Building the Right Team for Agentic Products
At MarutAI, companies and hiring managers frequently ask us how they should approach building their teams to design, deploy, and manage sophisticated agentic-infused products. Unlike traditional software or even single model/LLM solutions, agentic systems require a much different approach. They are collections of specialized, purposeful programs designed to collaboratively solve problems and research objectives, they demand a fundamentally different approach to architecture and development.
In this blog, we'll dive deeper into why an agentic products require distinct skillsets and personalities, and how to structure your team to build an effective, adaptive "society of agents."
Why Build Agentic Products at All?
Let’s briefly talk about why you’d consider an agent-based approach in the first place. Enterprises today face complex, dynamic challenges that exceed the capacity of single-purpose AI models or the deterministic logic typically embedded in traditional software. Often, business tasks require multiple steps performed autonomously—though not necessarily the same steps every single time. Agentic systems naturally excel in these scenarios because they consist of multiple purposeful agents interacting, collaborating, negotiating, and sometimes even competing to achieve the best possible results.
Each agent within this ecosystem can specialize deeply, operate independently, and communicate thoughtfully with other agents. This collaborative and distributed approach closely mirrors human teamwork, offering greater resilience, flexibility, and scalability compared to standalone AI solutions. However, the inherent complexity of these systems means the team you assemble to build and maintain your agentic ecosystem requires careful thought and strategic hiring decisions.
Understanding an Agentic Society
A big upfront caveat: Agents, much like any LLM-based approach, are inherently stochastic—not deterministic. You can set clear guardrails, provide detailed instructions, and define expectations, but you can never truly predict exactly what they'll output every time.
An agentic ecosystem isn’t simply a collection of chatbots or digital assistants. While traditional assistants passively await requests, agents proactively engage, negotiate, delegate, and dynamically adapt their behavior based on context. Agents form their own society, complete with specialized roles, communication patterns, and even implicit hierarchies. Within this ecosystem, you might find user-facing agents handling interactions, data-gathering scouts searching for valuable information, analytical reasoners interpreting complex data, or compliance agents ensuring regulatory adherence—all working together toward common organizational objectives.
Consider this analogy: Much like societies have laws to guide and constrain expected behavior, agentic systems rely on rigorous testing and validation practices with deterministic outcomes. These practices help to establish norms, reinforce guardrails, and keep agent interactions consistently aligned with their intended purpose.
Just as you thoughtfully consider culture, personalities, and complementary skillsets when assembling human teams, your approach to building teams for managing agentic ecosystems deserves equal attention. If your team's skills or temperament don't align with the demands of managing a complex agent-based system, the resulting mismatch can lead to inefficiencies, dysfunction, or even significant system failures.
Essential Skills and Roles in Building Effective Agents
To create and nurture this ecosystem effectively, your human team needs people with distinct skillsets, each corresponding to the needs of agentic design, operation, and management.
The Architect – Strategic Visionary:
This person holds the big-picture vision. They deeply understand your business strategy and can translate complex organizational objectives into clear, purposeful interactions among agents. Great architects don't just understand the potential of AI or technical system architectures; they grasp the nuances of organizational dynamics, clearly seeing how each agent’s role impacts the overall ecosystem.
But remember, the answer to every question isn't always “solve it with AI.” Many challenges businesses face can (and should) be addressed through traditional methods like heuristics, algorithms, or thoughtful development practices. AI models and agentic systems are powerful tools meant to enhance and augment your business outcomes—not to define them entirely.
Operations Specialist – The Systems Expert:
Keeping multiple intelligent agents running smoothly requires expertise in patience, monitoring, orchestration, and rapid deployment/re-deployment. This team member manages performance, health checks, incident response, and continuous integration, ensuring your agentic society remains stable and resilient. Agents need constant attention to get consistent results, the longer they run, they more they have to think about during conversations.
Interaction Designer – Humanizing AI:
Agents are fundamentally social—they interact not just with people, but also with other agents, data sources, and external partners. An ideal interaction designer knows exactly how to craft experiences that feel natural, intuitive, and trustworthy. Because agents rely on large language models (LLMs) to interpret and generate responses, interaction designers must be highly skilled at designing clear, effective prompts. This skill is critical at every level of ecosystem interaction. It’s important to note that prompt effectiveness varies significantly between different underlying models—especially between commercial and open-source options. An excellent designer recognizes these nuances, tailoring interactions and language carefully to match the specific LLM's interpretation capabilities.
Security & Compliance Lead – Keeper of Trust:
Agentic systems often handle sensitive information, operate autonomously, and make critical decisions without direct human oversight. This autonomy makes them particularly powerful—but also introduces significant risks. A dedicated security and compliance specialist ensures these agents operate safely, ethically, and transparently, building and maintaining trust with users and stakeholders. Think of the guardrails, access controls, and audit processes applied to your agents similarly to how you would grant data access privileges to human employees: thoughtfully, deliberately, and always guided by privacy, security, and compliance standards.
