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maxbendick 1 days ago [-]
What a bizarre README. From the top:
> 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses!
Ok, it's a framework. That can mean many things. Let's look at the "Key Features."
> ~3,500 lines of code: We treat simplicity as the first principle.
???
whattheheckheck 1 days ago [-]
[flagged]
fractorial 1 days ago [-]
How does a _multi-trillion dollar company_ think this is good presentation?
rk06 20 hours ago [-]
it is made by Microsoft employees, not Satya. Microsoft employees have various degrees of freedom on what level of quality to target
with absence of QA, quality is going downhill. thanks to AI mandate, quality is going downhill a lot faster
RugnirViking 22 hours ago [-]
seems to be a toolkit for taking some LLM model and training/finetuning it further based on some agentic task (like painting, playing a video game, etc)
grim_io 20 hours ago [-]
So this is the Xzibit meme of agent skills?
ricardo_lien 1 days ago [-]
how good is this?
codetiger 1 days ago [-]
Am still figuring out "What is this?"
owebmaster 16 hours ago [-]
I'd bet not even the vibecoders that prompted it know. But Claude said it's production ready
qainsights 2 days ago [-]
Agent Lightning v1.0.1 marks the first official release of the Agent Lightning Skill, which helps coding agents optimize other AI agents.
Provide an editable agent and a benchmark, and the skill guides systematic improvements to prompts, tools, workflows, models, and reasoning settings—balancing accuracy, cost, latency, and reliability through measured iteration.
> 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses!
Ok, it's a framework. That can mean many things. Let's look at the "Key Features."
> ~3,500 lines of code: We treat simplicity as the first principle.
???
with absence of QA, quality is going downhill. thanks to AI mandate, quality is going downhill a lot faster
Provide an editable agent and a benchmark, and the skill guides systematic improvements to prompts, tools, workflows, models, and reasoning settings—balancing accuracy, cost, latency, and reliability through measured iteration.