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Developer Tooling - Page 2
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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AI EngineerACP: The protocol that could finally decouple clients from agent harnesses
ACP standardizes how clients talk to AI agents. Early demos show any client controlling any harness. Adoption is the open question.
AI EngineerMCP apps fail without data-model separation — Indeed's practical lesson
Indeed's AI team reveals why most MCP app implementations create a black-box problem. The fix: separate data processing from UI rendering to keep the model…
AI EngineerAI agents fail without organizational context: the case for context engineering
AI agents are smart but ignorant of your organization's history. Context engineering solves the gap between code that compiles and code that works.
David OndrejOpen models reached parity. Now the bottleneck is your CI pipeline.
Open-weight models now rival frontier labs. The real competitive edge isn't the model—it's robust evals and CI infrastructure that enables reliable…
All About AIAI agents built a trading bot. Validation was the real challenge.
A coding agent built a weather trading bot in hours - then its own uncertainty logic blocked the trade. Agent speed is outpacing validation.
AI EngineerLLM inference is a memory problem, not a compute problem
Inference cost is the hidden operational tax on AI products. This workshop breaks down the KV cache bottleneck, model vs. serving optimisations, and when VLM…
Latent SpaceKilling code review is only safe for small, agent-native teams
Mandatory code review is gone at AMP. Bet: trust, agents, and cloud dev make review gates obsolete. Catch: that math works for 20 people, not every org.
Y CombinatorHarness, not model, now decides agent performance and cost
How much agent performance comes from the harness, not the model? YC's harness night shows huge gains—and the governance costs that follow.
Theo - t3․ggStop Pretending You Understand. Your Codebase Is Too Big.
If you think you must understand every line of your codebase, you’re wrong. The video explains why partial understanding is the norm and a feature, not a bug.
Hugging FaceWebGPU AI hits a device fragmentation wall that most teams will underestimate.
Hugging Face launched 207 WebGPU kernels for browser AI. The real news is the Jinja template approach that compiles per-device GPU code. Faster? Yes. But…
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