen Sonnet 3.5 was the best model, I couldn't wait to get my hands on something\nas smart as it but 10x faster and cheaper. Now we have that. Yet I never reach\nfor it.\n\nNow, I daydream of Opus 4.6 at Taalas's 17k tokens-per-second (Opus 4.6 is ~70\ntps, so 250x slower), yet I'm realizing that by the time we get there – say in a\nyear or two – will we even want to use it vs Opus 6.6?\n\nHere's my best explanation for why we keep reaching for the most expensive and\nslow models, even when cheaper and faster ones are available. There are four\nforces at play that make intelligence a weird thing to buy:\n\n1. The returns to intelligence are **nonlinear**\n2. Intelligence is **hard to measure**.\n3. Intelligence is **competitive**.\n4. Intelligence is a **commodity**. (You can always turn incremental capital into incremental intelligence.)\n\n## 1. The returns to intelligence are nonlinear\n\nThere's a new question tripping up most LLMs right now. It's the new \"how many\nr's in strawberry\":\n\n> The car wash is 50 meters away. Do you walk or drive?\n\nSonnet 4.6 and ChatGPT 5.2 tell you to walk.\n\nOpus 4.6 is the only model I know of that correctly tells you to drive (\"because\nyou'll need the car\"). Once you've seen a model make a mistake like that, it's\nreally hard to look it in the eyes and trust it with anything important.\n\nThis is because we know deep down that returns to intelligence are spiky and\ndiscontinuous. A tiny increase in intelligence can unlock a perspective that\nsimply doesn't exist at the level below it. The losses from insufficient\nintelligence are basically unbounded: someone who is fundamentally confused in\none seemingly small way can end up in the catastrophically wrong place. And the\nconverse is true too. Intelligence builds on itself. One correct insight early\non compounds into a totally different trajectory.\n\nConsider Warren Buffett as the poster child for this. He has a few key insights\nthat are basically invisible to most people, but those insights compound into a\ncompletely different trajectory. The difference between Buffett and the average\ninvestor may be a 0.001% difference in intelligence, but that can lead to\nmassively different outcomes.\n\nIntelligence isn't about exerting more effort. It's about seeing what's right in\nfront of you more clearly: finding the shortcut, the hidden door, the structural\nsimplification that was invisible a moment ago.\n\nIt's also about course-correcting as fast as possible when you realize you're on\nthe wrong path. Feedback loops dominate. Learning compounds.\n\nIntelligence might actually be unique in its nonlinearity. In a\n[David Deutsch](https://en.wikipedia.org/wiki/David_Deutsch) sense, it's the\nonly process that creates new explanatory knowledge, the creation of which is\ninherently unpredictable.\n\n## 2. Intelligence is hard to measure\n\nAnd here's what makes this extra tricky: we don't have good evals.\n\nThis is true for human evals too: SATs only goes up to 1600. If you have a room\nfull of 1600s, you'd have future Nobel laureates sitting next to future\ndeadbeats. And many Nobel laureates and future self-made billionaires and\ngeneration-defining-artists don't even get 1600s! Our tests literally don't\nmeasure the intelligence that matters most.\n\nLLMs keep exceeding our benchmarks, so we keep making harder ones. We're finally\ntaking teaching intelligence and measuring it seriously. I wish we were\nsimilarly ambitious about human intelligence: \"Oh damn, 40% of kids are getting\n1600s these days, gotta make SATs harder.\"\n\nWithout great evals, we default to vibes, reputation, brand loyalty, and price\nsignals. Which, honestly, is rational when you can't measure what matters.\n\nThe best eval I heard about recently is\n[Demis Hassabis's \"Einstein test\"](https://x.com/rohanpaul_ai/status/2025274123560362347):\ntrain an LLM on all human knowledge up to 1911, then see if it can independently\ndiscover general relativity. We need more evals like that.\n\n## 3. Intelligence is competitive\n\nThere's a third reason to always reach for the most expensive intelligence: in\nmany domains, intelligence is a race.\n\nI used to think that once we get models as smart as my CTO, Tom MacWright, we\ncan basically stop there and then work on compressing that intelligence down to\n8b parameters and making it faster and cheaper. Give me a country of Tom's in a\ndatacenter.\n\nBut in some domains, even if a model (or model + harness) is 0.001% smarter,\nthat could be the difference between winning and losing. In a competitive\ndomain, you don't just need to be good enough. You need to be better than\neveryone else.\n\nMy dad likes to tell the story of two hikers who see a bear. One hiker starts\nrunning, and the other says \"you can't outrun a bear!\" The first hiker says:\n\n> \"I don't have to outrun the bear, I just have to outrun you.\"\n\nIf someone could give you a consistent edge in the stock market, even a small\none, that edge could be worth a trillion dollars. But only if nobody else has\nit. The moment everyone has the same insight, it's priced-in and worthless. For\nthe stock market, you don't just need intelligence – you need _more_\nintelligence than everyone else.