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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.
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Building, deploying, and managing autonomous AI agents for workflow automation, customer support, internal operations, and more.
LLM InfrastructureModel selection, hosting, fine-tuning, cost optimization, and scaling LLM-powered systems in production.
Enterprise AIStrategies for deploying AI at scale across organizations, including governance, compliance, and change management.
Developer ToolsMCP servers, CLIs, SDKs, APIs, and open source tooling for building on agentic AI platforms.
IndustryAI applications across education, healthcare, finance, government, and other verticals.
ConferencesTranscripts and key takeaways from major education and AI conferences including ASU+GSV Summit.
Showing 889-912 of 928 posts
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.
U.S. Congressional Budget Office: AI and Its Potential Effects on the Economy and the Federal Budget
The report examines how artificial intelligence could boost economic growth and transform federal revenues and spending, while also highlighting uncertainties about its impacts on employment, wages, and the timing and scale of these effects.
Australian Government: Voluntary AI Safety Standard
The Australian Government’s Voluntary AI Safety Standard outlines ten guardrails for implementing safe and responsible AI practices, focusing on aspects like accountability, risk management, and transparency in line with ethical and international standards.
NVIDIA: Cosmos World Foundation Model Platform for Physical AI
NVIDIA's Cosmos World Foundation Model platform for Physical AI uses a dual-stage training approach with diffusion and autoregressive models on a massive curated video dataset to create versatile foundation models that are fine-tuned for robotic manipulation, autonomous driving, and other tasks, featuring a novel video tokenizer and integrated safety measures.
University of Chicago: Agentic Systems – A Guide to Transforming Industries with Vertical AI Agents
The content explains agentic systems—industry-specific AI agents powered by large language models—that offer real-time adaptability, domain expertise, and complete workflow automation through components like memory, reasoning engines, and cognitive modules.
Google: Agents – Architecture, Tools, and Applications
Generative AI agents extend language models by using external tools and orchestrated reasoning frameworks like ReAct and Chain-of-Thought, with practical implementations shown through examples such as LangChain and Vertex AI.
Swiss Business School: AI's Impact on Critical Thinking
The study finds that frequent use of AI tools is negatively associated with critical thinking skills, suggesting that while AI has benefits, there is a need for educational strategies to counteract cognitive offloading and maintain robust critical thinking abilities.
World Economic Forum: Navigating the AI Frontier – A Primer on the Evolution and Impact of AI Agents
This white paper examines the evolution of AI agents—from simple rule-based systems to advanced models capable of complex decision-making—and discusses their benefits, risks, and the critical need for robust ethical and governance frameworks to manage their growing role in society.
UNESCO: Guidance for Generative AI in Education and Research
UNESCO's guidance outlines ethical and responsible use of generative AI in education and research, addressing potential biases, copyright issues, and digital inequalities, while recommending human-centered strategies and regulatory measures for its integration and competency development.