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Coding Agents - Page 3
Practical shifts in agentic coding, review, and delivery. Curated tldw.news briefings about coding agents, with practical engineering takeaways from long-form AI and developer-tool videos.
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Cole MedinWhy your AI coding agent keeps ignoring your rules—and how to fix
Rules are probabilistic instructions; hooks are deterministic guarantees. This video makes the case that most teams overload their agent rules with process…
AI EngineerStop designing AI workflows. Start designing AI environments instead.
Stanford and Together AI show that environments—not workflows—let AI agents solve open science problems. Agents recently solved a 40-year-old kissing number…
AWS DevelopersSelf-Writing Agents: Shelf Life Extended, But Complexity Multiplied
Agents that write their own tools extend their shelf life—but without evaluation and guardrails, you trade maintenance for instability.
Latent SpaceVoice AI: The hard parts are pipeline design and latency, not models
Voice AI success hinges on pipeline orchestration, not model choice. Latency, cost, and reliability are the real constraints. Teams should expect a hybrid…
Cole MedinThe Slop Apocalypse Is Real – Why AI Code Bloat Demands New
AI code bloat is real – BMAD founder warns of a 'slop apocalypse' that increases token spend and slows cycles. Engineering leaders must rethink governance…
Theo - t3․ggWhy memory systems make AI coding agents worse, not better
Memory systems for coding agents are worse than useless. They store stale, irrelevant context that misleads models. The better approach: invest in…
Machine Learning Street TalkThe reasoning trail leads back to you: a security blind spot in
Encrypted reasoning traces from Claude, GPT-4, and Gemini can be decoded and replayed. Your private thoughts may not be private. Teams should treat reasoning…
AI EngineerAgent building is easy. Context is where agents still fail.
Building agents is now trivial. But as Jeff Ng demonstrates, agents without organizational context confidently recommend fixes that caused past outages. The…
Hugging FaceSmaller AI models can beat frontier models by using them as tools
A small RL-trained model outperforms frontier models at replicating ML research figures by using Codex as a tool—suggesting orchestration matters more than…
AI EngineerAgent automation: the real lesson is evaluation, not model selection
A single Hugging Face engineer replaced manual outreach with an agent workflow. The real signal? Evaluation matters more than the model. And he doesn't tell…
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