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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 841-864 of 985 posts
LEGO/The Alan Turing Institute: Understanding GenAI Impact on Children
A new study reveals how children aged 8–12 are already using tools like ChatGPT, highlighting benefits, risks, and the urgent need for child-centred AI design and literacy.
OpenAI: Disrupting Malicious Uses of AI - June 2025
OpenAI’s latest threat-intelligence report reveals how ten malicious operations—from deep-fake influence campaigns to AI-generated cyber-espionage tools—were detected and dismantled, turning AI against the actors who tried to exploit it.
Oakland University: The Memory Paradox
Oakland University’s latest paper warns that offloading too much thinking to digital tools can erode human memory systems, arguing for education that strengthens internal knowledge even while embracing AI.
Pearson: Asking to Learn
Pearson’s analysis of 128,000 student queries to an AI study tool uncovers a surprising share of higher-order questions—evidence that thoughtful AI integration can push learners beyond rote memorization.
Apple: The Illusion of Thinking
Apple’s new study shows that Large Reasoning Models excel only up to a point—then abruptly collapse—revealing surprising limits in algorithmic rigor and problem-solving stamina.
OpenAI: A Practical Guide to Building Agents
OpenAI’s new guide demystifies how to design, orchestrate, and safeguard LLM-powered agents capable of executing complex, multi-step workflows.
Vanderbilt: The AI Labor Playbook
Vanderbilt University’s new playbook re-imagines generative AI as a scalable labor force—measured in tokens and led by humans—rather than a software product to simply buy and deploy.
OpenAI: AI in the Enterprise
OpenAI’s latest paper distills insights from seven frontier companies, showing how an iterative, security-first approach to AI can boost workforce performance, automate routine tasks, and power smarter products.
Microsoft: Shifting Work Patterns with GenAI
A six-month field experiment with 7,000+ workers shows Microsoft 365 Copilot slashing email time but leaving meetings—and broader workflows—largely unchanged.
Springer Nature: Why AI Won't Democratize Education
Springer Nature’s new paper argues that commercial AI tutors fall short of John Dewey’s vision of democratic education, and calls for publicly guided AI that augments teachers and fosters collaboration.
McKinsey: Open Source in Age of AI
McKinsey’s latest report uncovers why more than half of tech leaders are turning to open source AI for performance and cost advantages—while grappling with cybersecurity, compliance, and IP concerns.
BCG: AI Agents, and Model Context Protocol
BCG’s new report tracks the rise of increasingly autonomous AI agents, spotlighting Anthropic’s Model Context Protocol (MCP) as a game-changer for reliability, security, and real-world adoption.
Securing Agentic AI: Insights from Google & AWS
A joint Google–AWS report explains how the Agent-to-Agent (A2A) protocol and the MAESTRO threat-modeling framework can harden multi-agent AI systems against spoofing, replay attacks, and other emerging risks.
Stanford University: Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data
Short-term educational technology log data (2–5 hours of use) can effectively predict long-term student outcomes, showing similar performance to models using full-period data. Key features like success rates and average attempts per problem are strong predictors, especially at performance extremes, and combining these log features with pre-assessment scores further enhances prediction accuracy.
World Bank Group: From Chalkboard to Chatbots – Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria
A World Bank working paper finds that using a GPT-4-powered virtual tutor in Nigerian secondary schools significantly boosts English, digital, and AI skills, with stronger gains for higher-performing, female, and higher socioeconomic students. The intervention proved highly cost-effective, equating to 1.5–2 years of traditional schooling and suggesting that scalable AI tutoring can enhance learning in low-resource settings, provided challenges like digital equity are addressed.
OpenAI: Multi-Agent Portfolio Collaboration with OpenAI Agents SDK
A multi-agent system built with the OpenAI Agents SDK delegates investment analysis tasks to specialized agents coordinated by a central Portfolio Manager, ensuring modular, scalable, and transparent research.
Bond: Trends - Artificial Intelligence 2025
Bond’s latest AI trends report reveals record-breaking adoption, surging infrastructure investment, and intensifying global competition that will reshape how people work, build, and come online.
AI Agents Governance Report: Autonomy Passport Framework
The Center for AI Policy’s latest report outlines the promise and peril of autonomous AI agents and proposes concrete congressional actions—like an Autonomy Passport—to keep innovation safe and human-centric.
Mary Meeker: Trends - Artificial Intelligence 2025
The report highlights AI's unprecedented growth in adoption and infrastructure investment, marked by rapidly falling inference costs, fierce global competition (especially between the USA and China), and significant integration into both digital and physical sectors that is reshaping work and economic landscapes.
AI Policy Brief: Governing Agent Autonomy in Digital Age
The report outlines the rapid shift of AI agents from research to deployment, emphasizing their autonomous, goal-directed capabilities along a five-level spectrum. It identifies three primary risks—catastrophic misuse, gradual human disempowerment, and extensive workforce displacement—and recommends policies such as an Autonomy Passport, continuous oversight, mandatory human control over high-stakes decisions, and annual workforce impact studies to ensure safe and beneficial integration of these agents.
North-West University: Exploring AI-Driven Conversations as Dynamic OER for Self-Directed Learners
The paper proposes that AI-powered conversations, like those from ChatGPT, can serve as dynamic and personalized open educational resources to support self-directed learning, while highlighting challenges such as ethical concerns and the need for proper teacher training and infrastructure.
Software Bill of Materials (SBOM) for the ibl.ai Platform
SBOM, software bill of materials, generative AI platform, LLM-agnostic, LangChain, Langfuse, Flowise, OpenAI GPT-4, Google Gemini, Azure OpenAI, Anthropic Claude, AWS Bedrock, open-source LMS, OpenAPI, Python SDK, JavaScript SDK, OAuth2, OIDC, SAML, LTI 1.3, ReactJS, Next.js, React Native, ibl.ai, university CIO, edtech, AI tutor, permissive licenses, vendor lock-in avoidance, cost control, enterprise security, higher education technology
Comparing ibl.ai to Firebase Studio for Universities
ibl.ai gives universities an off-the-shelf, cloud-agnostic AI platform with instant LMS-embedded tutors, content generators, analytics and full data ownership, enabling rapid, faculty-supported rollouts proven at peer institutions. In contrast, Firebase Studio is a generic, Google-dependent preview tool that leaves schools to code and maintain every education workflow themselves, exposing them to higher long-term costs, vendor lock-in and technical debt that ibl.ai’s pay-per-API model avoids.
How ibl.ai Scales Faculty & User Support
ibl.ai scales effortlessly across entire campuses by using LTI 1.3 Advantage to deliver one-click SSO, carry role information, and sync rosters and grades through the Names & Roles (NRPS) and Assignment & Grade Services (AGS) extensions—so thousands of students drop straight into their AI tutor without new accounts while every data flow remains FERPA-aligned. An API-driven ingestion pipeline then chunks faculty materials into vector embeddings and serves them via Retrieval-Augmented Generation (RAG), while multi-tenant RBAC consoles and usage dashboards give IT teams fine-grained policy toggles, cost controls, and real-time insight—all built on open-source frameworks that keep the platform model-agnostic and future-proof.