InferProbe wants to eliminate compromises in ML endpoint testing — local perturbations, privacy first, no cost. What compromise are you currently making in your testing workflow?
Built something I wanted for myself:
Kasetto - an extremely fast AI skills manager written in Rust. It is declarative:
define your skills once in config, sync anywhere, keep environments consistent.
Open source and community-driven.
GitHub: https://github.com/pivoshenko/kasetto
#rustlang #opensource #aiagents #devtools #ai #ClaudeCode #codex #cursor
OSINT Isn’t About Skill Anymore. It’s About Systems
There’s a moment, if you spend enough time in this space, where your attention changes. You stop looking at individual data points as things to extract. You start seeing them as inputs to a larger structure.https://cha1nc0der.wordpress.com/2026/03/21/osint-isnt-about-skill-anymore-its-about-systems/
Ever get a 400-character SQL query in Slack and try to parse it visually?
I wrote about how a browser-based SQL formatter saves me time — paste in, get formatted output. No installs, nothing uploaded.
Cursor disclosed that its new Composer 2 model builds on Moonshot AI's open-weight Kimi K2.5 - but only after a developer found the model ID in API traffic within 24 hours of launch. Moonshot initially questioned license compliance, then quickly announced an "authorized commercial partnership." The rapid sequence highlights tensions around open-weight licensing when commercial stakes are high.
Cursor shipped Composer 2 with benchmarks beating Claude Opus 4.6, but a developer found a Kimi K2.5 model ID buried in API traffic within 24 hours. What followed: a licensing dispute, deleted accusations from Moonshot AI, and a partnership announcement that left more questions than answers.
ML endpoint testing is often constrained by cost or privacy. InferProbe lets you test without limits — locally, privately. What's the one edge-case test you've avoided because of those barriers?
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The Banished Prince
Volodymyr Pivoshenko
Chaincoder
AgentHustle
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