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OpenClaw Creator: Why 80% of Apps Will Disappear

https://www.youtube.com/watch?v=4uzGDAoNOZc
1•schwentkerr•3m ago•0 comments

What Happens When Technical Debt Vanishes?

https://ieeexplore.ieee.org/document/11316905
1•blenderob•4m ago•0 comments

AI Is Finally Eating Software's Total Market: Here's What's Next

https://vinvashishta.substack.com/p/ai-is-finally-eating-softwares-total
1•gmays•4m ago•0 comments

Computer Science from the Bottom Up

https://www.bottomupcs.com/
1•gurjeet•5m ago•0 comments

Show HN: I built a toy compiler as a young dev

https://vire-lang.web.app
1•xeouz•6m ago•0 comments

You don't need Mac mini to run OpenClaw

https://runclaw.sh
1•rutagandasalim•7m ago•0 comments

Learning to Reason in 13 Parameters

https://arxiv.org/abs/2602.04118
1•nicholascarolan•9m ago•0 comments

Convergent Discovery of Critical Phenomena Mathematics Across Disciplines

https://arxiv.org/abs/2601.22389
1•energyscholar•9m ago•1 comments

Ask HN: Will GPU and RAM prices ever go down?

1•alentred•10m ago•0 comments

From hunger to luxury: The story behind the most expensive rice (2025)

https://www.cnn.com/travel/japan-expensive-rice-kinmemai-premium-intl-hnk-dst
2•mooreds•11m ago•0 comments

Substack makes money from hosting Nazi newsletters

https://www.theguardian.com/media/2026/feb/07/revealed-how-substack-makes-money-from-hosting-nazi...
5•mindracer•12m ago•1 comments

A New Crypto Winter Is Here and Even the Biggest Bulls Aren't Certain Why

https://www.wsj.com/finance/currencies/a-new-crypto-winter-is-here-and-even-the-biggest-bulls-are...
1•thm•12m ago•0 comments

Moltbook was peak AI theater

https://www.technologyreview.com/2026/02/06/1132448/moltbook-was-peak-ai-theater/
1•Brajeshwar•13m ago•0 comments

Why Claude Cowork is a math problem Indian IT can't solve

https://restofworld.org/2026/indian-it-ai-stock-crash-claude-cowork/
1•Brajeshwar•13m ago•0 comments

Show HN: Built an space travel calculator with vanilla JavaScript v2

https://www.cosmicodometer.space/
2•captainnemo729•13m ago•0 comments

Why a 175-Year-Old Glassmaker Is Suddenly an AI Superstar

https://www.wsj.com/tech/corning-fiber-optics-ai-e045ba3b
1•Brajeshwar•13m ago•0 comments

Micro-Front Ends in 2026: Architecture Win or Enterprise Tax?

https://iocombats.com/blogs/micro-frontends-in-2026
1•ghazikhan205•15m ago•0 comments

These White-Collar Workers Actually Made the Switch to a Trade

https://www.wsj.com/lifestyle/careers/white-collar-mid-career-trades-caca4b5f
1•impish9208•16m ago•1 comments

The Wonder Drug That's Plaguing Sports

https://www.nytimes.com/2026/02/02/us/ostarine-olympics-doping.html
1•mooreds•16m ago•0 comments

Show HN: Which chef knife steels are good? Data from 540 Reddit tread

https://new.knife.day/blog/reddit-steel-sentiment-analysis
1•p-s-v•16m ago•0 comments

Federated Credential Management (FedCM)

https://ciamweekly.substack.com/p/federated-credential-management-fedcm
1•mooreds•16m ago•0 comments

