Edward Wong leads Ibbaka’s research and community work. He is constantly using AI to explore ideas, test value and pricing models, develop databases of synthetic users and synthetic data and to document Ibbaka’s processes (Ibbaka documents its processes as context documents and prompt sequences. Here he explores his first two years of working with AI.

Witness the strategies shaping the future of B2B SaaS with exclusive access to our 5 most essential recent webinars—with our VIP decks now available for download. These sessions bring together the latest thinking from the industry’s top pricing and monetization experts, covering everything from Q1 2025’s biggest pricing shifts and the evolution of agent-based packaging, to actionable frameworks for AI pricing, mid-year trend analysis, and what’s really happening in B2B SaaS monetization.

Agents are popping up everywhere. Vibe coding and good tooling have made it easy to develop agents. Users and buyers are looking for simple solutions that leverage AI. Agents are the result. There are two broad trends: net new agents and agents built to access functionality and data in existing apps. How do pricing approaches differ in these two cases?

Professionals have a growing realization of the power of agents to take their work to the next level and are looking for ways to leverage AI. Pricing is a focal point for this as it has always been tool and data heavy and has long leveraged AI in different parts of the value chain. Pricing experts are looking for agents that complement them and that are specialized for specific customers or pricing challenges rather than generalist AIs.

One emerging strategy for designing and pricing a family of agents is the team. Agents are being designed as complements or replacements for well established functional teams. An example of this in the data space is Brighthive. They have designed their agents to reflect well established roles on a data team.

Over the past three months there has been a sea change in packaging and pricing for AI. The biggest change has been the rise of agents. But there has also been a shift to making AI the default. We can see that in recent moves by some of the world’s leading software companies: Intercom, Adobe and Gong.

An emergent pattern in the agent economy is for companies to provide their customers with the ability to build custom agents that sit on their platforms and help the customer get more value. These are often called User Built Agents. How is value created for customers with this new functionality? How will it be priced? Ibbaka used it value model generation AI to explore these critical questions.

On April 24 Ibbaka published some important research on pricing and billing in the agent economy. This is the first in depth report on the emergent Agent Economy. Agents are becoming one of the primary ways that generative AI functionality is being brought to market. The report is rather long, more than 80 pages, and in today’s high paced world not everyone will want to invest the time to read in depth We get that. Here are a series of prompts, and responses from Perplexity, that give different entry points into the report.

Pricing of agents is a hot topic in business circles. As we move to an agent economy how will pricing change? We explore this question by using the concept blending technique to create concept blends of Jobs to be Done and B2B SaaS and then Jobs to Be Done and Agent AI in the context of pricing. We then compare the two.

Pricing AI Agents is a critical challenge for pricing and innovation in 2025. Two approaches have emerged so far, the Ibbaka Agent Pricing Layer Cake and the Growth Unhinged Agent Pricing Matrix. Let’s look at how these work and how they can be used to price AI agents. As credit based pricing is becoming common for AI agents the two approaches are combined to address this.

The Agent Economy is rewriting the rules for B2B software and launching a revolution as important as the one Salesforce launched back at the beginning of the 21st C with its ‘No Software’ SaaS business model. Ibabka has compiled extensive research, including primary research, on the implications of agents for value, packaging, pricing and billing. This extensive report will help you execute on the changes we all need to make.

The agent economy will replace the subscription economy and most value currently captured within enterprise software will be delivered by agents. This will require new approaches to pricing. By combining the Jobs to be Done approach to pricing with the Ibbaka AI agent pricing layer cake there is a path forward for Agentic AI companies.

How will AI agents restructure the B2B SaaS sector? One frame for this is Clayton Christensen’s framework of disruptive innovation. Are B2B AI agents an example of sustaining or disruptive innovation? How does this impact go-ot-market strategies? What are the implications for pricing?

AI agents are emerging as a standard way to deliver AI functionality, especially in B2B. This has been underlined by Salesforce’s recent Agentforce announcements. Agent pricing is evolving from inputs and number of agents to actions and outcomes. This evolution is framing how we think about pricing generativeAI.

AI agents are emerging as a standard way to deliver AI functionality, especially in B2B. This has been underlined by Salesforce’s recent Agentforce announcements. Agent pricing is evolving from inputs and number of agents to actions and outcomes. This evolution is framing how we think about pricing generativeAI.