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Tech Transformed

EM360Tech
Tech Transformed
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  • Are Your Field Teams Disaster Ready and Safe?
    Takeaways#Satellitecommunications are essential for remote field teams.They provide safety and tracking for workers in isolated areas.Disaster preparedness involves proactive planning and communication.User-friendly #technology is crucial for effective utilisation.Reliable communication impacts day-to-day operations positively.Employers show care for employee safety through #satellitetechnology investment.SummaryIn this episode of #TechTransformed, Jonathan Care discusses the importance of satellite communications for field teams. He is joined by Mark O'Connell, EMEA & Asia Pacific General Manager at Globalstar, and Grace Finn, Senior Account Manager at Peoplesafe. Together, they explore how satellite technology enhances safety, disaster preparedness, and operational efficiency for remote, lone workers.We learn the differences between satellite and cell communication. O’Connell emphasises the importance of satellite communication, stating that due to field workers, there is a requirement to not be reliant on cellphone towers.O’Connell further clarifies that field teams who are working remotely, and are away from terrestrial communications, need access to constant communication.Finn also expresses the importance of field worker safety, sharing: “If the unforeseen does happen, they’re protected.” She emphasises that organisations should invest in satellite communications to ensure their teams' wellbeing and security.Tune in to learn the user-friendly aspects of the technology, its features for challenging environments, and the critical role it plays in ensuring reliable communication.For the latest tech insights visit: EM360Tech.com
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  • How Do AI and Observability Redefine Application Performance?
    "Having the insight and being able to stitch together your technical resources and business decisions together, is the prime place where observability can add value to you,” stated Manesh Tailor, EMEA Field CTO at New Relic.In this episode of the Tech Transformed podcast, Kevin Petrie, Vice President of Research at BARC, speaks with Manesh Tailor about the intersection of artificial intelligence (AI) and observability, and how this is positively changing business operations.Tailor emphasises how intelligent observability has changed beyond simple monitoring to provide real-time insights into customer experience and the entire technology stack. This enables informed decisions across engineering, operations, and business domains, directly linking technical performance to strategic business outcomes.He also discusses the different stages observability has been through and where it's leading to now. The current wave, Observability 3.0, takes advantage of AI to predict issues and even enable self-healing systems. New Relic has embraced this two-way street, using AI within its platform. This was in an ambition to help users and "AI monitoring" to track the performance of language models alongside traditional metrics. Such a platform provides a holistic view of system health and the cost implications of AI deployments.Alluding to the management of AI-powered applications, Tailor says collaboration is key between application and data science teams. Not only does it provide real time data but as a result leads to efficient decision making.Futuristically, the speedy proliferation of AI agents has both pros and cons for observability. This is where New Relic comes in. It addresses the challenges by constructing a platform-centric "AI orchestrator" with a growing library of AI-native agents. In essence, as AI-powered applications become increasingly integral to business operations, intelligent observability is no longer optional. TakeawaysObservability is crucial for understanding unknowns in systems.AI enhances observability by providing predictive insights.The evolution of observability includes intelligent monitoring.Collaboration between technical and business teams is essential.Cost efficiency is a key focus in modern observability.Real-time data is vital for effective decision-making.Self-healing systems represent the future of observability.AI and observability must work in tandem for success.The complexity of systems is increasing, requiring better tools.Observability is applicable across all organizational levels.Chapters00:00 Introduction to AI and Observability03:10 Defining Observability and Its Evolution05:49 The Role of AI in Observability08:46 Navigating AI-Driven Applications11:52 Target Users and Community for Observability14:57 Collaboration Across Teams17:55 Challenges and Opportunities in Observability20:47 The Future of Observability and AI23:54 Key Takeaways for CIOs and IT LeadersAbout New RelicThe New Relic Intelligent Observability Platform empowers businesses to proactively eliminate disruptions in their digital experiences. As the only AI-enhanced platform that unifies and correlates telemetry data, New...