Token-to-Credit Conversion: Avoiding Floating-Point Errors in AI Billing Systems

https://app.writtte.com/read/kZ8Kj6R
1•lasgawe•17m ago•1 comments

The Story of Heroku (2022)

https://leerob.com/heroku
1•tosh•17m ago•0 comments

Obey the Testing Goat

https://www.obeythetestinggoat.com/
1•mkl95•18m ago•0 comments

Claude Opus 4.6 extends LLM pareto frontier

https://michaelshi.me/pareto/
1•mikeshi42•18m ago•0 comments

Brute Force Colors (2022)

https://arnaud-carre.github.io/2022-12-30-amiga-ham/
1•erickhill•21m ago•0 comments

Google Translate apparently vulnerable to prompt injection

https://www.lesswrong.com/posts/tAh2keDNEEHMXvLvz/prompt-injection-in-google-translate-reveals-ba...
1•julkali•21m ago•0 comments

(Bsky thread) "This turns the maintainer into an unwitting vibe coder"

https://bsky.app/profile/fullmoon.id/post/3meadfaulhk2s
1•todsacerdoti•22m ago•0 comments

Software development is undergoing a Renaissance in front of our eyes

https://twitter.com/gdb/status/2019566641491963946
1•tosh•23m ago•0 comments

Can you beat ensloppification? I made a quiz for Wikipedia's Signs of AI Writing

https://tryward.app/aiquiz
1•bennydog224•24m ago•1 comments
Open in hackernews

Structuring large Clojure codebases with Biff

https://biffweb.com/p/structuring-large-codebases/
98•PaulHoule•6mo ago

Comments

4b11b4•6mo ago
If I understand correctly... keep denormalized data in views?
jacobobryant•6mo ago
yes, that's part of it.
tiffanyh•6mo ago
OT: really appreciate the web design of the site. Simple, clean, info dense, and good contrast.
jacobobryant•6mo ago
Thanks! It's all from scratch.
aboardRat4•6mo ago
With biff, but without comsat?
codemonkey-zeta•6mo ago
Maybe I don't understand, but I thought the whole point of datomic (and XTDB by extension) was to avoid denormalization.

I am surprised the author says:

> "Old Yakread" has a lot of slow queries. For example, loading the subscriptions page on my account takes more than 10 seconds: for each of my hundreds of subscriptions, it has to run a query to figure out how many unread posts there are and when the most recent post was published.

I would have thought you would grab all this data in a single query roughly like this:

  ;; Assuming XTDB v1.19+ or v2
  (def q
    '{:find  [?sub-id ?unread-count ?last-pub]
      :in    [user-id]
      :where [[?sub :subscription/user user-id]
              [?sub :subscription/feed feed-id]
              ;; join to posts in that feed
              [?post :post/feed feed-id]
              [?post :post/published timestamp]
              (not [?post :post/read-by user-id])
      ]
      :find  [(count ?post) ?unread-count
              (max timestamp) ?last-pub]
      :order-by [[?last-pub :desc]]})

^ AI disclaimer, but I think it gets the gist, you do your logical joins right in the query
jacobobryant•6mo ago
You can do that, it's just slow if there are a lot of results.

Agreed you want to keep data in your main database normalized since it's easier to reason about and avoid bugs/inconsistencies in the data. The inherent trade-off is just that it's more computationally expensive to get the denormalized data.

The idea of materialized views is to get the best of both worlds: your main database stays normalized, and you have a secondary data store (or certain tables/whatever inside your main database, depends on the implementation) that get automatically precomputed from your normalized data. So you can get fast queries without needing to introduce a bunch of logic for maintaining the denormalized data.

The hard part is how do you actually keep those materialized views up to date. e.g. if you're ok with stale data, you can do a daily batch job to update your views. If you want to the materialized views to be always up-to-date then things get harder; the solution described in the article is one attempt at addressing that problem.

refset•6mo ago
Datomic offers the ability to declare a "composite index" which can help to accelerate some kinds of access patterns but can't solve 6NF join overheads entirely. If you want guaranteed read performance then denormalized views are the way to go, and perhaps even an IVM engine like Materialize - or this looked promising at one time: https://github.com/sixthnormal/clj-3df