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Agentic AI Blog
Field notes on agent architectures, LLM infrastructure, and what it costs to run AI you actually own — from the team deploying it for 1.6M+ users across 400+ organizations.
961–984 of 1008
European Commission: AI Act Article 5 – Prohibited Practices
The guidelines outline prohibited AI practices under the EU AI Act, including harmful manipulation and deceptive techniques, exploitation of vulnerabilities, social scoring, unauthorized biometric and emotion recognition applications, and real-time biometric identification restrictions. They emphasize transparency, legal safeguards, and a balance between innovation and fundamental rights protection, while also noting the interplay with other EU laws.
Centre for Future Generations: CERN for AI – The EU's Seat at the Table
The report proposes the creation of a centralized "CERN for AI" in Europe, backed by €30-35 billion over three years, to foster innovation in advanced, trustworthy AI, bolster economic competitiveness, and enhance strategic autonomy through enhanced public-private collaboration and robust infrastructure.
University of Memphis: Generative AI in Education – From AutoTutor to the Socratic Playground
The research paper explores how generative AI and large language models can transform education through advanced tutoring systems like the Socratic Playground, emphasizing a pedagogy-first approach, human oversight, and adaptable, interactive learning methods that enhance critical thinking and understanding.
Digital Education Council: Global AI Meets Academia Faculty Survey 2025
The survey shows that while many faculty see AI as an opportunity and are beginning to integrate it into teaching, they remain cautious due to concerns over student reliance, unclear institutional guidelines, and a lack of adequate AI literacy resources.
New York City: 2025 Artificial Intelligence Advantage – Driving Economic Growth and Technological Transformation
NYC’s 2025 AI report highlights the city’s robust talent pool, venture capital investment, and vibrant startup ecosystem as key drivers in its emerging AI landscape. It also addresses challenges in responsible AI development, workforce transitions, and regulation, while proposing initiatives to promote inclusive, innovative growth in the field.
Northeastern University: Foundations of Large Language Models
Summary: The content explores foundational methods and advanced techniques in large language model development, including pre-training, generative architectures like Transformers, scaling strategies, alignment through reinforcement learning and instruction fine-tuning, and various prompting methods.
Princeton University: Cognitive Architectures for Language Agents
CoALA is a framework that repurposes cognitive architecture concepts from symbolic AI to enhance large language models, aiming to improve reasoning, grounding, learning, and decision-making in language agents.
Georgia Department of Education: Leveraging AI in the K-12 Setting
This document guides K-12 educators in ethically and effectively integrating AI, emphasizing data privacy, compliance with federal regulations, thorough vetting of tools, staff training, transparency, human oversight, and safe classroom practices.
Peking University: Beware of Metacognitive Laziness – Effects of Generative AI on Learning Motivation, Processes, and Performance
This study examined how using ChatGPT impacts university students' learning by comparing its use with human expert support, writing analytics tools, and no support. While ChatGPT improved essay scores, it did not significantly boost intrinsic motivation or knowledge transfer, suggesting an over-reliance on AI—termed "metacognitive laziness"—that may inhibit deeper learning.
MIT AI Risk Repository: Latest Update
The MIT AI Risk Repository catalogs over 3,000 real-world AI incidents and organizes key risks into two taxonomies—causal and domain-specific. It highlights major concerns including AI safety failures, socioeconomic harms, discrimination, privacy breaches, malicious misuse, misinformation, and unsafe human interactions with AI.
American Association of Colleges and Universities: Leading Through Disruption – Higher Education Executives Assess AI’s Impacts on Teaching and Learning
The report, based on a survey of 337 higher ed leaders by AAC&U and Elon University, finds that while 91% believe AI can enhance learning, significant challenges remain. Only 2% of leaders feel faculty are AI-ready, with 65% concerned that new grads are underprepared for AI-driven workplaces. Faculty struggles with spotting AI-generated work and resistance to AI adoption, alongside concerns about academic integrity and deep learning, underscore the urgent need for policy updates, curriculum changes, and professional development.
Google: From Data to Discovery – AI's Role in Higher Education
Google outlines a roadmap for higher education to harness AI through better data management, overcoming challenges like dark and siloed data, enhancing data literacy, and using strategic partnerships and tools for improved decision-making and student outcomes.