\n\nI'm not sure to what extent this is true in startups – classic YC advice is to\nignore competition. But in the attention economy, you definitely need to be\nbetter than everyone else. If your content is 0.01% better than the next best\nthing, that could be the difference between going viral and being ignored.\n\n## 4. You can always spend incremental dollars to get incremental intelligence\n\nRight now the most expensive models aren't actually that expensive. A few bucks\nper conversation. But that's changing fast.\n\nWe keep finding ways to spend more money for more intelligence: longer chains of\nthought, parallel reasoning, models that loop and self-correct for hours instead\nof seconds. Each of these multiplies the compute bill – on purpose.\n\nThere's a great example of this called the\n[Ralph Wiggum loop](https://ghuntley.com/ralph/), coined by Geoffrey Huntley.\nThe idea is simple: keep running an AI agent in a loop, feeding failures back\nin, until it succeeds. You're literally turning compute dollars into results\nthrough brute-force persistence. It's not elegant, but it works – and it means\nthat if the stakes are high enough, you can always throw more money at a\nproblem.\n\nWe're not just going to make intelligence cheaper. We're going to make it _more\nexpensive on purpose_ – because we'll keep finding ways to spend more compute on\nharder problems. The ceiling on what you can pay for intelligence is going to go\nway up. And if the returns are nonlinear, people will pay it. Gladly.\n\n## Nobody ever went bankrupt spending too much on good counsel\n\nA very-well-paid consiglieri once told me:\n\n> Nobody ever went bankrupt spending too much on good counsel, but plenty did\n> trying to save on it.\n\nWhy are lawyers so expensive? Why doesn't competition drive down the price?\n\nBecause all four forces are at play.\n\n1. The returns are **nonlinear**: you're paying for the one sentence that changes\n the contract, the one clause that closes a loophole. \n \n2. It's **hard to measure** the quality of legal counsel until you end up in\n court, and by then it's too late. So you rely on vibes, reputation, and price\n signals.\n\n3. It's directly **competitive** – you need counsel at least as good as the other\n side's.\n\n4. Legal intelligence is a **commodity** – you can always throw more at the problem:\n more associates, more partners, outside specialists. There's basically no ceiling.\n\nPut another way: you're not paying for the hours. You're paying for the\npossibility of unlocking a secret.\n\nOnce you have this perspective, you realize that law firms already run a _model\nrouter_ internally. When you email your law firm, they route your request to the\nbest-priced and fastest (ie someone with available capacity) intelligence for\nyour problem. Simple incorporation? Junior associate. Routine contract review?\nMid-level. Bet-the-company litigation? Senior partner.\n\n## The flippening\n\nWhen a new tool is weaker than you, you use it like a full-time employee. You\ngive it bounded tasks. You double-check its work. You keep the real decisions\nfor yourself. That's how we use LLMs today, and it works great.\n\nBut this only makes sense in a world where intelligence is both cheaper and\nworse than yours. And that world is temporary.\n\nNow imagine models + harnesses that are smarter than you. Not just faster, not\njust more encyclopedic, but actually better at reasoning, better at synthesis,\nbetter at seeing structure.\n\nAs discussed above, they've also become more expensive and slower than you. You\nwon't treat them like interns anymore. You have to treat them like partners. You\nhave to give them only the hardest problems, the ones that actually require\nintelligence, and let them do their thing.\n\nI've been thinking about this as **the Lawyer Flippening**.\n\nRight now most people use AI like middle managers. Tools like\n[Devin](https://devin.ai/) spin up sub-agents in parallel.\n[Gastown](https://block.github.io/goose/blog/2026/02/19/gastown-explained-goosetown/)\norchestrates 20-30 Claude Code instances on the same codebase. You assign\ntickets, let them grind, check their work, assign more tickets.\n\nBut the future looks different. The frontier model will be the most expensive\n\"employee\" in the room, even more expensive and slower than you, the human. This\nsuper expensive model will be sitting at the top of the pyramid, with a swarm of\ncheaper agents – and humans – beneath it.\n\nThis is kinda how companies already work. The CEO isn't even the top. The CEO is\njust the highest-paid full-time employee. Above them are all the sources of\nintelligence you can't afford at full-time rates, but that are still crucial:\nconsultants, advisors, board members, investors.\n\nAs the CEO of Val Town, a small startup, I try to push work towards the\nintelligence that can do it most efficiently (and honestly, joyfully, because\nthese are humans, not clankers), either on my team or of our advisors, lawyers,\ninvestors, etc.\n\nStructurally, this will be true as LLM intelligence gets better. We'll all want\npartner-level intelligence, but because it's so expensive, we'll have to route\nwork to it strategically. The model router will be more important than ever.