Data Strategist – The Information Architect:
Agents are data-driven entities. They live or die by the quality, structure, and availability of information. This team member manages your data strategy, ensuring each agent accesses reliable data streams, continuously updates outputs based on learned outcomes, and makes intelligent decisions about how much is too much or too little for the agent objectives.
Agent Behavior Specialist – AI’s Coach:
Agents, much like people, can sometimes act in unexpected ways. A dedicated behavior specialist closely monitors, shapes, and refines the agents' learning and behavior over time. Their role involves training agents on ethical principles and establishing clear behavioral norms, continuously refining their performance. Practically, this work can take various forms: from carefully curating datasets for agent fine-tuning to analyzing individual agent interactions—examining the supervisor prompt, the agent’s system prompt, and the user’s input to understand precisely why an agent responded in a particular manner, and determining whether this response genuinely advances the intended conversation or business goal. You might think of this role as similar to a psychologist assessing the health and effectiveness of human interactions, ensuring your agentic ecosystem operates in a balanced, effective, and responsible manner.
Personalities for Agentic Success
Beyond technical skills, building effective agentic ecosystems requires individuals who are innately curious and adaptive, comfortable learning, experimenting, and evolving as these systems dynamically change. Equally critical is having collaborative communicators who understand that agents operate collectively, navigating complex interactions and facilitating clear dialogue across diverse roles. Successful teams include strategic thinkers who naturally consider the downstream impacts of agent interactions, roles, and rules, and who excel at anticipating future scenarios.
Many different backgrounds can contribute to success in building agentic products. Effective teams often include individuals from diverse experiences—product management, psychology, user experience design, data science, computer science, marketing, and even anthropology. Each perspective adds depth to your team’s understanding of agent interactions, behaviors, and outcomes, ultimately enriching the overall design and functionality of your agentic ecosystem.
An Example of an Ideal Small Agentic Team
Below is an example of how you might structure position descriptions when assembling an effective small team for agentic products:
AI Architect
Description:
Responsible for designing and overseeing the overall agentic system, ensuring alignment between business objectives and AI interactions. Leads the strategy for how agents collaborate and coordinate within the ecosystem.
Skills:
Systems architecture and design
AI strategy and integration
Process analysis and optimization
Domain Knowledge:
Enterprise operations, strategic business planning, AI methodologies, and ecosystems thinking.
AI Operations Specialist
Description:
Ensures reliability, scalability, and stability of the agent ecosystem. Manages deployment, continuous monitoring, performance tuning, and rapid response to operational incidents.
Skills:
MLOps/AIOps frameworks and tooling
Monitoring, logging, and alerting
Cloud orchestration and infrastructure management
Domain Knowledge:
Cloud platforms (AWS, Azure, GCP), operational risk management, system reliability, and infrastructure scaling.
Interaction Designer
Description:
Designs intuitive and effective interactions between agents, users, and other system components. Crafts clear, impactful prompts tailored specifically to underlying LLMs.
Skills:
Conversational UX/UI design
Prompt engineering for LLMs
User-centric design principles
Domain Knowledge:
Human-computer interaction, usability principles, language modeling nuances, and behavioral psychology.
Security and Compliance Lead
Description:
Oversees the secure and compliant operation of agentic systems. Implements appropriate guardrails, data governance practices, and compliance monitoring to ensure safe interactions and data handling.
Skills:
Cybersecurity best practices
Regulatory compliance (GDPR, HIPAA, SOC 2)
Risk assessment and auditing
Domain Knowledge:
Data privacy, cybersecurity frameworks, regulatory environments, ethical AI standards.
Agent Behavior Specialist
Description:
Monitors, assesses, and improves agent behavior and interactions. Curates datasets, analyzes agent responses, and fine-tunes agent models to ensure effectiveness, alignment, and ethical decision-making.
Skills:
Dataset curation and management
Model fine-tuning and evaluation
Model construction
Behavioral analytics
Domain Knowledge:
Machine learning techniques, psychology of interactions, ethical AI considerations, reinforcement learning, and iterative model improvement.
Putting It All Together: Hiring Strategically
As a business leader, the choices you make about hiring profoundly influence the success of your agentic-based systems, far more than simpler features like chatbots or digital assistants. Agentic products aren’t just tools; they're complex ecosystems of autonomous intelligent entities interacting dynamically, requiring thoughtful design, management, and continuous oversight.
Focusing solely on technical abilities without considering strategic vision, interpersonal dynamics, or personality fit risks creating fragmented, ineffective, or even problematic behaviors within your agent society. When building your team, think carefully about the blend of skills, mindsets, and personalities each candidate brings. You're not merely hiring technicians; you're assembling a group of people who deeply understand that they're creating and nurturing a community of intelligent agenets.
This means looking beyond traditional tech hiring criteria. Seek out team members who inherently grasp the nuances of building agentic systems—individuals who can anticipate complex interactions, manage emergent behaviors, and adapt quickly when surprises occur. Ultimately, the strength and coherence of your agentic ecosystem will reflect the thoughtfulness and strategic intent behind your hiring decisions.