AI 资讯
Perl PAGI Project Updates
Quick update to anyone interested in upcoming changes to the PAGI project (spiritual successor to Plack/PSGI). 1) Distribution split up: when we released PAGI, we initially released everything as one distribution. PAGI ( https://metacpan.org/pod/PAGI ) currently has a) the PAGI specification; b) the reference server and c) a bunch of ease of use tools, similar to the role that the Plack distribution played for PSGI. Putting everything into one place was just to make my life easier as in the early bunch of releases there was a lot of fixes and updates, most of which cut across all three parts of PAGI. Also I wanted to make it easy for people getting into PAGI to be able to explore the ecosystem. However now that code seems to be settling down having these in independent repos and releases makes more sense. Going forward the PAGI repo will only update if the spec itself changes; PAGI::Server and PAGI::Tools (where all the utilities and helpers now go) likewise. I think this will start to bring some stability to the ecosystem, especially now that PAGI::Server is functionally complete based on the goal chart I had for it initially. So I will only update it to fix bugs and security issues. PAGI::Tools will probably continue to see evolution over the summer as I start to nail down more common use cases and identify patterns worth encapsulating. 2) Specification clarifications and updates: The PAGI specification itself will move to v0.3 in the next release and it contains mostly clarifications and fixes. Biggest change will be a more detailed mechanism for controlling streaming output, especially around handling back pressure as well as new callbacks to notice when the output buffer is getting full and when it clears. Hopefully these changes will make it easier and more reliable to do streaming in PAGI. PAGI::Server has been updated to match, and the response helper in PAGI::Tools has some updates around that as well. Currently all this sits on Github: https://github.com/j
AI 资讯
I built Proofline because AI agents are getting too good at sounding finished
AI agents are getting very good at writing final reports. The problem is not only that they make mistakes. The problem is that sometimes they make mistakes with excellent presentation. Proofline is a 5-skill Markdown pack that catches fake-ready output before it turns into a release, handoff, public post, or "yeah, looks done". What Proofline does It is not trying to be another giant agent. It works as a review route after the agent produces a result: Reference Gap Ready Gate Reality QA Lean Pass Repair Report Compiler Each step asks an annoying but useful question: what is missing from the references, what was not checked, where did the agent pretend everything was fine, and what actually needs to be fixed? Who it is for Builders working with Codex-style agent chats, AI coding workflows, Markdown handoffs, and any process where "done" needs to mean more than a confident paragraph. Release: https://github.com/aisflows/proofline/releases/tag/v0.2.0-rc5
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