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According to Gartner, 95% of what's being promoted as "AI agents" aren't actually agents at all.We're experiencing what Jordan Wilson from Everyday AI podcast brilliantly calls the "overagentification of everything." (E582)If you're not totally sure about what makes an AI Agent read our previous post <a data-mce-href="https://destrain.ai/blog/what-is-an-ai-agent--the-definition" href="https://destrain.ai/blog/what-is-an-ai-agent--the-definition">What Is an AI Agent? The Definition</a> <h2>The great mislabeling</h2>Simply put, companies are slapping the word "agent" on anything that even touches an LLM. As Wilson points out: "Much of the market hype misuses the term 'agent'. Anything with LLM isn't agent, agentic or even meaningful AI."But why does this matter to your business?Because this confusion is creating a massive gap between what businesses think they're buying and what they're actually getting.<h2>What people are asking for</h2>Here's a fascinating insight from Daniel Whitenack, CEO of Prediction, from the Practical AI podcast (E352): "Every time I've actually asked people about what they want with their AI agent, it turns out what they want is either RAG chatbot or automated workflow."<blockquote>If I had asked people what they wanted, they would have said faster horses.</blockquote>Think about that. Many businesses can't even imagine yet what agents are capable of. They're missing out on these dynamic assistants and turning instead to incremental upgrades: slightly smarter chatbots accessing company knowledge or predefined automated workflows with a sprinkle of increased capabilities compared to what was done 10 years ago already.They are valuable tools. They improve efficiency. They save time. A little bit.Agent's transform whole processes.<h2>The hidden cost of confusion</h2>This mislabeling isn't harmless marketing fluff. When companies label their LLM wrappers "agents" their customers think that "this is it". At the same time they dillute the real possibilities of the actual dynamic agentic shift. They become disillusioned with AI's actual potential. They fall behind competitors who understand the difference.What does this mean for your business? You might be settling for a chatbot when you could have a digital colleague. You might be buying into the 95% when you should be looking for the 5%.<h2>Why We're Writing This</h2>At Des Train AI, it's crucial that our customers know exactly what they're buying. We've had directors from large companies come to us stating that "Agents are nothing, they will never work". That smells like something a person disappointed with something sold to them as "agent". We can show they work, I'm running multiple agents as we speak.When we say "AI agent," we mean systems that dynamically figure out how to solve problems using the existing tools and complementing the persons doing the work. Not because it sounds impressive, but because that's the technology that actually transforms businesses. Setting the right expectations upfront means you get the transformation you're investing in, not another disappointment dressed up in AI buzzwords.<h2>How to Spot the Real Thing</h2>Here's your quick test. Ask your vendor: "Does this system decide HOW to accomplish tasks, or does it follow predetermined steps?"If they start talking about workflows, templates, or configurations you're probably looking at the 95%, not the 5%.Real agents don't need you to spell out every step. They figure out how to achieve the outcome you want. That's the transformative difference.<h2>The Path Forward</h2>Our mission is to complement people’s work with AI agents that help amplify the businesses they build.Why? Because when businesses understand what real AI agents can do: dynamically solving problems, taking ownership of processes, adapting their approach based on context, it changes everything.The technology for genuine AI agents exists today. One of the challenges is cutting through the "overagentification" to find it.Ready to join the 5% using real AI agents? <a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact">Contact</a> us to see the difference.

