This story was originally published on HackerNoon at: https://hackernoon.com/why-ai-coding-agents-suck-at-product-integrations-and-how-membrane-fixes-this.
AI coding agents excel at building features but fail at production integrations. The issue isn't AI capability—it's lack of integration-specific infrastructure.
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This story was written by: @membrane. Learn more about this writer by checking @membrane's about page, and for more stories, please visit hackernoon.com.

AI agents can scaffold UIs, call APIs, and generate data models in seconds. But when it comes to building production-grade integrations, they consistently under-deliver. This isn't an AI problem. It's an infrastructure problem.

This story was originally published on HackerNoon at: https://hackernoon.com/can-chatgpt-outperform-the-market-week-17.
New max drawdown...
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This story was written by: @nathanbsmith729. Learn more about this writer by checking @nathanbsmith729's about page, and for more stories, please visit hackernoon.com.

New max drawdown...

This story was originally published on HackerNoon at: https://hackernoon.com/the-next-ai-race-will-start-at-the-application-layer.
AI’s scaling race is ending. With reliable foundation models in place, the real advantage now lies in cost-efficient, fast, application-layer innovation.
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This story was written by: @tyingshoelaces. Learn more about this writer by checking @tyingshoelaces's about page, and for more stories, please visit hackernoon.com.

Engineers have been living a grueling, frustrating slog out of the mud, says Andrew Keen. Keen: The real story isn't a glamorous race to the top; it's been a slog. The new metrics for success are about cost, speed, and creative problem-solving, he says.

This story was originally published on HackerNoon at: https://hackernoon.com/your-ai-has-amnesia-a-new-paradigm-called-nested-learning-could-be-the-cure.
This post breaks down the three most surprising and impactful ideas from this research, explaining how they could give AI the ability to learn continually.
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This story was written by: @hacker-Antho. Learn more about this writer by checking @hacker-Antho's about page, and for more stories, please visit hackernoon.com.

Google Research has introduced "Nested Learning," a new, brain-inspired paradigm that fundamentally rethinks how AI models are built. The paradigm views a single AI model not as one monolithic entity, but as a system of components.

This story was originally published on HackerNoon at: https://hackernoon.com/google-and-yale-turned-biology-into-a-language-heres-why-thats-a-game-changer-for-devs.
The team built a 27B parameter model that didn't just analyze biological data—it made a novel, wet-lab-validated scientific discovery
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This story was written by: @knightbat2040. Learn more about this writer by checking @knightbat2040's about page, and for more stories, please visit hackernoon.com.

A new paper on a 27-billion parameter cell model isn't just about biology. It's data engineering and a blueprint for the future of applied AI. The team built a 27B parameter model that made a scientific discovery.

This story was originally published on HackerNoon at: https://hackernoon.com/how-search-engines-actually-answer-your-questions.
Modern search Q&A explained: how knowledge graphs, DeepQA, and MRC turn messy web pages into direct, trustworthy answers.
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This story was written by: @superorange0707. Learn more about this writer by checking @superorange0707's about page, and for more stories, please visit hackernoon.com.

Modern search Q&A is basically two engines working together: a knowledge-graph engine (KBQA) that’s great at hard facts, and a deep neural engine (DeepQA + MRC) that reads messy web pages like a speed-reading grad student. Around them is a lot of plumbing: data pipelines, retrieval, ranking, fusion, robustness tricks like R-Drop, and even opinion classification on top of long evidence passage

This story was originally published on HackerNoon at: https://hackernoon.com/google-gemini-file-search-the-end-of-homebrew-rag.
Will Google's Gemini File Search kill homebrew RAG solutions? We test drive to compare function, performance and costs. Plus sample code for PDF Q&A app.
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This story was written by: @zbruceli. Learn more about this writer by checking @zbruceli's about page, and for more stories, please visit hackernoon.com.

Will Google's Gemini File Search kill homebrew RAG solutions? We test drive to compare function, performance and costs. Plus sample code for PDF Q&A app.

This story was originally published on HackerNoon at: https://hackernoon.com/ai-is-coded-postmodernism-a-look-at-bohemian-rhapsody-the-matrix-and-more.
A clear, provocative look at how generative AI mirrors key postmodern concepts—simulacra, hyperreality, pastiche, authorship, and nonlinear fragmentation.
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This story was written by: @theaiethicist. Learn more about this writer by checking @theaiethicist's about page, and for more stories, please visit hackernoon.com.

Generative AI operates through the same core mechanisms that define postmodern art—simulacra, hyperreality, challenged authorship, pastiche, mixed high/low culture, and fragmented nonlinear assembly—making it a concentrated, computational form of postmodernism.