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  • AI Agents: The Rise of the Autonomous
    Takeaways#AIagents are #autonomous entities that can perceive and act.Human oversight is essential in the initial stages of AI implementation.Data quality and trust are critical for effective AI agents.Guardrails must be integrated into the design of AI agents.Modularity in design allows for flexibility and adaptability.#AI should be embedded in data management processes.Collaboration between data and application teams is vital.SummaryIn this episode of #TechTransformed, Kevin Petrie, VP of Research at BARC, and Ann Maya, EMEA CTO at Boomi, discuss the transformative potential of AI agents and intelligent automation in business. They explore the definition of agents, their role in automating processes, and the importance of human oversight. Maya introduces us into the world of AI agents stating that, at its core, it’s an autonomous entity within #AIsystems that can perceive its environment. This creates a deep dive into how they evolved from traditional automation to “observe, think, and act” in novel and autonomous ways.Maya addresses AI skepticism by acknowledging its growing autonomy while underscoring the current necessity of human oversight. She also highlights data's crucial influence on an agent's perception and decisions, emphasising the need for quality, trustworthy data in effective AI. Moreover, Maya and Petrie explore AI's practical implications, pointing to Google's agent-to-agent protocol as vital for managing language model interactions and enabling effective communication across diverse agents within complex systems.For the latest tech insights visit: EM360Tech.com
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  • How AI Agents Are Changing Enterprise Cloud Development
    "If AI has proven anything, it will change pretty rapidly. Understanding its limitations and not asking too much of it is significant. What’s successful is prototyping tools," said Rob Whiteley, CEO of Coder. "Such tools where AI can create an application, while not the world's most graceful code but will get you to working prototype pretty quickly. That would probably take me days or weeks of research as a developer, but now I have a working prototype so I can socialise it."In this episode of the Tech Transformed podcast, Dana Gardner, a thought leader, speaks with Rob Whiteley, CEO of Coder, about the transformative impact of agentic AI on software development. They discuss how AI is changing the roles of developers, the cultural shifts required in development teams, and the integration of AI agents in cloud development environments.Agentic AI is seemingly set up for favourable outcomes. Or is it? Agentic AI is believed to shake-up enterprise IT, offering a productivity boost similar to the iPhone's impact. This isn't about replacing developers but amplifying their output tenfold. It aims to allow the implementation of rapidly created solutions and iteration that has been unimaginable in the past. This shift requires valuing "soft skills" like communication and collaboration over pure coding proficiency, as developers guide AI "pair programmers."The synergy of AI agents, human intellect, and Cloud Development Environments (CDEs) is key. CDEs provide secure, governed, and scalable platforms for this collaboration, allowing developers to focus on business logic and innovation while AI handles the coding groundwork. This requires a move from rigid "gates" in development processes to flexible "guardrails" within CDEs. Such a move fosters innovation with built-in control and security.Flexibility and choice are vital in this constantly advancing AI space. CDEs enable organisations to select the best AI agents for specific tasks, avoiding vendor lock-in by expressing the development environment as code. This leads to practical applications like faster prototyping, enhanced code development, and automated testing, significantly boosting code output. Furthermore, agentic AI democratises development, empowering non-engineers to build solutions.Preparing for this future requires proactive experimentation through AI labs, engaging early adopters, and viewing AI as an augmentation of human skills. Watch the podcast for more insights on CDEs and the impact of AI agents on enterprise cloud development. TakeawaysAgentic AI is a transformative technology for software development.The role of developers is shifting from hard skills to soft skills.AI agents can significantly increase productivity in coding tasks.Organizations need to rethink their development strategies to integrate AI.Cloud development environments are essential for safely using AI agents.Choosing the right AI agent is crucial for effective development.Security and governance are critical when integrating AI into development.AI can empower non-developers to create applications.Guardrails are more effective than gates in managing AI development.Organisations should experiment with AI to find the best fit for their needs.Chapters00:00 Introduction to Agentic AI and Developer Roles03:20 Transformative Impact of AI on Development06:50 Cultural Shifts in Development Teams10:30 Integrating AI Agents in Cloud Development Environments12:49 Choosing the Right AI Agents15:21 Security and Governance in AI...
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  • Customer Success: Your Revenue Compass in the AI Storm
    Takeaways#Customersuccess is about helping customers get value from products.The perception of customer success is shifting from a cost centre to a revenue generator.#AI can enhance customer success by providing predictive insights and automating processes.Customer success teams are uniquely positioned to identify upsell and cross-sell opportunities.Collaboration between customer success and sales teams is essential for maximising revenue.The integration of AI tools can streamline customer success operations.SummaryEver wonder how to transform existing customers into your company’s most powerful growth engine? According to Gainsight’s Chief Revenue Officer, Marilee Bear, it starts with one deceptively simple principle: “helping customers get value from your product.” This #TechTransformed episode features Christina Stathopoulos, Founder of Dare to Data, in conversation with Marilee about the dynamic role of customer success – a powerful avenue for building deeper customer bonds, boosting retention rates, and ultimately achieving significant revenue gains.Tune in to learn how to unlock the potential of customer success as a catalyst for cross-selling and upselling opportunities. Explore how to equip your customer success teams with commercial acumen and harness their potential as a secret weapon for business growth.Whether you're a #CRO looking to optimise revenue or a business leader navigating the AI revolution, this episode offers invaluable insights into the future of customer success.For the latest tech insights visit: EM360Tech.com
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