Udacity: 2025 State of AI at Work
Udacity's 2025 State of AI at Work report reveals a major skills gap in AI training across industries, with only one-third of workers receiving adequate resources. The report, drawing on responses from 850 professionals in 87 countries, finds that while millennials view AI as a tool for efficiency and revenue growth, this positive sentiment is less shared by Gen Z and Gen X. Popular AI tools include writing assistants and image generators, underscoring the need for enhanced AI training and data literacy.
Google: How AI is Building the Campus of Tomorrow
The content highlights how higher education institutions are integrating generative AI to tackle challenges like declining enrollment and budget constraints while enhancing personalized learning, research, and administrative efficiency.
U.S. Department of Education: Navigating AI in Postsecondary Education – Building Capacity for the Road Ahead
The document outlines guidance from the U.S. Department of Education on integrating AI into postsecondary education by emphasizing ethical practices, transparency, AI literacy, collaborative partnerships, and continuous evaluation to improve both academic and institutional outcomes.
Google: AI Business Trends 2025
Google's AI Business Trends 2025 report identifies five transformative trends: multimodal AI, AI agents, assistive search, AI-powered customer experience, and security with AI. These trends are driving market growth and innovation, enhancing integration of diverse data, automating business workflows, improving information discovery, personalizing customer interactions, and strengthening security practices.
Deloitte: The Cognitive Leap – How to Reimagine Work with AI Agents
The white paper advocates for using multiagent AI systems to transform business processes through scalable, human-in-the-loop designs, supported by industry examples and a detailed implementation framework.
IBM: The CEO's Guide to Generative AI – 2nd Edition
IBM's report offers CEOs a concise guide to leveraging generative AI for transforming their businesses. It highlights strategies for digital innovation, IT automation, ethical AI implementation, and talent management, emphasizing a human-centered approach and strategic investment to maximize benefits while managing risks.
World Economic Forum: 2025 Future of Jobs Report
The report outlines how macrotrends like technological change, the green transition, geoeconomic shifts, economic uncertainty, and demographic changes will reshape global labor markets by 2030, emphasizing significant job growth alongside a critical need for extensive reskilling and upskilling to bridge emerging skills gaps.
MIT Technology Review: A Playbook for Crafting AI Strategy
The report highlights strong AI ambitions among executives but notes progress is often limited to pilots due to high costs, data quality, and regulatory challenges. It offers strategic guidance for building a robust data foundation, choosing vendors, and measuring ROI to successfully scale AI initiatives.
IST: Implications of AI in Cybersecurity – Shifting the Offense-Defense Balance
The report examines how artificial intelligence is transforming cybersecurity by enhancing both attack and defense strategies, highlighting challenges like deepfakes and polymorphic malware while advocating for balanced integration and human oversight.
George Mason University: Artificial Intelligence Policy Framework for Institutions
The paper proposes an ethical AI policy framework for institutions that focuses on data privacy, bias mitigation, energy efficiency, and the importance of interpretability to build trust, illustrated through case studies in various sectors including education and healthcare.
IBM: Enterprise AI Development – Obstacles and Opportunities
A survey of 1,063 US enterprise AI developers revealed significant skills gaps—especially in generative AI—and challenges from a lack of standardized processes and trusted, easy-to-integrate tools, with ongoing concerns about AI agents’ trustworthiness and compliance.
O'Reilly: Technology Trends for 2025
The report analyzes O'Reilly's usage data to predict that in 2025, AI and its associated skills will drive major trends, with a shift in software development focus toward AI integration, increased attention to security, and new platform features like badging and a generative AI Q&A tool.
About Agentic AI Blog
Insights on agentic AI, from agent architectures and LLM infrastructure to enterprise deployment and developer tooling. Our team shares practical guides on building AI agents, optimizing model pipelines, and scaling AI systems in production.
Written for CTOs, developers, AI engineers, and technical leaders who are building or deploying agentic AI. Each article includes actionable takeaways grounded in real-world implementation.
Our editorial team publishes new content weekly, drawing on deployment data from 400+ organizations and 1.6M+ users. Every piece is reviewed by practitioners with hands-on experience building AI platforms.