Techstrong.ai

Some of the biggest AI risks won’t show up in dashboards. Futurist and Hugo Award–winning author David Brin joins 𝗔𝗜 𝗡𝗮𝘁𝗶𝘃𝗲𝗗𝗲𝘃 to explore accountability, transparency, and long-term responsibility as AI-native systems scale across industries. Make time for this conversation during RSAC. 📍 March 23 at RSAC 🎟️ Included with RSAC badge 🔗 https://buff.ly/W3pcXDb #AINativeDev #RSAC #FutureOfAI #AILeadership

The question is no longer if AI writes code. It’s whether security keeps pace. 𝗔𝗜 𝗡𝗮𝘁𝗶𝘃𝗲𝗗𝗲𝘃 dives into how AI-generated code reshapes governance, architecture, and security expectations. This full-day forum is built for teams navigating faster development without sacrificing trust. 📍 March 23 at RSAC 🎟️ Included with RSAC badge 🔗 https://buff.ly/W3pcXDb #AINativeDev #RSAC #SecureDevelopment #AIEngineering

Pilot success is only the beginning of enterprise transformation. Early agent deployments often deliver strong results. The real challenge emerges when organizations attempt to replicate those wins across business units, security frameworks, and cost structures. Microsoft’s Richard Riley explains that moving from isolated success to enterprise impact requires more than technical validation. Security and governance must scale with the agent footprint. Cost models must be understood and managed. Strategic focus must replace experimentation overload. Organizations that succeed treat agent adoption as a structured progression. They establish governance early, align initiatives to measurable business outcomes, and expand deliberately across functions. Read the full article to understand how to move from pilot projects to enterprise transformation: https://buff.ly/6FOlTd2 Then explore how Microsoft Power Platform supports secure and scalable agent deployment: https://buff.ly/SXoW67G #EnterpriseTransformation #DigitalTransformation #PowerPlatform #AI

What if an AI could combine the strategic reasoning of an LLM with the deep, stateful computation of a specialized engine? The Chronosynaptic-Gemini hybrid architecture achieves this. allowing agents to act as research assistants, exploring topics ranging from CRISPR to quantum physics and beyond. Learn about the architecture powering this next step in AI-assisted discovery: https://buff.ly/RfdYcTL #MachineLearning #Innovation #DeepTech

In network operations, treating probabilistic GenAI and deterministic automation as interchangeable is a high-risk mistake. GenAI excels at synthesizing unstructured data for investigation, while deterministic automation is essential for precise, repeatable changes. Forcing GenAI to execute actions creates unpredictable failure modes and audit nightmares, undermining stability and security. Learn how to strategically apply each approach by reading our full framework: https://buff.ly/gCFAIBd #NetworkAutomation #GenAI #RPA

The era of "vibe working" has arrived. Anthropic just launched Claude Opus 4.6, and it’s no longer just a chatbot—it’s a coworker. Learn more 👉 https://buff.ly/nKVRNqi #Anthropic #Claude #AI #AgenticAI

Are organizations struggling to adopt AI? A global survey of 505 data and analytics professionals identifies technological infrastructure and skills as top barriers. Learn more 👉 https://buff.ly/sKOwF3F #AI #AIAdoption #IT #Survey

Explore why the four largest U.S. tech giants are forecasting a record-breaking $650B in capital expenditure for 2026. From massive data centers to GDP-altering investments, see how the AI arms race is reshaping the global economy and testing investor patience. 🔗 https://buff.ly/GCHXPgg #AI #Spending #BigTech #Investment

In the rush to deploy AI, transparency is often the first casualty. True explainability and fairness are impossible without a clear, auditable view of the data journey from origin to model input. Governance is no longer just a compliance task; it is the essential framework that makes AI systems auditable, improvable, and ultimately, trustworthy. Consider how governance evolves from a checklist to a cornerstone of intelligent operations. Read the full perspective here: https://lnkd.in/edFBntua #DataGovernance #ResponsibleAI #Transparency

Traditional monitoring dashboards are failing in the age of multi-model AI. When every service uses a different LLM, silent degradation, cost explosions, and cascade failures become invisible to conventional metrics. The shift from one model to many is unplanned and inevitable, leaving teams blind to issues that only users notice. Explore the essential metrics and 4-week plan for monitoring a multi-model AI environment. Read the full article: https://buff.ly/XcshFPf #AIOps #Observability #LLM