8090 Solutions Inc.’s Post

Let’s not add AI for the sake of AI. Let’s prioritize user needs, not the technology. https://lnkd.in/gZKCbkCH

https://lnkd.in/etxfJqpc AI agents are emerging as a new class of users, independently navigating the interfaces we design and performing complex tasks on our behalf. This marks the beginning of a new era of interaction, the Agent-Computer Interaction, where user experience encompasses not only human-computer relationship, but also the experiences of the AI agents.

In this UX Magazine article, discover how deploying a Conversational AI platform, like Amelia, allows businesses to unlock the full potential of Large Language Models for enterprise-grade use cases: https://hubs.li/Q02G5Yvc0

Legacy companies integrating an AI chatbot into their product… Many companies are eager to brand themselves as "AI-driven," but sometimes it feels like adding a chatbot is just a shortcut to appearing cutting-edge. While a genuine AI integration can truly enhance UX and productivity, simply layering AI on top of outdated systems often leads to confusion, inefficiency, and, yes, some entertainingly off-base responses. The true value of AI lies in its thoughtful application, making complex processes seamless and user-centric. For #AI to be more than a checkbox, companies need to ensure it’s woven deeply into their strategy, not just as an add-on. Join this AI Discussion Group on Telegram: https://t.me/hashtag_ai

Very forward looking perspective around agentic systems. We need traditional management capabilities to provide feedback and oversight into the process. We are likely to see agents operating like workers and teams to accomplish higher order tasks. We will need specialization and feedback to manage the limitations of AI.

My question is, How do we build up and maintain such feedback loops? How can we incentivize every stakeholder in the loop to give us constant feedback? Once we have trustworthy, authentic feedback data regularly, then how to use the data will be another question. First, we need to have the data. How can we do that? #Evaluation #AIUXR

This is spot on. This is why Qualiti has spent the last year building a system focused on putting human engineers in control. AI is capable of incredible things and doing most of the work for us, but, in their current and near-term state, only frameworks that fully manage agentic autonomy correctly, keeping human oversight in key places, can actually unlock the full power of these tools.

Beyond the tech: Ethan Mollick's insight aligns perfectly with what I’ve been calling 'Delegation 2.0' - we're not just managing AI, we're developing a new generation of leaders who can blend human wisdom with AI capabilities. Current UX focuses on technical control, but misses the critical need for interfaces that support strategic vision and ethical decision-making. #AIManagement #FutureOfWork #Delegation2.0 #CogsToCaptains

A gap in the work of the AI labs is that they don’t seem to see the next phase of AI as about management: how do we verify & control the work of flawed semi-autonomous AI agents. Current UX designs for agents are all about autonomy or else are highly technical. We need to focus on feedback loops & check-ins for the managers that actually will be able to best use these systems.

Exactly, but management has two components: Ensure trust in today's work and build trust that tomorrow's will be better. We don't just need verify and control, we also need to teach. As you would with any newly hired assistant on their way to a highly contributing team member. That's why any intelligent application needs to be capable of learning. As Ethan Mollick points out, we need a new paradigm for UX to support MLVPs (https://lnkd.in/dSE4u8du): Intelligent products that can be supervised and that will improve towards increasing autonomy over time, like a real assistant.