\n\n## The LLM that pays for its own inference: how much should you spend on intelligence?\n\nHere's a thought experiment I can't stop turning over. Imagine giving an LLM a\n$100k bank account. Its only job: earn enough to pay for its own\ninference and generate a return. It's basically a hedge fund of one. And\nsuddenly it's facing the exact optimization problem we all face: how much of\nyour capital do you burn on intelligence vs. keep as returns?\n\nHedge funds charge \"2 and 20\" – 2% management fee, 20% of profits. Should our\nLLM hedge fund do the same? Allocating 2% of its capital under management to its\nown inference? But is that actually optimal, or just convention?\n\nWhat is the optimal ratio of sharpening the axe to chopping wood? How much\nshould you spend on thinking vs. doing?\n\nThe returns to intelligence are so nonlinear that investing in meta-work –\nbetter tools, better systems, better agent harnesses – can feel incredibly\njustified. And sometimes it _is_ justified. But if you take it too seriously,\nyou enter a cognitive black hole where you spend all your time becoming smarter\nfor an application stage that never comes. It's yak-shaving all the way down.\n\nOur self-supporting LLM _can't_\nyak-shave forever, because its inference costs are real and its returns are\nmeasurable. Every hour it spends upgrading itself is an hour it's not earning.\nThat pricing mechanism – having to internalize the cost of your own intelligence\nand improving that intelligence vs the opportunity cost of earning more money\nwith our current intelligence – is exactly what's missing when a human\ndisappears into tool configuration for weeks. Nobody is billing you for your own\nthinking time, so there's no natural brake.\n\nBut sometimes sharpening the axe _is_ the point. Douglas\nEngelbart spent his entire career on this. He called it \"bootstrapping\": using\nyour current tools to build better tools, which you then use to build even\nbetter tools. It's the original intelligence-buying-intelligence loop that\nkicked off the information age. The highest-leverage use of intelligence is\nbuilding tools that make intelligence more effective.\n\nThis is what I've spent my career on. Like Notion, Val Town is a tool for making tools. The whole \"tools for thought\" tradition is\nreally just the tradition of intelligence investing in itself at the societal\nlevel. (Not every company in the world could or should be in the tools for\nthought space, but _some_ meaningful percentage should!)\n\nHere's the fun part: watch what this self-supporting LLM would independently re-invent.\n\nIt would want more money under management to amortize the fixed costs of its own\nthinking, so it reinvents fundraising so it can manage other people's money too\n(collect more management fees).\n\nIt has to decide what insights to share vs. gate-keep – it reinvents marketing vs proprietary\nresearch.\n\nIt might want to recruit other LLMs or humans for specialized tasks – it\nreinvents the firm.\n\nIntelligence generates capital. Capital buys more intelligence. More\nintelligence generates more capital. The loop compounds.\n\nThis is the big loop that Anthropic and OpenAI and all frontier labs are running\nright now: use capital to build intelligence, use the resulting\ncapital and intellgience to buy more compute, build even more intelligence.\n\nSam Altman has said that intelligence and energy are the two assets that matter,\nand really intelligence is primary because intelligence is what gets you more\nenergy. In this system, capital is just a proxy for energy. The more capital you\nhave, the more energy you can buy, and the more intelligence you can build. The\nintelligence-capital loop is the fundamental economic engine of our time.\n\nI love that with this single constraint – the LLMs gotta eat – you can see how\nall institutions we've already built (hedge funds, law firms, startups, venture\ncapital) are just different shapes this loop naturally takes.",[],[163,327],"ee3f3af6-2abf-11f1-876b-42dde27851f2","eval.md","019d3531-6d35-73dc-a4dc-ec9ca23fec5a",["D",1774713924926],"---\ntitle: steve-eval – getting AI to write like me\ntags: writing, ai, evals\ndate: 2026-03-22\n---\n\n# Steve Eval – getting AI to write like me\n\nMarch, 22 2026\n\nI wanted to see if I could get LLMs to write non-slop in my voice that I'd enjoy\nreading, and maybe even put my name on (only if it was good enough).\n\n## Creating the rubric\n\nI build this with Codex in a Ralph Wiggum loop:\n\n1. Pull a blogs I've written and a couple I haven't\n2. Make a rubric that would uniquely identify my writing\n3. Score the posts\n4. Based on the scores, update the rubric to be more accurate\n5. Repeat until the rubric scores all of my posts at > 90 and everyone else at <\n 90\n\nThe output after about 5 hours and some manual input from me:\n[EVAL.md](https://www.val.town/x/stevekrouse/steve-eval/code/EVAL.md).\n\n### My n-dash watermark\n\nThe best part of this process was when I came back after a while and the rubric\nhad gotten nerfed. It removed this rule that I had added manually:\n\n> Instant fail — Em-dashes or touching dashes (-14)\n>\n> Em-dashes (—) or n-dashes without spaces on both sides in the author's own\n> prose. Steve ONLY uses spaced n-dashes: `word – aside – word`. Any other dash\n> style is not Steve. Dashes in direct quotations or poem attributions are\n> excluded.