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Developer Tooling - Page 13
Tools that change how teams build, review, and ship. Curated tldw.news briefings about developer tooling, with practical engineering takeaways from long-form AI and developer-tool videos.
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The Pragmatic EngineerWhy agentic design still needs the human sketch
Design engineer Maggie Appleton on why sketching remains essential even as agents accelerate UI prototyping, and why multiplayer alignment is the next big…
GOTO ConferencesAI Agents Won’t Work Without Platform Engineering
The book 'Thinking in Platforms' argues that AI agents require structured platforms. But the harder shift is organizational: treating platforms as products…
Theo - t3․ggGrok 4.7: The Expensive Stepchild of the AI Model Race
Grok 4.7 promised to be the best model ever. It costs 2x more than GPT-6 Astra, has AI safety mishaps, and a fish-slope game so bad it's meme-worthy. The…
Theo - t3․ggYour Agent Setup Is Probably Outdated: Trust Defaults
Most Claude Code fears are outdated. Learn how to prompt for autonomy, avoid the dumb zone, and let agents finish tasks without babysitting.
Latent SpaceWhy Jev treats AI as a database, not a coworker — and
TypeSafe launches Jev, a model built for programmatic decision-making, not human chat. Three structured output types, calibration scores, and a sharp…
AI EngineerFrom Prompt Slop to Skill Engineering: A Practitioner's Playbook
Prompting alone cannot overcome a model's gravitational pull. Skill engineering — treating skills as harness extensions with sub-agents, anti-attractors, and…
Cole MedinJev Changes the Cost Structure of AI Agent Workflows
Jev introduces system-one models for fast, cheap decision-making. 40-1000x cheaper than LLMs for classification. The trade-off: unproven at production scale.
David OndrejWhy engineering leaders should care about Jeff's real-time AI decisions
New Jeff model is 200x faster, 400x cheaper than GPT-4o mini, returns calibrated probabilities in 100ms with zero hallucinations. Not a chat model, but a…
AI EngineerSmall models are good. Your serving stack is the problem.
Small models have caught up to frontier models on specific tasks. The problem: traditional inference clusters can't serve them efficiently. Pull-based…
Machine Learning Street TalkEnterprise voice agents fail. Here's the fix most teams miss.
Speech recognition is not solved. Mistral's research lead breaks down why enterprise voice agents fail at scale and why customization, not generalization, is…
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