Tag: AI Agents

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Microsoft “App Builder” & “Workflow” Agents

Microsoft is expanding its Copilot Frontier Programme with two powerful new agents. These are the App Builder and Workflows Agents.

These put “app creation” and automation directly into the hands of everyday users, with zero coding needed just an idea and an ask. These new agents are designed to further democratise innovation across every person in every organisations, making it possible to build “apps” and streamline processes using nothing more than natural language.

They are rolling out in the US now and will come to UK, Canada and the other regions over the next week or so.

I’ll add a demo to this blog soon!

What are the App Builder and Workflows Agents?

Firstly, these are new, in preview for Frontier (early adopters) and may change. They are not designed to replace Power Apps or Copilot Studio but more about adding value to info workers and non developers. Here is the new agents, which you can get by going to the main Copilot page, agents and get more agents.

App Builder: A no-code agent that enables anyone to design and deploy lightweight apps in minutes. It can generate a Microsoft Lists backend if needed and is grounded in Microsoft 365 content like Word, Excel, and Teams.  These are not full blown apps that can hook into enterprise data or anything but create simple to use, functional and simple agents for things like data input, collection and look up.

Image (c) Microsoft

Workflows: An automation agent that turns everyday requests into flows across Outlook, Teams, SharePoint, Planner, and more – without needing Power Automate expertise. Again these are quite simple, but great for simple automation needs when you know what you want to do but don’t have time or want to learn / use Power Automate.

Image (c) Microsoft

Both these new agents are integrated into the Copilot Studio lite experience, ensuring they inherit Microsoft 365’s enterprise-grade security, compliance, and governance. 

How Do They Work?

These agents work like other agents but are specific functional agents. They work by:

  • Using Natural Language Prompts: users can simply describe what they need. For example “Build me a dashboard to track campaign milestones” or “Send a Teams reminder every Friday at 3pm” – and Copilot translates that into a working app or automated flow. 
  • Multi-turn Editing: Once the agent is created it can be modified, updated, refined with additional interactions without having to starting from scratch. 
  • Ensuring Seamless Integration: Outputs are instantly shareable, just like a document link, and respect existing permissions and governance.

These agents lower the barrier to innovation and help spur on what is possible. Instead of relying on IT or developers, any employee can now build tools that fit their needs whether that’s a lightweight app for tracking, or a workflow that eliminates repetitive admin. Since they are built into Microsoft 365, they inherit the same security, compliance, and governance as the rest of the platform. 

App Builder Use examples

  • Create a product launch dashboard to track milestones and assign tasks. 
  • Build a calculator app for quick cost estimates, grounded in Excel data. 
  • Generate interactive lists for project tracking, with Microsoft Lists as the backend.

Workflows agent use examples

  • Automate weekly Teams updates with deadlines pulled from Planner. 
  • Set up email reminders for approval deadlines. 
  • Manage calendar scheduling by automatically blocking time for recurring tasks. 

Current Limitations

  • Frontier Programme Only: Currently limited to participants in the Copilot Frontier Programme and need to be “deployed by IT admin” initially
  • Language Support: Available in English only. 
  • Controls: Access depends on Microsoft 365 app store settings and admin policies. 
  • Governance & Permissions: Agents respect existing role-based access controls. 
  • Scope: Aimed at designing lightweight apps and workflows; complex scenarios will still require Copilot Studio or Power Platform. 
  • Performance Throttling: Heavy usage may trigger throttling.  


Deploying the App Agent and Workflow Agent

These new agents are currently only available for organisations enrolled in the Copilot “Frontier Programme”.To access the agent, you need to go to the M365 Copilot app (or https://m365.cloud.microsoft/chat) and go to Agents. From there you should be able to see the new Agents as shown below.

NOTE: If you can’t see these new agents, you’ll need to chat to your friendly IT team as they may need to enable / deploy these agents whilst they are still in preview state. Again these are only available for organisations enrolled in the Copilot “Frontier Programme”.

Final Thoughts

The App Builder and Workflows agents represents another step forward in Microsoft’s vision of empowering everyone to innovate with AI.

Whilst these agents are far from a replacement for full-scale development or automation platforms, they provide a fast, accessible way to solve everyday problems. For organisations in the Copilot Frontier Programme, these agents are a glimpse into a future where building apps and automations is as easy as describing what you want.

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The Future of AI Agents and shift to Agentic AI

Image of Satya Nadella

In a recent podcast episode with Bill Gurley and Brad Gerstner, Satya Nadella – CEO of Microsoft, discussed a wide range of topics related to his role at Microsoft, the state of the technology, business growth and capitalism in this new “AI Era”.

The podcast which you can watch on YouTube here covered some interesting topics including the Future of AI Agents and their potential to transform how we interact with technology. In this blog (worth a listen), Satya gives his predications/insights into the future of AI Agents and emphasises that AI agents will fundamentally change the landscape of software-as-a-service (SaaS) solutions, predicting that the traditional notion of business applications will collapse in the era of agentic AI.

What is Agentic AI?

Agentic AI refers to artificial intelligence systems that can make decisions and take actions autonomously, without direct human intervention. These systems are designed to perceive their environment, reason about the best course of action, and execute tasks independently. In short these agents are designed to function as workplace teammates, capable of handling various tasks across different applications.

As example, in e-commerce platforms, instead of static, rule based chatbots, agentic AI-driven systems can track a customer’s journey, personalised recommendations, and assist with returns seamlessly without user / supervisor input. These agents will be able to actively learn from interactions, optimising the customer journey in real time and learning about user preferences.