Almost Everything Called an "AI Agent" Isn't

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An AI agent is a system where AI dynamically directs its own processes and tool usage, maintaining control over how it accomplishes tasks.Anthropic's definition above captures it pretty well. And this is a question I get a lot.That word "dynamically" is everything. It's the difference between following a recipe and being a chef. It separates the agent from chatbots and copilots by enabling autonomy and action.<h2>The Core Difference </h2>Not an Agent: You ask a chatbot to summarize the quarterly sales and it prints them to your screen. When you ask it to send it to your collague, it apologises for not being able to do that.Not an Agent: You tell a agentic process the steps it needs to take in order to analyze quarterly sales data. It fetches them according to your instructions, does the defined analysis and sends them where you have defined. You ask it to compare it with previous quarter and it freezes.Real Agent: You ask an AI agent to analyze sales data. It decides which data sources to examine, what timeframes matter, which metrics to compare, identifies anomalies you didn't ask about, and determines the best way to present its findings. It asks you for more detailed information and digs deeper into insights that interest you. When you see something it missed, you ask it to improve and it will.<blockquote>You tell it what you want to achieve, not how to achieve it.</blockquote>One needs instructions. The other figures it out.One is a one trick pony. The other solves varying problems using varying tools and data sources.One gives out what it wants. The other complements the user's expertise.That's it. That's what makes something an AI agent. You tell it what you want to achieve, not how to achieve it. (You need to give it enough guidance of course. And the tools, you need to hand in the tools. It's never that simple.)<h2>What This Looks Like in Practice </h2>Think of it like asking someone to get coffee. You don't need to say "walk to the kitchen, grab a mug from the cupboard, pour coffee in the mug..." You just say "bring me some coffee" and they figure out the steps. Add "two sugars", and they disgruntly return to the kitchen, but they know what it means.That's exactly how AI agents work. When you tell an agent "analyse the status of this shipment," you don't spell out every step. The agent reasons what is an shipment, where to get it's data, what checks are relevant and what needs to be done for different statuses. It might ask you clarifying questions or need instructions to improve the end result - but that's why you're there, you're the expert afterall. You're not the expert in reading a spreadsheet. Instead your an expert on understanding what is relevant of the information on the spreadsheet. Agents put the user's expertice is in the focus.What does this mean for your business? Increasingly flexible process supporting tools complementing employees exprtise. Using the same tools, spreadsheets, instructions and database as always. Internal and external data sources and tools. You're not programming workflows anymore. You're delegating outcomes.<h2>The Outcome</h2>Software that needs instructions saves time. Software that figures things out supercharges productivity.At Des Train AI, we focus on genuine AI agents for real business processes. The kind that dynamically control their own processes to achieve your goals. The kind that actually figure things out. Using your existing tools and infrastructure. Complementing your team's expertise.Is your business ready for AI that doesn't just assist but actually does?Ready to see what real AI agents can accomplish? <a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact">Contact us</a> to explore the possibilities.---Jonas Pomoell is the founder and AI business consultant at Des Train AI Oy, specializing in deploying transformative generative AI solutions. With deep expertise in AI-driven business automation, Jonas helps companies unlock productivity and growth through advanced, practical AI agent implementations. &nbsp;

