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Every published item, in order · 4309 items
Sep 27
How-toBuildersSelected73°17:48
CMU Releases AI Agents Course 11-768 with 9 Lectures Online

Free access to a full graduate-level agent curriculum from two researchers behind major agent frameworks makes this a structured alternative to scattered blog-post learning. Practitioners building agent systems can use the videos and cmu-agents.com materials as a self-study path, working through the 9 published lectures before the rest of the term's recordings land.

shao__meng@shao__mengSource
How-toBuildersMulti-sourceSelected73°16:20
Opus 5.5 Draws a BaoCut Promo Video Frame by Frame

The takeaway is that coding agents can double as animation pipelines: deterministic Canvas rendering plus a beat table gives Opus 5.5 a feedback loop where keyframe stills can be self-checked before a full render. Developers who want AI-made promo assets without a motion-design tool can adapt this prompt structure, grounding the model in real code and specs to avoid hallucinated features. It also shows Claude Code reusing local CLIs like Codex without API keys.

Event
宝玉@doteySource
How-toBuildersSelected12:48
Harrison Chase argues probability thresholds beat LLM judgment in agents

The point reframes agent reliability as an engineering problem: convert model judgment into numeric scores so thresholds, logs and eval tests become possible. Teams building production agents can adopt this pattern to make decisions auditable and testable. It contrasts with opaque end-to-end prompting where behavior is hard to regression-test.

Harrison Chase@hwchase17Source
How-toBuildersSelected73°10:48
Ollaya serves open decision models locally with TypeSafe-compatible API

Decision models are a lighter, cheaper alternative to calling a full LLM for routing and classification tasks, and Ollaya makes them as easy to run locally as Ollama made general models. Developers building LLM routers, guardrails or zero-shot classifiers can drop it in behind a TypeSafe-compatible API without cloud dependencies. GLiClass and NLI-style models offer a concrete comparison point against embedding-based classifiers.

Geek@geekbbSource
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How-toBuildersMulti-sourceSelected73°05:49
Builders urged to learn engineering fundamentals before using agents

Agent outputs can look correct while hiding suboptimal or fragile solutions, so evaluation and engineering judgement stay essential even as coding assistants improve. Developers and technical leads adopting tools like Claude Code should invest in fundamentals — evals, architecture and concurrency — rather than delegating decisions entirely. The exchange offers a practical counterpoint to messaging that coding skills are no longer needed.

Event
elvis@omarsar0Source
How-toBuildersMulti-sourceSelected72°05:48
Jev Router Experiment Shows Benchmark Limits in Agent Harness Testing

Independent harness tests like this show why vendor benchmark numbers often fail to predict task-level performance for your own workflows. Builders evaluating model routers or agent harnesses can take the concrete lesson that results depend heavily on the test setup, so replicating with your own workloads matters more than leaderboard rankings. The System One versus System Two framing offers a practical lens for deciding when to route cheaply and when to pay for heavier reasoning.

Event
elvis@omarsar0Source
Sep 26
How-toBuildersSelected22:25
Sebastian Raschka's Reasoning From Scratch Video 5 Covers Log-Probability Scoring

Log-probability scoring underlies loss functions like cross-entropy in pre-training and distillation, so the material transfers well beyond answer ranking. Practitioners building inference-time scaling or self-refinement pipelines can follow along with the timestamped PyTorch implementations and the MATH-500 evaluation setup. It is a hands-on complement to reading papers on reasoning methods.

Official accountSebastian Raschka@rasbtSource
How-toBuildersSelected73°17:02
Open-source Skill teaches Claude Code APK reverse engineering

The interesting part is the workflow design: instead of shipping binaries, the Skill encodes expert decision-making and lets the agent provision its own toolchain, which is a reusable pattern for other domain skills. Reverse engineers and mobile security researchers can plug it into Claude Code or Codex and get a working APK analysis pipeline. Being MIT-licensed, it is free to fork and adapt for internal triage work.

Lxfater@lxfaterSource

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