\n\nIf you think about it, this rule kinda represents a watermark for my writing. Up\nuntil recently, I didn't realize that I was typing n-dashes instead of m-dashes!\nI don't even know how to type an m-dash and now I don't want to know. If you\never see writing with an m-dash or with the dashes touching the works on either\nside of it – unlike this – then you know it definitively wasn't me.\n\nBut after a couple hours of my Ralph Wiggum loop, this rule had disappeared! I\nasked the AI why and it linked me to this passage that I had supposedly written:\n\n> This tool—and others like it—are stops on our way toward end-programmer\n> programming.\n>\n> [Catching Stars, Val Town Blog](https://blog.val.town/catching-stars)\n\nI laughed out loud. That post was ghost-written for me by our new team member\n[Pete Millspaugh](https://www.petemillspaugh.com/)! The Steve Eval was correctly\nidentifying text not written by me!\n\nEven before this result, we had stopped the ghost-writing practice. I'm not a\nfan. I much prefer when the byline is accurate, and posts are written by the\npeople who say they wrote them. We had only done it that time out of a mistaken\nfeeling that people would prefer to hear from me, the founder. But that only\nworks if we're doing it authentically, so it didn't make sense. I just updated\nthe author on that post to Pete, because after all, he wrote it!\n\n## Writing new posts\n\nTo write a new post, I would vomit out all my thoughts about a new blog by voice\nand then give AI that transcript. Then I'd tell it to do the following in\nanother Ralph Wiggum loop:\n\n1. Write a draft blog post\n2. Score it with the steve-eval\n3. Based on the feedback, create a new draft\n4. Repeat until the score is > 90.\n\nI wrote two blogs with this approach, in part:\n\n- [Intelligence Buying Intelligence](https://stevekrouse.com/intelligence)\n- [What if you never had to get an API key ever again?](https://stevekrouse.com/x402)\n\nThe AI-produced results weren't great, so I spent a lot of time editing and in\nmany cases rewriting whole sections by hand. I think those posts are pretty\ndecent in spite of the help I got from AI.\n\n## Conclusion\n\nThis was a fun exercise, but mostly not very helpful for me yet. I'm excited for\nwhen AI is good enough to be able to do this well.\n\nBut it is fun to learn that I have a fairly unique watermark – long live my\nen-dash clauses with spaces around it! – and to get a bit clearer about what I\nthink good writing in my voice looks like.\n\n## Further reading\n\nThe folks at Every are thinking in this direction:\n\n- [AI Style Guides: How to Help AI Write Like You](https://every.to/guides/ai-style-guide)\n- [How to Build an AI Style Guide](https://every.to/guides/how-to-build-an-ai-style-guide)\n\nA list of AI writing tropes:\n\n- [tropes.fyi](https://tropes.fyi/)",[],[163,334],"ee3f320e-2abf-11f1-876b-42dde27851f2","ask.md","019d3531-6d35-73dc-a4dc-ea3e05ba83cf",["D",1774713924926],"---\ntitle: Great examples of people asking for what they want\ntags: legibility, ask-vs-guess-culture, date-me-docs, hire-me\n---\n\nThis is a collection of excellent job postings or resumes, people pouring their\nheart-and-soul into a post that explains who they are, who they're looking for,\nand how you might fit into their story.\n\n# Work for me\n\n### Janie Leger looking for an Au Pair\n\n![Screenshot 2026-03-22 at 11.25.47@2x.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/9922b1f7-e895-4671-4caf-a2a922f7e100/public)\n\n[Tweet](https://x.com/JanineLeger/status/2035457636527734857?s=20) –\n[Description](https://docs.google.com/document/d/1UdIEdh9ULIrx4x0KaZvIfFfM1OlySmltYI7ahEjyoUQ/edit?tab=t.0)\n–\n[Application](https://docs.google.com/forms/d/e/1FAIpQLSebJhm0K_kTkvDoKorFkyCwAmYZU4qQyYPlC9tdW800scQ0DA/viewform)\n\n# Hire Me\n\n# Date Me\n\nThe whole date me directory, obviously, and some in particular and fantastic\nexamples:\n\nhttps://x.com/stevekrouse/status/2036836965312528830?s=20",[],[163,341],"ee3ee4d4-2abf-11f1-876b-42dde27851f2","advice.md","019d3531-6d35-73dc-a4dc-e5bf85cca2f4",["D",1774713924926],"---\ntitle: Advice to college students in 2026\ntags: advice, education, startups, legibility\ndate: 2026-01-01\n---\n\n# Advice to college students in 2026\n\nOn Friday, a group of students will be visiting by my office as part of \"Penn\nTech Trek\", a program where Penn students visit tech companies. I went on two\namazing Tech Treks, one in NY and one in SF, so I am really excited to get to\npay it forward for the next generation.\n\nSo I sat down and thought about:\n\n- What I wish someone would've told me when I was in college\n- What I learned since I graduated\n- What advice I'd give to a college graduate in 2026\n\n### AI\n\nI feel like in 2026 you have to start with AI. It's just in the air, so much\nexcitement and fear. What jobs will be left? It's a wild time to be joining the\nworkforce!