Agentic AI typically inhibits the following features:

  • Autonomy: Agentic AI systems can operate independently, making decisions based on input data and predefined goals.
  • Adaptability: These systems can adapt to changing circumstances and inputs, adjusting their actions to achieve their objectives.
  • Proactivity: Agentic AI can anticipate user needs and take actions without explicit instructions, making them more proactive in their behavior.
  • Collaboration: In the future, agentic AI systems will be able to work together in multi-agent networks, collaborating to handle complex tasks that a single agent cannot manage alone.

Changes Ahead for AI Agents

The video / podcast is an hour and a half (but an enjoyable and informative listen). Reading between the sections, Satya talks extensively about where he sees AI Agents evolving massively through 2025. I have summarised this below.

Increasing Sophistication and Capabilities

AI agents will become increasingly sophisticated and capable, eventually replacing traditional software applications. These agents will be able to understand and anticipate user needs, providing personalised and proactive assistance. They will leverage advanced natural language processing (NLP) and machine learning algorithms to interact with users in a more human-like manner.

Autonomous AI Agents

Through 2025. we will see autonomous AI agents handle more and more complex tasks with minimal human oversight, optimising workflows and enhancing efficiency across industries. These agents will streamline workflows, manage intricate operations, and simplify everyday activities. For example, OpenAI’s “Operator Agents” will autonomously execute multi-step processes, such as scheduling meetings or managing projects.

Multi-Agent Networks

Sayta talks abiut the “future” being a place that is not about singular agents but more about networks or systems of agents where agents can discover and collaborate with other agents. These multi-agent networks will enable agents to handle tasks that they can’t do themselves by invoking other agents (agents talking to other agents). This collaborative approach will enhance the overall capabilities and efficiency of AI agents.

Vertical AI Agents

Vertical AI agents, which are specialised for specific industries, are expected to have their moment in 2025. These agents will dominate their respective fields by offering tailored solutions that address industry-specific challenges. For example, retail AI agents will act as personal shoppers, offering personalised recommendations and optimising inventory management.

Persistent Memory and Personalisation

AI systems with persistent memory will enable highly personalized interactions, transforming AI into long-term companions that adapt to user preferences and habits. This capability will allow AI agents to provide more relevant and context-aware assistance, enhancing user experiences.

Emotional Intelligence

Future AI agents are expected to possess emotional intelligence, allowing them to understand and respond to human emotions. This will enable more empathetic and effective interactions, particularly in customer service and healthcare settings.

Integration with IoT and Personal Devices

AI agents will increasingly integrate with the Internet of Things (IoT) and personal devices. This integration will enable seamless interactions across various platforms and devices, creating a more connected and efficient ecosystem. For example, AI agents in smart homes will manage household tasks, monitor energy usage, and provide personalized recommendations.

Ethical AI and Transparency

As AI agents become more prevalent, there will be a greater emphasis on ethical AI and transparency in decision-making. Ensuring that AI agents operate responsibly and transparently will be crucial for gaining user trust and acceptance. This includes addressing issues related to data privacy, bias, and accountability.

Proactive AI Agents

Proactive AI agents will anticipate user needs and take actions without explicit instructions. For example, an AI assistant might reorganize your day based on traffic updates and weather, reschedule missed appointments, and even draft personalized messages. This proactive approach will make AI agents more valuable and indispensable in daily life.

Enhanced Communication and Collaboration Tools

AI agents will enhance communication and collaboration tools, making it easier for teams to work together. These agents will facilitate real-time collaboration, manage project timelines, and provide insights to improve productivity. They will also assist in content creation, research, and workflow automation.

Shift and the of SaaS apps?

Another interesting section to listen too is at around 31 minutes, where Satya talks about his vision of how AI agents could potentially replace traditional SaaS (Software as a Service) applications. Whilst something that will not happen over night, he talked about the shift from business apps with connectors into other apps, but in an agent to agent and agent to back-end system.

We can already have connectors into applications like SAP, Dynamics etc. A great quote he used was “when was the last time any of us really went to a business application” In the AI age, we access the data in these systems from a mesh of data sources which over time, these back-end SaaS systems would eventually become obsolete as AI agents take over multi-repository CRUD (Create, Read, Update, Delete) operations. This shift would lead to the collapse of conventional business applications, with AI agents handling the core logic.

The idea will be that you simply pull information from systems through AI Agents such as looking up customer details, updating inventories, changing a contact in NetSuite CRM for example or checking delivery status for an order.

Other examples, Sayta talked about with regards AI Agents included:

Infinite Memory: He explained that infinite memory refers to the ability of AI agents to retain and recall information over extended periods, much like a human’s long-term memory. This capability will allows AI agents to build on past interactions and experiences, making them more effective and personalized in their responses and actions.

Proactive Task Management: AI agents are envisioned to operate autonomously, handling complex tasks such as processing customer returns, managing shipping invoices, and optimizing supply chain operations. This proactive approach reduces the reliance on user-initiated interactions, further diminishing the need for traditional SaaS applications.

Automation of Business Logic: Satya explained that AI agents would be able to automate many backend business processes, creating a new tier of multi-agent orchestration. This means that business logic, which is currently hardcoded into individual applications, will be managed by AI agents across multiple apps or databases and will adapt based on useage and need.

Integration with Existing Tools: Nadella highlighted the integration of Python with Excel as an example. AI agents can use Excel’s visualisation capabilities for advanced tasks, transforming it into a more intelligent and autonomous tool. This integration demonstrates how AI agents can enhance existing applications, making them more efficient and reducing the need for traditional SaaS apps.

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