What Is an AI Agent? The Definition

AI agents are revolutionizing busines processes and supercharging teams in their daily work. They don't only assist but actually get things done by reasoning and performing actions using the same everyday tools people are using in their work. For this they need the USB-C of integrations, the Model Context Protocol or MCP. [Read more on that from our previous blog on <a data-mce-href="https://destrain.ai/blog/how-do-ai-agents-actually-do-things" href="https://destrain.ai/blog/how-do-ai-agents-actually-do-things" title="How do AI Agents actually do things?" data-mce-selected="inline-boundary">How do AI Agents actually do things?]﻿</a>This Model Context Protocol revolution is changing everything about business tool integration. Tools that were never on your "integration radar" are suddenly becoming critical for AI agent workflows. Error tracking systems, project management platforms, communication tools and services you've always accessed manually are now expected to work seamlessly with AI agents.But here's what might surprise businesses starting to deploy AI agents: many modern, everyday tools still lack the comprehensive programmatic access that agents prefer. No API. No CLI. No filesystem access. And certainly no MCP integration. It's not a blocker but a speed bump.This isn't just about what tools you use anymore. It's about a fundamental shift and it's happening on two fronts:<ol><li>are your everyday tools ready for the MCP world</li><li>are the services you provide prepared for customers who expect MCP compatibility?</li></ol><h2>The Two-Sided MCP Reality</h2>This transformation is hitting businesses from both directions:As a tool consumer: Are your everyday SaaS business tools easily integratable with AI agents? Can your agents actually work with your error tracking, project management, analytics, and communication platforms? Or will you need complex automation workarounds for tools that should offer direct access?As a service provider: Are your services ready for customers who expect MCP integration? When your clients start deploying AI agents, will your platform be the one that "just works" or the one that requires expensive workarounds?The businesses recognizing both sides of this shift are the ones preparing for competitive advantage.<h2>The Great Tool Migration</h2>Take Google Firebase Crashlytics – used to manage millions of mobile apps daily, yet lacking API and CLI access for the basic operations that AI agents need to perform. And that is just one of the tools that feel thoroughly modern still operate with limited programmatic access. This pattern might be more common than many businesses initially realize.This is creating rapid market pressure, especially for tools where switching costs are low and alternatives exist.We're entering a period where integration capability will drive tool selection like never before. In SaaS categories where options are plentyful and switching costs are reasonable – error tracking, project management, analytics platforms, communication tools – the pressure to offer proper programmatic access is intensifying rapidly.Why? Because when your competitor's AI agents can seamlessly work with their entire tool stack while yours require manual intervention or complex automation, the productivity gap becomes unmistakable.At Des Train AI, we're expecting this pattern to accelerate. Companies evaluating new tools now ask about MCP compatibility upfront. Existing tools without proper API access are getting replaced, especially in categories where migration is straightforward.<h2>If switching is easy it should be done</h2>Everything can be integrated with AI agents – that's not the question. The question is efficiency and competitive timing.When switching costs are high (legacy enterprise systems, specialized industry software, deeply embedded workflows), building computer use automation for MCP use makes perfect sense. These integrations are worth the complexity.But when switching costs are low? When modern alternatives with native MCP support exist? When the tool is used frequently by agents? The calculation changes completely.This is should be rapid change in easily-switchable tool categories. And the tools that don't adapt quickly are losing customers to competitors who understand the new integration reality.And especially if you provide any tools, services or interfaces online including portals and websites - even for consumers. For a service provide&nbsp;the shift represents both risk and massive opportunity.The risk: Your internal processes, customers and partners will start expecting AI agent compatibility. If your platform requires complex workarounds while competitors offer direct integration, you'll lose to "the one that just works with our agents."The opportunity: Being MCP-ready positions you as the forward-thinking choice. When prospects are evaluating tools for their AI-enabled workflows, comprehensive integration support becomes a decisive factor.Companies doing their MCP implementation now will have competitive advantages over those waiting to see how the market develops.<h2>The change is silent</h2>This isn't a distant future consideration. AI agents are being deployed today, and their integration requirements are driving tool selection decisions right now.The question isn't whether MCP compatibility will matter. It's whether you make the right choices right now, both internally and with the broad spectrum of services you provide externally.The AI agent revolution is incremental and is happening within the everyday business processes. There will be no press releases of the agent deployments from your competitors. You'll know when you see them pass you due to their increased efficiency and quality it's already too late. But what if you could be the one on the driver's seat?Ready to evaluate both sides of your MCP readiness? The companies moving fastest are auditing their tool integration gaps while simultaneously planning their service integration capabilities. <a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact" title="Contact us">Contact us</a> to develop a strategy that addresses both your tool consumption and service provision in the MCP-enabled future.Interested to discuss more? <a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact" title="Contact">Book a meeting!</a>--- Jonas Pomoell is the founder and lead AI business consultant at Des Train AI Oy, specializing in deploying transformative generative AI solutions. With deep expertise in Model Context Protocol implementation and business tool integration strategy, Jonas helps companies navigate both the consumption and provision sides of the AI agent integration revolution.[The cover image taken 19.8.2025, real life questionnaire for paying users from widely used tranlsation and localization platform <a data-mce-href="https://phrase.com/" href="https://phrase.com/" title="Phrase">Phrase</a>]

Your tools need AI access. Your customers expect it too.

