How to Onboard an AI Agent for Your Engineering Team

Since the launch of ChatGPT, the AI world has been buzzing with innovation. This year, it’s all about AI agents—those digital teammates that can take on repetitive tasks, giving you back precious time to focus on the work that truly matters.

At Scout, we’ve been asking ourselves: how can AI make life easier for our engineers? Startups often come with unique challenges, especially for engineers who juggle multiple roles. One day, you’re fine-tuning deployment pipelines; the next, you’re troubleshooting infrastructure issues or answering a teammate’s urgent question.

And here’s where the problem lies. Even in an open and collaborative team, constant interruptions can disrupt a productive engineer’s day, leading to fragmented work and slower progress. That’s where our two Slack agents—Teach AI and Ask AI—come in.

These agents are designed to do more than just answer FAQs; they’re actively learning, evolving, and helping us bridge gaps in knowledge while improving our engineering teams productivity. Employing these two agentic workflows allows teams to easily build internal knowledge bases with the help of AI.

Luckily for you, we’ve done the hard work and created two templates for these agents that can be easily added to your workspace on Scout and deployed via Slack. In this blog, we’ll look at how these agents have helped us reduce interruptions and speed up progress. The result? Engineers can focus on high-impact tasks without sacrificing team collaboration or support.

Teach - AI

This agent integrates directly with our “Teach AI” Slack channel. Engineers use this channel to document their ongoing projects and share best practices, creating a centralized knowledge repository. By doing so, the AI continually learns from real-world applications, evolving to provide increasingly accurate and context-aware assistance.

The Teach AI workflow behind the scenes is actually rather simple and straightforward. When a user submits a message in Slack, it’s processed through an LLM to generate a concise document title. The content is then routed through one of Scout’s “Save Blocks” to store it in the internal knowledge base. Finally, a follow-up LLM block notifies the user, confirming the information has been saved and providing the generated document title for reference.

Ask - AI

The “Ask AI” Slack channel acts as your first point of contact for troubleshooting, quick guidance, and even answering more complex questions.

Instead of interrupting another engineer for guidance, team members can now turn to the “Ask AI” channel. There, they’ll find detailed, step-by-step instructions tailored to resolve issues quickly. These aren’t generic answers; the AI taps into the Teach AI repository to provide context-specific solutions that evolve as your team’s knowledge grows.

One of our senior developers put it best: “This has not only saved me a huge amount of time but has also reduced the mental load associated with re-contextualizing after each interruption. The number of daily interruptions has dramatically decreased, allowing me to focus more on solving new problems and driving our projects forward. This solution has proven invaluable in maintaining my productivity and well-being, while still ensuring that my colleagues can efficiently resolve their issues.”

The Results: A Collaborative, AI-Enhanced Team

The synergy between Teach AI and Ask AI has been transformative for Scout’s engineering team. We’ve seen a significant reduction in interruptions. On average, some of our senior engineers can spend up to 2 hours a day providing support or helping to unblock fellow team members. By empowering engineers to access accurate, actionable insights without breaking their flow, these agents have paved the way for a more productive and collaborative environment. Freeing up on average 8-10 hours a week from the senior engineers allowing them to focus on driving projects forward.

Beyond productivity, this approach fosters a culture of shared knowledge and continuous improvement. As engineers contribute to the Teach AI channel, they’re not only documenting solutions for today but also building a resource that benefits the entire team long-term. It’s a win-win: senior engineers can focus on innovation, and junior developers have the tools they need to grow and succeed.

This also addresses the challenge of “siloed” information. In many teams, a few key folks become the go-to experts, holding much of the critical knowledge. But what happens when one of them leaves? Historically, that expertise would leave with them. Now, thanks to our internal knowledge base, those insights are captured and preserved, ensuring they remain accessible to everyone.

Democratization of Knowledge

The same principle applies to onboarding new hires. Starting a new role often comes with a steep learning curve, and some people may hesitate to ask for help. The Ask AI channel removes that barrier, giving new team members a judgment-free way to get answers. With AI as their first point of contact, they can learn and adapt quickly without fear of asking “dumb” questions.

Now you may be saying, "Wait a minute," if theres a workspace channel where people are asking questions, can't other team members just look at whats being asked? Yes, yes they can. However, you can also slide into Ask AI's DMs! This allows users to ask questions privately, ensuring no hesitation over how the question might be perceived by others. It’s a safe space for learning without fear of judgment.

Not Just for Dev Teams

The impact of these agents extends far beyond the development team. While engineers were the primary focus during implementation of these agents, other departments like QA teams, product managers, and even customer support have quickly seen the value in using Teach AI and Ask AI.

For QA teams, having access to a centralized knowledge base means faster debugging and streamlined testing processes. They can quickly find context-specific information without needing to wait for a developer to clarify details, reducing bottlenecks and improving turnaround times.

Product managers, on the other hand, benefit from a clearer understanding of the technical nuances behind features. They can use the Ask AI channel to explore workflows or review past decisions documented in the Teach AI repository. This not only helps them make more informed decisions but also bridges the gap between technical and non-technical teams.

Even customer support teams can leverage these tools to find accurate responses to technical inquiries without escalating every issue to engineering. By democratizing access to knowledge, these workflows foster cross-team collaboration and empower every team member to work more effectively.

Getting Started with Teach AI and Ask AI

If you’re ready to transform your Slack workspace, Scout’s Teach AI and Ask AI templates make it easy to get started. If you’re looking to build an internal knowledge base with AI, these two are a must.

With Teach-AI and Ask-AI added to Scout's template library getting started is a breeze. Sign up for free today on Scout and explore our template library with dozens of prebuilt workflows ready to run.

To start with Teach-AI and Ask-AI simply head over to workflow templates found at the top of the workflows page, navigate to the operations tab and add these two workflows to your workspace.

For a more comprehensive how-to, visit our Slack Bot deployment guide.

With just a few clicks, you can integrate Scout's Teach AI and Ask AI into your team’s daily routine. Whether you’re a small startup or a growing enterprise, don’t let knowledge gaps or interruptions slow your team down, these tools can scale with your needs, ensuring that AI works for you—not the other way around.