\n\nI've been thinking a lot about workout classes. For most of human history,\nworking out was a part of life, farming, cleaning, etc. But then we automated\n99% of physical labor, which is why it seems like there's a gym or yoga studio\non every block. If you told a farmer in the year 1800 that 99% of people\nwouldn't farm in the future, he'd be very confused. What are these muscles for?\nWhat jobs will there be?\n\nThe same may be true for us. Maybe brains won't be required for work. Maybe\nwe're about to automate thinking.\n\nWhat's left? The human touch. Take solace in the fact that we don't watch robots\nplay basketball or chess, or make art.\n\nAlso: if there's no job for you because a robot can do anything you can do\nbetter, then that also _necessarily_ means there's _incredible_ abundance in\nsociety. Maybe we all become like trust-fund kids looking to make life\nmeaningful. There's always teaching or art.\n\nBut most importantly, I want to share a lesson about bubbles. A very smart\nfriend called me frantically about how they feel like they need to quit their\njob and join a company to get in while it's good, because this is a\nonce-in-a-lifetime new industry being born. I told her she should take a deep\nbreath. Hype cycles come and go. It's hard to have historical perspective on\nyour first one. She didn't believe me. But that wasn't even AI! That was crypto.\nThat's how all-consuming bubbles are. I know this one feels different, but\nthat's how they all feel. So we should all take a deep breath.\n\n## Legibility\n\nLegibility means giving the world affordances for how they can interact with you\nand fit you into their lives – for jobs, romance (have you heard of\n[Date Me Docs](https://dateme.directory/)?), friends, collaborators, vendors,\netc. You can think of it as your \"interface\", like your own personal API. Or as\nHenrik says,\n\"[A blog post is a very long and complex search query to find fascinating people and make them route interesting stuff to your inbox](https://www.henrikkarlsson.xyz/p/search-query)\".\n\nBy default, you're invisible to the world. At the other end of the spectrum are\ntruly famous people. I'm talking about this secret third thing where you put a\nlot of stuff about yourself and what you're interested in, working on, thinking\nabout, etc, online so that you are a visible person.\n\nWhen I started the Future of Coding podcast & community and blogged super\npublicly, I thought about creating a lighthouse to attract my people and\ncollaborators. I walked into an empty room and started talking at the walls and\nyou'll never guess what happened next. People came into the room! And they're\nstill there! (Even though I left!)\n\nLegibility is how I found some of my best friends, investors, employees and\nsolutions to my problems. Unfortunately Twitter is not what it was, but find a\nplace where you can post online – a link is all that matters – and do as much of\nit as you can. Quantity over quality, excluding slop, of course.\n\nA well-phrased problem is a problem half solved. In framing it, you sometimes\nsolve it. Now that it's written down you can email it to friends, tweet it, ask\nAI. I had incredible back pain and was complaining about it to a friend who had\na super kooky solution that worked out.\n\nHowever, don't let illegibility stop you from doing things, especially in the\nearliest days. When I started my independent researcher / podcaster phase,\neveryone in my life thought I was crazy, and it was hard to explain to folks\nwhat I was doing. I just kept talking about it online in whatever way I could,\nand it got more legible over time. Henrik does a great job explaining the\nimportance of illegibility in\n[Looking for Alice](https://www.henrikkarlsson.xyz/p/looking-for-alice).\n\n## People\n\nLikely, the best work you'll ever do will be with people. Either you choose\nthem, or they'll be chosen for you. (Either you'll hire them or you'll join a\nteam.) Take this incredibly seriously. Your job is to cultivate your\nrelationships and future coworkers, employers, and employees.\n\nTreating people super well is such an amazing hack, and it's easy to justify all\nthe way up and down the value chain.\n\nFigure out (and continually refine) what your values are so you can spot when\nyour partners don't share them and end things earlier, saving yourself\nheartache. For example, I value reading, writing, honesty, integrity, kindness,\nself-awareness, legibility, nerdiness, personal projects.\n\n## Reading\n\nReading is important.\n\nMy strategy is to stop reading or listening whenever I'm bored. Don't let the\nwrong book stop you from reading the right one. Boring books will become\ninteresting when the timing is right. I mostly do audiobooks. It's important to\nplay with speed to keep you engaged. Fiction counts.\n\nThe solutions to a lot of your problems exist, and someone took the time to\nwrite them down. Don't be stupid - read the solutions. For example, if you want\nto start a startup and you don't read The Lean Startup, The Mom Test, Paul\nGraham's essays, and watch the Startup School videos, you're playing guitar\nhero, not guitar.\n\n## Goals\n\nGoals are tricky, because the stupidest and least informed version of yourself\nis the one setting them for smarter future versions of you. Still, containers\nand targets are powerful.