This article discusses insights from a conversation between Ajit and Akhil on the "Money Masala" podcast, where they analyze Salesforce's recent challenges with Agent Force and explore the rapid evolution of household robots powered by AI.
The Video Source
In a recent episode of "Money Masala," SaaS and AI pricing experts Ajit and Akhil discussed the contrasting realities of AI implementation across different sectors. They examined Salesforce's difficulties with their Agent Force platform alongside the surprisingly rapid advancement of household robots, offering insights into how AI is transforming business and everyday life.
Salesforce's AI Growing Pains: Agent Force's Confusing Value Proposition
The conversation began with a critical analysis of Salesforce's recent performance issues, particularly the slowdown in revenue growth despite recent price increases. At the center of this discussion was Agent Force, Salesforce's AI agent platform, which hasn't gained significant traction.
Akhil observed that Salesforce has "a history of bad execution, bad product launches. They launch products before anything is built…Mark Benioff's history—he did it with Salesforce Einstein, he never has a product and he releases it."
The experts pointed to several issues with Agent Force's implementation:
Confusing Pricing Model
The hosts were particularly critical of Agent Force's pricing structure, which charges $2 per "conversation" with additional overage fees.
"What is an agent force conversation? How do you define an agent force conversation? And why should I give you $2 per agent force conversation?" Ajit questioned. "I have a problem—I want you to get my salespeople to put data in Salesforce. Everyone in my organization hates using Salesforce. Why will I have a conversation with Salesforce?"
Shift from Seat-Based to Usage-Based Pricing
Salesforce has historically offered seat-based pricing, where customers know exactly what they're purchasing. Agent Force represents a major shift to usage-based pricing, creating uncertainty for enterprise customers who prioritize cost predictability.
"Usage-based pricing, while it is the buzzword or the favorite child of all pricing experts out there, needs to be done with nuance, carefully," Akhil noted.
Poor Positioning
The experts argued that Salesforce focused on platform positioning rather than solving specific customer problems, making it difficult for potential users to understand how Agent Force addresses their needs.
"Pricing is positioning, and this is completely botched positioning," Ajit emphasized. "When I go to a customer, [they want to know] do you have aspirin because I am having a headache? Or do you have that cold pack because I have a shoulder issue?"
The Surprising Advancement of Household Robots
In contrast to Salesforce's struggles, the conversation shifted to the rapid advancement of household robots, which has surprised many industry observers with its pace.
Why Robots Have Advanced So Quickly
Akhil explained several factors driving this acceleration:
- Hardware improvements: "The actuators that you use, the motors that you use, the battery efficiency, the lightness of the components—it has obviously improved. That's not sexy, that's boring, no one talks about it, but it is there."
- Elon Musk's influence: "When Elon Musk launched their Optimus line of robots, which were the first mainstream humanoid robots…when Elon Musk does things, people and the industry both have a lot of trust and faith in him."
- Investment in the sector: "If you are an up and coming robotics startup who wants to build a humanoid robot, VC money becomes easier because VCs are like, 'if Elon is investing in this, then this is something worth looking at.'"
- LLM integration: "The rise and the significant improvement in the LLMs is what is driving this…you talk to a robot…it might not seem but the Apple example is the most important and critical example. The fact that the robot has the capability to understand that this is an apple…and that robot knows if it's a rotten apple, it needs to be thrown, and if it's a good apple, it needs to be put in the refrigerator."
The Economic Feasibility of Household Robots
When discussing pricing, Ajit estimated that paying for regular house cleaning costs around $5,000 per year. Akhil predicted that household robots might become affordable within a similar range soon:
"The sweet spot is $20,000 to $40,000. It is very feasible within the next two years, and again, my confidence comes from seeing how fast the technology is evolving, how fast the usability of these devices is changing."
For widespread adoption, Akhil suggested robots would need to be versatile: "If it is doing five things only, it is not enough. It should be able to, out of the box, do 20 things, and as it lives in the house, it should be able to start learning to do new things."
The Future of AI and Robotics
The conversation expanded to broader implications of these technologies:
Self-Driving Cars and Humanoid Robots
Ajit wondered if it might be easier to have a robot drive a car than to build self-driving systems into vehicles. Akhil responded that robots would likely interface directly with vehicle systems rather than physically operating controls like humans do.
Military Applications
The pair briefly discussed how robotics might transform warfare, with Akhil noting: "This is not going to happen as fast as it is happening in the consumer space…because all these are hackable devices. Anything that is connected to the network, as fast as security may move, the cracks always catch up."
Ethical Concerns
They touched on ethical concerns around autonomous robots, with Akhil invoking Asimov's Three Laws of Robotics: "A robot will not injure a human being, a robot will have to obey a human being…and assuming that the first two laws are not being breached, the robot will make sure that it does not get harmed."
Timeline to AGI (Artificial General Intelligence)
On the question of how close we are to AGI, Akhil offered: "If we only concentrate on making LLMs better, AGI is not happening in two years, but…if we concentrate on other architectures, other infrastructure, AGI is a possibility within two to four years."
Key Takeaways
The contrast between Salesforce's struggles with Agent Force and the rapid advancement of household robots highlights several important lessons for SaaS executives:
- Value proposition clarity is essential: Customers need to understand exactly what problem your AI solution solves and how it will be measured and charged.
- Predictability matters to enterprise customers: Usage-based pricing creates uncertainty that many enterprise customers aren't comfortable with.
- Product-led growth beats marketing-led launches: Salesforce's approach of announcing products before they're fully developed creates skepticism and disappoints users.
- AI integration is transforming hardware and software alike: The combination of improved LLMs with better hardware is creating opportunities for products that seemed like science fiction just a few years ago.
- The pace of AI advancement continues to surprise even experts: As Ajit noted, "Looking at how fast my job as a coder is being replaced…I am already flabbergasted. Every day as I interact with these AI tools…nothing surprises me anymore."
For SaaS executives, these insights suggest both caution and opportunity in AI implementation—caution in how AI capabilities are packaged and priced, but opportunity in how quickly AI can transform product capabilities when properly executed.