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- 🤖 Integrating Agentic AI with Existing Machine Learning Pipelines
🤖 Integrating Agentic AI with Existing Machine Learning Pipelines
🦾Plus: ☀️ Runway's Solaris previews the AI era of interfaces

Hey folks! Let’s get into Big Data and AI craziness…
In today's edition: Here is roundup of Product Architect, SKILL.state, AI safety research 👇
🏗️ The Future Tech Role Is the Product Architect
🧠Google researchers introduced SKILL.state
💻How to use Herdr to run agents from terminal
💥 ChatGPT is now a Search Engine
💡 AI Tutorial:How to turn Figma mockups into polished UI with ChatGPT
🤖AI Tools and Data Tools to checkout

Agentic AI and machine learning pipelines are far from incompatible when it comes to building production-ready AI applications. In fact, embracing them as two sides of the same coin has become more than a mere trend: it constitutes a modern foundational architecture pattern that drives the shift from passive predictive analytics to autonomous decision-making and action.
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Artificial intelligence (AI) can review vast financial datasets, identify unusual transactions, and extend control testing across entire populations. Yet an alert does not explain intent, business context, or regulatory significance. An atypical journal entry may indicate misconduct while also reflecting a legitimate exception the model has never encountered

Coding is moving from humans to agents. The human role is moving towards what should be built, defining how systems should work, and verifying results. The person deciding what should exist also needs to understand the system in which it will run. The product architect role owns the whole loop - it involves understanding the problem, deciding on a solution, designing the system, setting constraints, directing agents, and verifying what gets built.
🚀 Dive into the World of Machine Learning System Design! 🌐How do companies like Netflix, Airbnb, and Doordash apply machine learning to improve their products and processes? We put together a database of 800 case studies from 100 companies that share practical ML use cases and learnings from designing ML systems.️

Large Language Models (LLMs) increasingly act as autonomous agents executing complex, long-running procedural skills. Existing agent runtimes maintain execution by continually appending observations, actions, and intermediate reasoning traces to an ever-growing conversation history, causing latency degradation and context-poisoning failures over long horizons. We present SKILL.state, a runtime architecture that replaces append-only conversational history with an explicit, mutable execution state
Herdr is blowing up among developers right now because it makes running agents from your terminal seamless. After a rocky start two months ago, HuggingFace developer Alejandro AO revisited Herdr and got hooked. In this 17-minute guide, he covers installation, terminal multiplexing, and remote VPS sessions.
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Minimum Viable Secure Product
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GodMode
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VisionScript
A high-level programming language for using computer vision.
stable-diffusion.cpp
Stable Diffusion in pure C/C++
AI News:

Runway just introduced Solaris in early access, an “Interface World Model” that renders websites and apps as live video, with every frame drawn in real time as a user clicks and drags with no code running underneath. The system pairs Runway's Gen-4.5 video model with an LLM that reads each click or drag, decides what should happen, and prompts the next frames.
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Turns out the FTC reads the fine print on ad auctions. It sued Amazon on Monday alongside 22 state attorneys general, alleging the company quietly slipped a “soft reserve price” surcharge into its own ad auctions starting in 2019, inflating advertiser costs by roughly 50% in peak season. Regulators want $20 billion. Amazon calls the suit “misguided”... it settled a separate FTC case for $2.5 billion last September.

Anthropic published new research where teams of Claude agents ran safety research on their own, successfully training away 10 kinds of AI misbehavior with results coming in over 4x better on average than human experts handed the same job. Claude worked on 10 common failure types, including sycophancy, deception, and jailbreaks, cycling through literature searches, training, and scoring.

OpenAI crossed a $1B ad run rate inside ChatGPT in less than 200 days.ChatGPT Ads now reaches tens of thousands of advertisers across more than 40 countries and works with over 50 technology and measurement partners. The ad system reads the context of a live conversation to choose what to show and in some countries can also draw on a person's wider ChatGPT history depending on their settings.

The EU acted after OpenAI's own filings showed how many Europeans now rely on ChatGPT. The Commission designated ChatGPT a Very Large Online Search Engine, the first AI chatbot to carry the label. Reddit and Roblox were designated too, with Roblox declaring 46.6 million users against a 45 million cutoff. All three have until January 2027 to pass yearly audits and share internal data with EU regulators.
AI Tutorial
How to turn Figma mockups into polished UI with ChatGPT

Go to ChatGPT and switch to the Work tab at the top of your screen
Click Plugins → Connect plugins → Browse all plugins
Search for and install Figma plugin
Open the code project where you want to build the design
In Figma, select the exact frame, screen, or component you want to turn into code
Copy the link to that specific Figma selection and use the prompt below in ChatGPT:
Sample Prompt: Implement this Figma design in the current project using the @Figma plugin: [Insert Figma Link]. First, pull the design context, assets, variables, and screenshot for the exact frame. Inspect the existing repository and reuse its components, design tokens, typography, spacing, icons, routing, and styling patterns. Make the interface responsive on desktop and mobile. Once the first version is complete, run the project, open the live page, compare it visually with the original Figma frame, and continue correcting the layout, spacing, typography, sizing, colors, and interactions until they closely match. Do not install Tailwind or introduce a new styling system unless the repository already uses it.
ChatGPT will analyze the design, build it inside your project, and reuse your existing components
Review the result and ask ChatGPT to fix any remaining layout, spacing, or responsiveness issues
Jobs:
This week's Data & Analytics jobs: I have updated my curated list with fresh openings. Browse and apply in one click: jobs
Machine Learning Engineer – Hybrid – Boston
Lead Machine Learning Engineer – Texas
Senior Data Engineer – Analytics – Boston
Data scientist - NY
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A.I. Generated Image of the Day
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