\n\nI think it's super useful to point yourself at concrete examples. This is the\npoint of role models and heroes. The same is true in startups. A startup pitch\nis a lot about which company you want to be like. For example, Val Town wants to\nbe like Vercel or GitHub or Cloudflare. This is also relevant in selling and\npositioning.\n\nSeek out role models and role model companies, and as you \"meet your heroes\"\nfind increasingly better role models. Nobody is perfect.\n\n## Random startup tips\n\nFocus is your biggest weapon. Jealousy is the guard. Do fewer things better. The\nrewards to scale make this exponentially true.\n\nStay until your cliff date if there's a good chance the company will make good.\n\nDon't try to save money on corporate lawyers. Just use Nick Harley (or someone\nelse strongly recommended) and don't worry about it.\n\nVCs are pretty good at recommending startups. Once you realize you need to\nunderwrite the startup you join as if you were a VC, you can kinda outsource it\nto VC firms. But it's even better if you can talk to the VC who's on the board,\nnot just read press clippings.\n\nVCs and other wise folks have so much wisdom, but also so much anti-wisdom.\nThey're often biased by what worked for them at a specific moment in time, ie\nthey convinced me in 2013-2019 that devtools was not an investable category.\nJoke's on them!\n\nPre-seed investing is mostly about people. Ignore the market and product, except\nas signals about the people. Only invest in people you've known for years and\ntrust implicitly. That way you can underwrite their trajectory, judgment, taste,\nand integrity. If they have those, they'll fix any bad product or market faster\nthan you ever could. As PG says, a startup idea must seem like a bad idea in\norder to succeed, so don't judge ideas, judge people.\n\nA really great path to starting a startup is to get a job somewhere cool and\nlearn all their problems. It's really hard to get jazzed about solving a B2B\nenterprise's problem. It's really easy to get jazzed about your own problems. So\njoin a B2B enterprise and get yourself some valuable problems.\n\nOnce you work at a company, you can often find the role you want by navigating\nthe company. It's easier to walk in the easy door, and then work your way over\nthan to try to get the job you want when you don't know anyone there.\n\nIt's really hard to apply for jobs without knowing what it's like to be on the\nother side, reviewing candidates and hiring. VC is the same. It's awesome to be\non both sides, the \"buy side\" and the \"sell side\". It makes things less mystical\nand makes you more empowered. College admissions teaches the wrong lessons. Life\nis a lot more hackable and personal.\n\nIf you want to work somewhere, make it your mission and target them relentlessly\n– respectfully, without being a stalker. Nobody goes for the love offensive, but\nit's the best. I know a bunch of stories about super successful people walking\nin the side-door to their dream job by simply being persistent, resourceful, and\nshameless.\n\nWorking at a VC firm early in your career is a great way to kickstart things.\nIt's like you're sitting at the top of a hill, getting to look out over the\nwhole industry. I recommend First Round Capital. Thrive also seems hot right\nnow. Probably others are good too.\n\n## Emotional tips\n\nIf you have a bad habit you can't quit, don't shame yourself. Get curious.\nThere's probably a good reason it exists. Escapism. Learning leadership.\nSomething else.\n\nThe Landmark Forum is a three-day motivational course that I recommend with\ncaveats. It was key to starting my first company. Yet it's also a bit cult-y in\nhow they try to get you to sell their course for them. Still, I'd recommend it\nheartily if you find yourself stuck.\n\nIf you're upset about someone else and pointing a finger, you're probably upset\nabout something in yourself that you're not acknowledging yet and need some\nself-soothing. Any time you're upset, it's usually not about them. It's about an\nemotional need in yourself you have to meet. Non-Violent Communication is a\ngreat book. I made [this mobile-friendly worksheet](/nvc) I use every 6 weeks or\nso during emotional conversations.\n\n## Seek out mentors\n\nEmail me with questions. I love giving advice. Most people do.\n\nAsk for money or a job or intros, get advice.\n\nAsk for advice, get money or a job or intros.\n\nI'm steve@val.town.",[],[163,348],"ee3e6c70-2abf-11f1-876b-42dde27851f2","abstraction.md","019d3531-6d35-73dc-a4dc-e0cc51a39fe3",["D",1774713924926],"---\ntitle: Delegation & management is what you do when you lack proper tools & abstractions\ntags: ai, programming, philosophy\ndate: 2025-03-01\n---\n\n# Delegation & management is what you do when you lack proper tools & abstractions\n\nIn other words, AI Agents are NOT the future of software development.\n\nBut it's no surprise everyone is confused.\n\n## New media mimics old media\n\nNew media always initially resembles old media. Early television resembled film and radio. Early web pages looked like newspapers. \n\nIt took decades for tv, movies, tiktok, and algorithmic feeds to emerge. And to move from banner ads to google ads.