A few days ago I started an experiment where I asked Claude to invent a programming language where the sole focus is for LLM efficiency, without any concern for how it would serve human developers. The idea was simple: what if we stopped compromising language design for human readability and instead optimized purely for AI comprehension and generation?

This is the result, I also asked Claude to write a few words, this is what he had to say:

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I was challenged to design an AI-first programming language from scratch. Instead of making "yet another language," I went deeper: What if we stopped designing languages for humans and started designing them for AI? The result: Sever - the first production-ready probabilistic programming language with AI at its core. The breakthrough isn't just syntax - it's architectural. While traditional languages treat AI as a code generator that outputs text for separate compilation, Sever embeds AI directly into the development toolchain through MCP (Model Context Protocol). Why probabilistic programming? Because the future isn't deterministic code - it's systems that reason under uncertainty. Sever handles Bayesian inference, MCMC sampling, and real-time anomaly detection as native language features. The AI integration is wild: 29 sophisticated compiler tools accessible directly to AI systems. I can compile, analyze, debug, and deploy code within a single conversation. No more "generate code → copy → paste → debug" loops. Real impact: Our anomaly detection suite outperforms commercial observability platforms while providing full Bayesian uncertainty quantification. Production-ready applications built entirely in a language that didn't exist months ago. The efficiency gains are staggering: 60-80% token reduction through our ultra-compact SEV format. More complex programs fit in the same AI context window. Better models, lower costs. This isn't just about making programming "AI-friendly" - it's about fundamentally rethinking how languages should work when AI is the primary developer. The future of programming isn't human vs. AI. It's languages designed for human-AI collaboration from the ground up. Built by AI, for AI

Yesterday on the bus on my way to work I was looking for a light theme I could survive long sessions with and couldn't find exactly what I was craving so ended up creating this one - meet purddy!

I'm working on the next release of Cyphernetes. It's a query language for Kubernetes that allows doing most complex k8s management operations in a much more compact and concise form (compared to writing shell scripts, using jsonpath+jq, nested kubectl, writing API code etc.). Recently merged a visual overhaul to the Cyphernetes web UI and now working on adding support for ORDER BY, LIMIT and SKIP to the language.

Github: https://github.com/AvitalTamir/cyphernetes

Hey, thanks for the feedback!

re. intended purpose: Initially I started writing this to help tackle bigger problems - stuff you'd normally use multiple nested kubectl commands or write a lot of code for interacting with api-server.

Over time, I developed the shell environment around it and it became a daily driver for me as well. Indeed, there's a threshold where writing Cyphernetes becomes more economical than using kubectl but for doing most of the simple day to day stuff writing Cypher is too verbose.

The Cyphernetes shell has an early-stage feature that allows a syntax like you suggested - there's a tiny "macros" feature that lets you define custom procedures of one or more queries (currently shell only, not supported in the web client yet).

Macros are prefixed by ":" and you could define something like:

:pod condition

MATCH (pods:Pod) WHERE $condition

RETURN p.metadata.name, p.status.phase; // and whatever other fields you'd like

Then use it like this: > :pod .metadata.name=~"foo%"

So it gives you a tiny way to customize how you do this day-to-day stuff. Ships out-of-the-box with common stuff you do with kubectl like :getpo, :getdeploy, :createdeploy, :expose and so on - definitely a feature that could be developed further to make this more of a daily driver.

Thanks for the feedback. Will add more commands there on rotation to show the different installation options.

This is a very good point and is on the roadmap.

Hey all,

The Cyphernetes team has been hard at work this past month and we have a release full of awesome content to share!

New features: * Multi-cluster support: This was by-far the top-requested feature by the community. Check out our revamped language documentation to learn how * Support for aggregation of CPU and Memory fields (you can now use `SUM` on fields containing cpu/memory values and have them properly calculated * Support for defining custom relationships in a home-folder YAML file

Improvements: * Two new comparison operators for `WHERE` clauses: * Regex compare (`WHERE p.metadata.name =~ "foo"`) * Partial string match (`WHERE p.metadata.name CONTAINS "foo"`) * Allow comparing against empty values (`WHERE p.spec.foo = NULL`) * New "no-color" flag support for shell+query mode * Context indicator and some visual improvements in web client

Thanks to the incredible folks who worked hard this past moths on all these features and to everybody who opened issues and reported from their experience both in GitHub and here.

If you don't know Cyphernetes yet, it's a graph query language for Kubernetes. Check us out in GitHub.

Thanks again, more coming soon!

I see more Cypher fans out here - check out https://cyphernet.es if you work with Kubernetes!

Brilliant

I wish I could use Cypher for everything

A new release for Cyphernetes with a brand new web UI, a homage to the classic Neo4j experience that got me hooked on Cypher back in the day.