Business people analyze data and big data technology Two businessmen calculate business analysis and display images of complex data sets on a computer on the screen. artificial intelligence

AI agents are here – but how do they actually do things?Everyone’s talking about AI agents. But here's the real question: How do they actually access information and take action?Businesses today rely on countless digital tools—from calendars and email platforms to customer management systems and e-commerce applications. Typically, integrating new AI capabilities into these tools involves significant technical effort, ongoing updates, and substantial maintenance.But what if AI agents could seamlessly interact with these existing tools, without continuous updates or complex integrations?Enter the Model Context Protocol (MCP). Think of MCP as a lightweight, intelligent layer placed neatly on top of the systems your business already uses. Rather than recreating your current infrastructure, MCP enables AI agents to directly and effortlessly utilize your existing tools.<h2>Here's how it works in practical terms:</h2>Flexible Inputs: If an Agent can imagine it, the integration layer can consume it. Instead of making integrations that open up specific predefined reports from the reporting database, why not run reporting queries that the agent formulates for you based on your query. “Hey Agent, can you visualize last month's first-time purchaser’s ticket value” and continue with “Ok, now cross-reference those with our marketing campaign results”. Agent formulates the queries and chews up the results for you. But it’s not limited to those queries, ask whatever you like.Automatic Discovery: When your business integrates a new tool—like a CRM system or a marketing analytics platform—the MCP automatically broadcasts the new capabilities. AI agents immediately recognize these additions and autonomously start utilizing them. This means no downtime, no updates required for the agents, and no extra burden on your IT department.Flexible Integration: MCP uses a simple yet powerful format (JSON) already familiar to your technology teams. This ensures quick, straightforward, and low-cost integration.Future-Proofed Industry Standard: The recent announcement by OpenAI endorsing MCP as an industry standard highlights its significance. MCP, managed by Anthropic, ensures your investment today remains relevant tomorrow. It took less than 6 months from publication of the Protocol to be adopted by players such as Sharepoint, DropBox, and HubSpot. For example, imagine your business has recently integrated a new customer feedback system. Traditionally, making this feedback accessible to AI-driven analytics would involve extensive integration and manual configuration. With MCP, the moment this system becomes part of your infrastructure, AI agents automatically discover and start using the feedback data to enhance customer insights—immediately, seamlessly, and without requiring any additional configuration.<h3>What is the impact?</h3>For decision-makers, this means faster deployments, reduced costs, and greater agility in responding to market demands.In essence, MCP makes your business smarter: not by reinventing your tools, but by seamlessly enhancing how AI can utilize what you already have. AI agents won't replace your team but instead supercharge your people, empowering them with extraordinary capabilities to achieve more, faster by getting AI to work as their sidekick.Ready to see MCP in action and unlock your business’s full potential? <a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact">Contact us</a> today to start your journey.---The writer, Jonas Pomoell, is the founder and lead consultant at Des Train AI Oy, helping businesses harness the full potential of generative AI. Specializing in practical, transformative AI agent implementations, Jonas guides companies in streamlining processes, boosting productivity, and driving growth with tailored, advanced AI solutions.

How do AI Agents actually do things?