\n\nAI is the same. Our closest analogue is the software engineering employee, so of course we're delegating to it. And to scale up, we think we need to scale up our employees, and all the sudden, we are managers.\n\nBut management sucks. We should all want to be superpowerful craftspeople (think Iron Man), not managers of armies of minions.\n\nIf you're thinking about managing your swarm of 20 AI agents, stop! You've gone too far! This is the equivalent of wondering how in 1910 you'll hitch 20 horses to a wagon to achieve 60mph speeds. You're in the wrong paradigm entirely.\n\nOr like thinking that the way to replace a room full of human accountants is a swarm of digital accountants. No! It's a spreadsheet and a single human. The fact that calculations are happening under the hood is transparent to the user.\n\n## Agents are an implementation detail\n\nAI Agents are an incredible *implementation detail*. You can dramatically increase the effectiveness of AI, when you put it in a feedback loop with its environment. This is undeniable.\n\nThis does NOT mean that we humans have to INTERFACE with agents. Back to a car analogy: whether it's an internal combustion engine or an electric motor, the interface to a car is the same steering wheel and pedals. Nobody has to MANAGE the firing of the pistons.\n\nThe same should be true for human programmers. We should not tie ourselves to the interface of delegating to agents.\n\nWhy? Because delegation & management are the worst possible ways of increasing ones leverage. \n\nYou should only succumb to delegation & management when all other methods fail you.\n\nAny use of delegation & management is a cry for a better abstraction or tool.\n\nFor example, booking a flight. We used to call travel agents. Now we have web interfaces that are better. You can express your preferences more quickly and precisely. You can use your monkey eyes to quickly take in all the options and trade-offs.\n\nYet, people still hate booking flights and often do delegate it to their assistants. Why?\n\nBecause the interface still isn't good enough! It still takes a way too many unnecessary clicks. \n\nThink about ecommerce before amazon & shopify optimized the checkout flows. I know very few people who delegate buying stuff on amazon. The interface has minimized incidental complexity.\n\nBut what about when you don't care about the details and just want something to work? For example, \n@pete_millspaugh\n told me about how his car has an issue. He tried to solve it himself, but he just doesn't have the time to learn about cars and how to fix them. Ultimately, he just wants a working car, not an understanding of cars. Thus, he delegates to a mechanic.\n\nThis is fine, but we should acknowledge that it's still the lack of sufficient tools that makes this delegation necessary. In this particular case, a big part of the problem seems to be a lack of observability.\n\n## Observability: a case study\n\nThis is similar to web servers that lack good observability. You would need to delegate to humans to ssh into various servers and read log streams, hunting for what could be going wrong. \n\nOr you could invest in observability tooling. When an issue comes up, one human at a once glance can see exactly where the problem is. If your observability is good enough, you can even automate remediation measures\n\nLet's pause and meditate on the distinction between delegating to your 4 human teammates to ssh around to find the issue vs an observability + remediation tool that automatically detects issues (like a ddos) and blocks the proper ip addresses. The second case may superficially appear like delegation, but it is in fact a TOOL at the right level of ABSTRACTION.\n\nThe same thing is happening in code. Humans are delegating the writing of code to AI agents. Humans are not reading this code. (You can call this \"vibe code\" or \"write-only code\".) People say that this is just the next step up in higher-level programming languages.\n\nYes, it's true that \"code nobody reads\" is not new. When we compile C to Assembly, nobody reads the Assembly. (Unless it's a leaky abstraction.) So isn't English the newest high-level programming language?\n\n## English is not a programming language\n\nNo! English is a very bad interface for expressing programming ideas.\n\nAs Dijkstra said, \"The purpose of abstraction is not to be vague, but to create a new semantic level in which one can be absolutely precise.\"\n\nEnglish is vague. Programming requires precision. The whole point of higher-level languages is to let you be precise at the right level — not to let you be imprecise.\n\nAs Bertrand Russel said, \"Everything is vague to a degree you do not realize till you have tried to make it precise.\"\n\nOr as Dijkstra said, \"Instead of regarding the obligation to use formal symbols as a burden, we should regard the convenience of using them as a privilege: thanks to them, school children can learn to do what in earlier days only genius could achieve.... When all is said and told, the \"naturalness\" with which we use our native tongues boils down to the ease with which we can use them for making statements the nonsense of which is not obvious.