The latest articles on DEV Community by Heelo (@heelodev). https://dev.to/heelodev https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4200743%2F293af69f-ca5f-4d57-b0a4-bd7696f06c6c.png https://dev.to/heelodev en Heelo Fri, 23 Oct 2026 03:39:05 +0000 https://dev.to/heelodev/why-tool-execution-is-still-hard-for-ai-agents-41pe https://dev.to/heelodev/why-tool-execution-is-still-hard-for-ai-agents-41pe <p>AI agents are getting better at understanding instructions, generating plans, and reasoning through complex problems.</p> <p>But planning a task and actually completing it are two very different things.</p> <p>For example, consider this simple request:</p> <p><strong>"Schedule a meeting for Friday afternoon and send a confirmation email."</strong></p> <p>It sounds straightforward. But for an AI agent, this involves multiple steps, different tools, and several possible failure points.</p> <h2> 1. Tool Integration Is Harder Than It Looks </h2> <p>Different services expose different APIs, authentication methods, parameters, and response formats.</p> <p>An agent may know what the user wants but still struggle to interact with the right tools.</p> <p>A consistent execution interface could help reduce this complexity.</p> <h2> 2. Multi-Step Workflows Introduce New Problems </h2> <p>Many real-world tasks require more than one action.</p> <p>Creating a calendar event might involve checking availability, confirming details, and calling an external calendar API.</p> <p>What happens if one step succeeds but the next one fails?</p> <p>How should the agent recover without repeating actions that have already been completed?</p> <h2> 3. Reliability Matters </h2> <p>Giving an agent permission to execute tasks creates new responsibilities.</p> <p>Developers need to consider:</p> <ul> <li>API failures and timeouts</li> <li>Missing information</li> <li>Duplicate actions</li> <li>Authentication errors</li> <li>User confirmation before important actions</li> <li>Whether the final result matches the user's original intent</li> </ul> <p>A successful API response doesn't always mean a task was completed correctly.</p> <h2> 4. What We're Building at HEELO </h2> <p>At <strong>HEELO</strong>, we're building an execution layer for AI agents.</p> <p>Our goal is to make it easier for AI systems to interact with real-world tools and manage multi-step operations through a more consistent interface.</p> <p>Our development work focuses on tool integration, execution workflows, clarification handling, error management, and testing.</p> <p>We're still actively developing and validating these capabilities, and reliability is one of our central priorities.</p> <h2> 5. From Talking to Doing </h2> <p>The next generation of AI shouldn't just generate better answers.</p> <p>It should also help turn those answers into useful, dependable actions.</p> <p>That's the direction we're exploring at HEELO.</p> <p><strong>From talking to doing. 🚀</strong></p> <p>We're curious: What's been your biggest challenge when building tool-using AI agents?</p> <p>Learn more about HEELO: <a href="https://heelo.dev" rel="noopener noreferrer">https://heelo.dev</a></p> agents ai llm