Exploring the Versatility of the Janet Programming Language
By
veqq
Fresh out the oven, still warm. Top of the tray.
Summary
Janet is a functional and imperative programming language that can be used for system scripting, embedding in other programs, rapid prototyping, and dynamic systems. It is implemented mostly in standard C99 and runs on Windows, Linux, and macOS. Janet is easily portable to new platforms and offers more out-of-the-box features compared to other embeddable languages.
Key quotes
· 3 pulledJanet makes a good system scripting language, or a language to embed in other programs.
Janet can be easily ported to new platforms.
While Janet is embeddable, it comes with a bit more out of the box than many other such easily embeddable languages.
You might also wanna read
Four practical steps to control Azure Foundry token costs for agentic AI workloads
This article provides practical guidance on controlling token costs in Microsoft Azure Foundry, particularly for agentic AI workloads where
purplefrogsystems.com·42m ago
MerLean-Prover: A Recursive Agent Harness for Lean 4 Theorem Proving Outperforms Baselines
MerLean-Prover is an end-to-end Lean4 theorem prover that replaces 'sorry' declarations with kernel-checkable proofs using three agent types
arxiv.org·49m ago
Why small pull request policies can backfire on software quality
The article critiques a common software engineering policy that limits pull requests (PRs) to small sizes (e.g., 500 lines, few files). Whil
apenwarr.ca·2h ago
How Anthropic contains Claude's expanding access across its products
Anthropic describes how it has evolved its approach to granting Claude, its AI assistant, increasingly broad access to internal systems over
anthropic.com·4h ago
Testing Cursor's Jira integration: How ticket quality affects AI agent performance
Cursor launched a Jira integration that lets developers assign tickets directly to an AI agent, eliminating context switching. The author te
bit.ly·4h ago
Netflix engineer's open-source tool cuts AI token usage by up to 90%
Netflix senior engineer Tejas Chopra created software called "Project Headroom" that prunes redundant tokens from AI agent instructions befo
theregister.com·4h ago