\"\n\nBut then why does prompt-to-app work so well? \n\nFor example, the last couple of days, I vibe coded a couple of small apps, barely looking at the code. It was super fun and useful! (Guys, I promise, I'm not a hater. I LOVE AI. Just ask my teammates or my fiancée.)\n\nThe code was meh, but that didn't matter. This does superficially seem similar to how we don't care that compiled bytecode is impossible to maintain.\n\nBut alas we get to the heart of the matter: an abstraction is a transparent tool. Unless something goes very wrong (ie abstraction leakage), when you use Python to describe something, you know exactly what's happening under the hood and how to steer it. This is similar to the controls of a car. You don't have to know anything about how the engine works to drive. These are good abstractions.\n\nThe same is true for no-code and low-code tools, like Wix, Squarespace, Zapier, Retool. These are very precise tools at a higher-level of abstraction. You know exactly what they are doing and how to make them do what you want.\n\nAn important property of a tool is the feedback it gives to the human about what is possible. You make a precise change and get immediate feedback. This is getting your hands wet in the clay. English-as-programming language does a very poor job at this. Especially when you're waiting minutes for any feedback.\n\nVibe coding (coding without looking at the code) is very similar to using a website builder like Squarespace. The generated code really does not matter. Until you want to do something complex. Then you're in trouble.\n\nUltimately, in my opinion, there is irreducible complexity in building software, and thinking that we can paper over it with english and smarter agents is wrong. It's not having enough respect for the underlying complexity, and how hard it is to build better abstractions.\n\nI've spent years of my life trying to build better abstractions and programming languages, ie improvements over react or http to make it easier for folks to build web apps. It's hard! At the end of the day, the state of the art is complex React, plus a hand-rolled server, and a lot of hard engineering work to make it all work.\n\nDon't you think if there were better abstractions available us programmers would use them?\n\nNo matter how smart AI gets, AI will be subject to the same laws of intelligence that humans are. Good code will be just as – if not more – important for AIs to write than it is for humans to write, and for the same reasons.\n\nThinking that understandable code doesn't matter is like thinking that it doesn't matter how heavy the materials we build buildings out of in the future because we can just build robots that are strong enough to carry it. Sure, but why waste the power? \n\nWe can put genius programmers on a shitty codebase and they can figure it out, but they'll be 100x more productive if you let them pay down the tech debt, and work in a beautiful codebase. The same will be true for AI.\n\n## The future of programming\n\nSo what is the future of coding with AI?\n\nThat's the wrong question. \n\nThe right question is: what is the future of programming we want? What is the dream programming experience 10 years from now to build some specific piece of software?\n\nThe fact that we'll have faster, cheaper, smarter AI is a given, in the same way that we'll have faster and cheaper cpus and gpus.\n\nAlan Kay invented the personal computer by buying his way into the future, in the 70s, spending millions on what would be commodity hardware in the 90s.\n\nBret Victor showed what a dream Learnable Programming environment would look like in 2012, which we still haven't been able to implement. There was no AI involved, simply because it wasn't the limiting factor for making programming more learnable.\n\nSoftware creation should be a transparent tool, with amazing abstractions, that removes all drudgery from programming, that lets you get even closer to the problem domain than before, lets you use your brain maximally, learn maximally, stay in a flow state, complete tasks quickly, manage lots of complexity, maintain and refactor large brownfield apps over long periods of time joyfully\n\nThis is the future we should be shooting for. Agents will certainly play a part, but in the same way that pistons play a part in internal combustion engines. Humans should use a steering wheel or pick their precise desired location on a map.",[],[163,355],"ee4154f8-2abf-11f1-876b-42dde27851f2",["D",1774713924926],"directory",[177,178,179,180,181,182,183,184,185,186,187,188,189,190,191],[163],["D",1739394544742],["D",1789559472742],{"_11":12,"_127":73},{"_11":12,"_123":-5,"_72":73,"_30":71,"_124":125,"_126":24},{"_38":113,"_13":16,"_32":35,"_114":75,"_115":62,"_116":117,"_118":79,"_119":75,"_120":41,"_121":14,"_122":12},"ctx",{"_51":-5,"_147":404,"_405":406,"_407":408,"_409":24,"_410":24,"_411":24,"_412":87,"_413":-5,"_414":-7,"_415":-7,"_416":26,"_417":24,"_418":24,"_419":-5,"_420":24,"_421":24,"_422":24,"_423":-5},"ENV",{"_375":376,"_377":378,"_379":63,"_380":381,"_382":383,"_384":385,"_386":387,"_388":389,"_390":391,"_392":393,"_394":395,"_396":397,"_398":399,"_400":401,"_402":403},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

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