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Hoot: Scheme on WebAssembly

https://www.spritely.institute/hoot/
2•AlexeyBrin•54s ago•0 comments

What the longevity experts don't tell you

https://machielreyneke.com/blog/longevity-lessons/
1•machielrey•2m ago•0 comments

Monzo wrongly denied refunds to fraud and scam victims

https://www.theguardian.com/money/2026/feb/07/monzo-natwest-hsbc-refunds-fraud-scam-fos-ombudsman
2•tablets•6m ago•0 comments

They were drawn to Korea with dreams of K-pop stardom – but then let down

https://www.bbc.com/news/articles/cvgnq9rwyqno
2•breve•9m ago•0 comments

Show HN: AI-Powered Merchant Intelligence

https://nodee.co
1•jjkirsch•11m ago•0 comments

Bash parallel tasks and error handling

https://github.com/themattrix/bash-concurrent
2•pastage•11m ago•0 comments

Let's compile Quake like it's 1997

https://fabiensanglard.net/compile_like_1997/index.html
1•billiob•12m ago•0 comments

Reverse Engineering Medium.com's Editor: How Copy, Paste, and Images Work

https://app.writtte.com/read/gP0H6W5
2•birdculture•17m ago•0 comments

Go 1.22, SQLite, and Next.js: The "Boring" Back End

https://mohammedeabdelaziz.github.io/articles/go-next-pt-2
1•mohammede•23m ago•0 comments

Laibach the Whistleblowers [video]

https://www.youtube.com/watch?v=c6Mx2mxpaCY
1•KnuthIsGod•24m ago•1 comments

Slop News - HN front page right now hallucinated as 100% AI SLOP

https://slop-news.pages.dev/slop-news
1•keepamovin•29m ago•1 comments

Economists vs. Technologists on AI

https://ideasindevelopment.substack.com/p/economists-vs-technologists-on-ai
1•econlmics•31m ago•0 comments

Life at the Edge

https://asadk.com/p/edge
3•tosh•37m ago•0 comments

RISC-V Vector Primer

https://github.com/simplex-micro/riscv-vector-primer/blob/main/index.md
4•oxxoxoxooo•41m ago•1 comments

Show HN: Invoxo – Invoicing with automatic EU VAT for cross-border services

2•InvoxoEU•41m ago•0 comments

A Tale of Two Standards, POSIX and Win32 (2005)

https://www.samba.org/samba/news/articles/low_point/tale_two_stds_os2.html
3•goranmoomin•45m ago•0 comments

Ask HN: Is the Downfall of SaaS Started?

3•throwaw12•46m ago•0 comments

Flirt: The Native Backend

https://blog.buenzli.dev/flirt-native-backend/
2•senekor•48m ago•0 comments

OpenAI's Latest Platform Targets Enterprise Customers

https://aibusiness.com/agentic-ai/openai-s-latest-platform-targets-enterprise-customers
1•myk-e•50m ago•0 comments

Goldman Sachs taps Anthropic's Claude to automate accounting, compliance roles

https://www.cnbc.com/2026/02/06/anthropic-goldman-sachs-ai-model-accounting.html
3•myk-e•53m ago•5 comments

Ai.com bought by Crypto.com founder for $70M in biggest-ever website name deal

https://www.ft.com/content/83488628-8dfd-4060-a7b0-71b1bb012785
1•1vuio0pswjnm7•54m ago•1 comments

Big Tech's AI Push Is Costing More Than the Moon Landing

https://www.wsj.com/tech/ai/ai-spending-tech-companies-compared-02b90046
4•1vuio0pswjnm7•56m ago•0 comments

The AI boom is causing shortages everywhere else

https://www.washingtonpost.com/technology/2026/02/07/ai-spending-economy-shortages/
2•1vuio0pswjnm7•57m ago•0 comments

Suno, AI Music, and the Bad Future [video]

https://www.youtube.com/watch?v=U8dcFhF0Dlk
1•askl•59m ago•2 comments

Ask HN: How are researchers using AlphaFold in 2026?

1•jocho12•1h ago•0 comments

Running the "Reflections on Trusting Trust" Compiler

https://spawn-queue.acm.org/doi/10.1145/3786614
1•devooops•1h ago•0 comments

Watermark API – $0.01/image, 10x cheaper than Cloudinary

https://api-production-caa8.up.railway.app/docs
1•lembergs•1h ago•1 comments

Now send your marketing campaigns directly from ChatGPT

https://www.mail-o-mail.com/
1•avallark•1h ago•1 comments

Queueing Theory v2: DORA metrics, queue-of-queues, chi-alpha-beta-sigma notation

https://github.com/joelparkerhenderson/queueing-theory
1•jph•1h ago•0 comments

Show HN: Hibana – choreography-first protocol safety for Rust

https://hibanaworks.dev/
5•o8vm•1h ago•1 comments
Open in hackernews

Show HN: Vector-logic, a lightweight rules engine from first principles

https://github.com/dmitry-lesnik/vector-logic
8•dmitry_stratyfy•2mo ago

Comments

dmitry_stratyfy•2mo ago
Hi HN, I'm one of the creators. I've been tackling the problem of managing complex business rules for years (especially in fintech), and wanted a lightweight, Python-native tool that was built on a solid theoretical foundation.

We built vector-logic (it's on PyPI) and wrote a hands-on guide for Towards Data Science: https://towardsdatascience.com/building-a-rules-engine-from-...

The whole framework is based on a theory we call 'State Algebra,' which we co-authored for arXiv: https://arxiv.org/abs/2509.10326

Happy to answer any questions!

Antibabelic•2mo ago
How does this compare to something like Prolog?
dmitry_stratyfy•2mo ago
Prolog is heavy-weight 1st order logic machine.

vector-logic is light-weight propositional logic inference engine. Optimised for simple queries like "what is the value of 'y' given all rules and evidences", and also allows you to iterate through the entire valid set (all valid assignments).

We also bothered to make the interface very simple and intuitive - you'll have very shallow learning curve.

nch1357•2mo ago
Hi Dmitry. This is really cool -- thanks for sharing! This is very clean and intuitive, and it definitely come in handy when I'm mapping out systems logic.
dmitry_stratyfy•2mo ago
Glad to hear that! Ping me if you have any questions
d_blumberg•2mo ago
Is it brute force or uses some sort of heuristics?
dmitry_stratyfy•2mo ago
Good point. Yes, it uses optimisation for various tasks.

First of all, it uses compact representatin of rules - similar to DNF, but converted to a sparse matrix.

Second, for the inference (which is a process of compiling the knowledge base) the order in which rules are compiled is crucial. We use two types of heuristic optimisations for this process, one is based on Jaccard similarity, another is so called predator-pray heuristics.

Happy to give more details, let me know

d_blumberg•2mo ago
I checked your benchmarks. Runtime with 30 rules is 5x longer than with 45 rules. Am I missing something?
dmitry_stratyfy•2mo ago
This is an expected behaviour. More rules impose more constraints on the feasible space. The space with more rules is hence much smaller. The only pitfall is that in the middle of calculation the feasible space may blow up before eventually shrinking. This is where the optimisation heuristics helps. Your previous question was spot on :)