The Most Important Agent You’ll Ever Build

Four Key Criteria for Implementing a Successful Agent

What is the most important agent that an Agentforce customer will ever implement? The very first one. If the first agent is a failure, then you substantially decrease the odds of any subsequent agents being approved or even considered.

I’m not saying the first agent needs to make the most revenue, be the most high-impact use case, save tons of hours, or even be all that objectively successful. But it needs to show potential and an achievable scale.

I had a recent conversation with a CMO who was looking to reevaluate her tech stack and get started with AI agents. But before we even began solutioning, she stated up front, “whatever the final tech stack is, it can’t include Data Cloud. I don’t even want to hear the name of that product.” 

Naturally, I had to inquire further. Turns out she had a Data 360 implementation go awry. After digging deeper, my suspicions were confirmed: it wasn’t the product at all that had failed her. It was the implementation. The partner they had selected failed in three ways:

• They did a poor job of defining functionally what the initial use cases were and how they would bring value
• They didn’t understand technically the product, best practices, proper data modeling, and how to implement it for optimal execution of those use cases
• And they failed the customer strategically on advising how to reframe their use cases for better performance, asking the right questions, ensuring training and adoption were in place, documenting what was done, as well as why

First impressions matter. If we don’t select the right use cases, the right partner, the right data, and equip users with the right capability… then you drastically lower the likelihood of:

• Adoption
• Leadership buy-in
• Budget approval
• Resource allocation and support across the organization

Basically, if the first agent isn’t successful, then you may have just torpedoed the chances of your next use case even happening. If the inaugural flight doesn’t take off, you may be grounded for good.

So how do we avoid that? How do we ensure a successful first agent?

Criteria for a Successful Agent

There are four considerations an agent has to follow for it to ensure proper success, adoption, and scale:

And if I had to add a fifth criteria, it would be Plausible Deniability: Find yourself a good fall guy to blame this on if it flops!

Kidding, of course. If you follow these four criteria, you won’t need a scapegoat. But really, this framework should serve as your north star for determining and prioritizing your most qualified agentic use cases.

1. Feasibility: Can you realistically build this?

It’s agentic, not magic. Let’s make sure we have the clearest path to success with the least resistance:

• Do you have reliable, accessible, high-quality data?
• Are your systems and APIs integrated (or accessible to be integrated)?
• Do you have the technical talent and the right partner in place to support it?
• Is there a reasonable timeline for delivery?
  

2. Measurability: Can you objectively show success?

If you can’t measure it, you can’t defend it. One of the biggest missed steps I see is agents built without any determining criteria of success.

You need:

• Clear success metrics tied directly to business goals
• Established baseline benchmarks to measure against
• User / system feedback loops
• Dashboards or reporting in place
  

3. Viability: Will it impact business in a meaningful way?

This is where strategy meets reality. Context, culture, and communication become very important here.

• Do you have executive sponsorship?
• Commitment from teams / stakeholders involved?
• Clear ownership and operational accountability?
• Is this in a low-risk area where we can test / iterate without missteps affecting business as usual?
  

4. Desirability: Will people actually use it?

This one is underrated, often ignored, and the most intuitive (if we step back to consider why and not just what and how).

• Were users involved in shaping the agent?
• Do users actually want an agent for these types of interactions (e.g., is this a convenience for users, or does it make our brand appear less personal?) 
• Is there transparency, explainability, and review logic?

Your fallback logic matters here. This is a set of predefined behaviors when an agent doesn’t know what to do, can’t complete the task, or hits a low-confidence threshold. Think of fallback logic as a safety net when the agent needs a graceful way to fail forward without losing user trust.

Great Agents Start With Great First Impressions

Your first Agentforce use case doesn’t need to be perfect; it just needs to earn the right for what comes next.

The experience that CMO had with her Data Cloud project is a reminder of what happens when the first impression is mishandled. One early misstep can follow every future conversation and quietly shut the door on tools, strategies, and innovations that would have delivered real value. A poor debut has a long shadow, and it can pre-load the next initiative with opposition before it even starts.

Your first Agentforce use case is your chance to break that pattern. It sets the tone. It builds trust. It shows your teams what is possible when the right use case, the right implementation, and the right expectations come together. Most importantly, it keeps the door open for all the exciting future agent use cases.

Leverage Agentforce in a way that is feasible, measurable, viable, and desirable. And let your first agent be the one that opens the runway, not the one that closes it.