The way people interact with technology is about to change and as everything in AI age the change is going to be ultra fast. Traditional menus, forms, and buttons are being replaced by something far more natural: language. Natural language interfaces are not just a UX trend but they represent a structural shift driven by both user demand (ease of use) and compelling cost-efficiency (ease of build). For businesses, the direction is clear: adopting natural language interfaces is a strategic move that’s quickly becoming the default.A natural language interface allows people to interact with systems by simply speaking or typing using everyday language. And I'm not talking about chatbots. It’s a broader transformation that is is influencing every kind of digital service, every user interface and tool.<h2>Why now?</h2>The shift has been made possible by the rapid advancement of large language models (LLMs). These models don’t just “understand” human language better but, especially when coupled with agentic approach, can actively guide the user, handle ambiguity, and adapt to the context.<h2>Why it matters</h2>Natural language interfaces offer five key advantages over traditional user interfaces:<h3>Cost-efficient to build</h3>A simple text input or speech recognition field can replace complex forms or multi-step flows, reducing development and maintenance costs. A single user interface can also serve many different tasks, making it versatile and reducing the number of tools needed.<h3>No learning curve</h3>If you can speak or write, you can use the interface. There’s no need to learn how the system works as it adapts to you. Never has the world had so accessible system that "if you can speak you can use it".User tells it in their own words. And can add an image or video that extends the context. No more confusion or misunderstandings.<h3>Self-guided by design</h3>If something is missing or unclear, the interface can ask follow-up questions in real-time guiding the user naturally through the process. No need to create manuals or helps, the user interface IS the manual.<h3>Built for problem-solving</h3>Because the system understands intent and context, it can go beyond basic commands and help the user find actual solutions. The system can provide suggestions or options for the user. For example does the user want to make a purchase, receive an written offer or that a sales person calls to discuss the details?<h3>Hyper-personalized</h3>By combining user input with background data, these interfaces can tailor responses precisely to the situation and individual. This is one of the key drivers behind the whole transformation. It is not enough to provide a link, or a generic response. It's not even enough to provide the generic description. Users expect to get the solution tailored exactly to their needs.<h2>What does this mean for your business?</h2>Natural language interfaces make digital services more accessible, human-centered, and efficient. It’s a paradigm shift in how humans and machines collaborate.Curious about how this could benefit your organization? <a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact">Let’s talk.</a> We help businesses explore, design, and implement AI-driven natural language solutions tailored to their real-world needs.---Jonas Pomoell is the founder and lead AI business consultant at Des Train AI Oy, specializing in deploying transformative generative AI solutions. With deep expertise in AI-driven business automation, Jonas helps companies unlock productivity and growth through advanced, practical AI agent implementations.

Natural Language transforms User Interfaces

Document, Digitization, Digital Display, Organization, Data,
Digitization, Automated, Work Tool, Cloud Computing, Enterprise Resource Planning,Ai,
Artificial Intelligence

Artificial intelligence (AI) is everywhere, yet many businesses haven’t fully heard about or understood one of its most powerful tools: AI agents. But what exactly is an AI agent – and why should you care?Simply put, an AI agent is a generative AI actor capable of independently automating tasks. Instead of passively waiting for individual instructions, an AI agent proactively plans, reasons the necessary steps, and autonomously manages complete processes. For example:"Classify this customer support email, assess its trustworthiness, reply according to our customer service guidelines, and forward critical issues immediately to the relevant department."The AI agent independently plans its tasks: it identifies necessary information, evaluates and categorizes the content, generates responses using established company protocols, and manages required follow-up actions. It achieves all this seamlessly by leveraging existing tools and interfaces. It can ask for more details or pass the case to customer service person.Why does this matter? Because AI agents represent the next generation of business automation powered by generative AI technology. They function as digital employees capable of transforming customer service, sales, competitor analysis, and administrative workflows – all around the clock, empowering human teams to focus on strategic work.At Des Train AI, we build and deploy generative AI agents, experiencing firsthand their impact in increasing efficiency, reducing response times, and driving growth. This technology isn’t futuristic. It's a opportunity businesses are leveraging today.Is your company ready to harness the transformative power of generative AI agents?<a data-mce-href="https://destrain.ai/contact" href="https://destrain.ai/contact">Contact us</a> and book a meeting to discover how AI automation can accelerate your business growth today!---Jonas Pomoell is the founder and lead AI business consultant at Des Train AI Oy, specializing in deploying transformative generative AI solutions. With deep expertise in AI-driven business automation, Jonas helps companies unlock productivity and growth through advanced, practical AI agent implementations.

Blog

Almost Everything Called an "AI Agent" Isn't

What Is an AI Agent? The Definition

Your tools need AI access. Your customers expect it too.

How do AI Agents actually do things?

Natural Language transforms User Interfaces

What is an AI Agent – and Why Does It Matter?