Don't Fear the Agents

In the rush to leverage the popularity of AI, the market has quickly become crowded with AI software. Terms like LLM, workflow, and agents (or agentic) are being used interchangeably, but the reality is, these are fundamentally different, and mistaking one for the other can sink your AI deployment process by adding additional overhead, maintenance, and people to manage. 

Let’s dig deep to understand the real difference between whether a platform is leveraging an LLM, a workflow builder, a true agentic approach, or some combination of the three. 

Let’s talk about LLMs

LLMs are general purpose reasoning machines that have been trained on massive amounts of text. At their core, they are prediction engines. They generate the next best word or token based on the input they receive from the user. 

What they’re good at: 

• Interpreting natural language
• Generating coherent responses
• Reasoning across text
• Acting as copilots to guide you “where to next”

They don’t:

• Natively know context unless explicitly stated
• Remember state across tasks and conversations unless specifically built that way
• Take action on their own without user input

LLMs are like a good consultant: very good at taking requests, analyzing the request and making an effort to align output to a request. They generally won’t take the extra step of doing the work unless prompted. 

Workflows: The process automation darlings

Workflows are predefined, rule based sequences of logic. These sequences can usually be repeated by a scheduling tool or platform. These exist to visually represent steps in a process, usually a flow-type interface with branching “if this then that” steps. 

Examples: 

• Salesforce flows
• Zapier or n8n drag and drop process builders
• Clay table automation
• Marketo nurture campaigns
  

What they’re good at: 

• Predictable results once built
• Non technical user friendly
• Easy for anyone to step through and understand the process
• Audit trails and version control

They don’t 

• Provide general dynamic flexibility
• Fix themselves or redo logic based on flaws
• Adapt to nuance or context changes

One thing to note: Just because a workflow builder includes the ability to prompt for specific steps to be built a certain way, does NOT mean your workflow builder is agentic. 

Agents bring it together

Agents are autonomous entities that act in pursuit of goals, powered by reasoning, memory, context and sometimes LLMs. 

What they’re good at: 

• Perceiving the environment (input state)
• Plan next steps through reasoning
• Take actions across systems or APIs
• Reflect, retry and self correct in real time

Examples: 

• An agent that understands your sales cycles and throughput and can detect stale deals, generate recommended actions and even send the follow up email on your behalf
• A companion that can triage accounts and identify key whitespace based on external buying signals, while writing those data points to CRM, without explicit instructions

They don’t: 

• Always follow the context
• Always align action to priority
• Always know where they went wrong

The defining characteristics of agents are important because it sets them apart from simple stepped workflow builders. 

The best agents have: 

• Contextual awareness
• Decision making logic
• Access to tools via MCPs (Model Context Protocols)
• Guardrails to protect sensitive data
• Ability to operate over time and contextualize across states
• The logic to self assess and self correct when something is amiss

Why this all matters, especially for revenue teams

The difference between a prompt based workflow and an agent is the difference between a GPS navigation and a self driving car. 

If you’re a revenue leader or a GTM tech buyer, don’t ask if the tool you’re buying “uses AI”. Ask if it can ask on your behalf, with context, memory and agency. 

True revenue agents will be able to fully understand your business: pipeline and forecast, proactive risk assessment and mitigation, coaching and enablement applied dynamically, and RevOps finally out from under the data grind. 

The Future is Agentic

Don’t fall into the trap of believing that Agents = Maintenance. If you have to keep tabs on your processes, or worse, hire someone specifically to manage a tool, there’s a good chance that tool isn’t agentic. 

As your tech stack gets more complex, the last thing you need is another workflow builder. Remember, an LLM can be the brain, the workflow sets up repeatable specific routines, but agents act as functional teammates alongside your human capital. Remember the differences. 

The future of sales and RevOps isn’t more dashboards, workflow builders, or maintenance heavy scheduled processes. It’s agents that work the problem for you.