AI SaaS Pricing: How to Profit When Every Prompt Has a Real Cost

In SaaS, variable costs are familiar. AWS and Azure bills rise and fall with traffic, storage, and bandwidth, but you can usually forecast them and smooth them with commitments.

AI flips the model because cost is triggered by a mixture of behavior and model choice, not just scale. Each generation can add metered COGS, and multimodal makes the spikes sharper: images, audio transcription, voice output, and video generation can cost orders of magnitude more than a short text reply. Retries, longer outputs, bigger context windows, and tool calls amplify this fast.

Then comes the perception problem. Buyers are trained by ChatGPT and Gemini that AI feels cheap or “free” at the point of use, which anchors expectations. The executive challenge becomes defending value and margin while keeping usage predictable.

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Going Deep: My Journey from ChatGPT User to AI-First Builder

Like many of you, I started experimenting with ChatGPT out of curiosity.

Initially, it was a helpful assistant, assisting with tasks ranging from writing emails to drafting summaries and even brainstorming ideas for presentations. I got good at writing prompts. I learned to coax better answers by refining my questions, layering context, and iterating until the output was just right.

But here’s what I quickly realized:

Being proficient at using ChatGPT doesn’t mean you understand how large language models (LLMs) and Generative AI (GenAI) really work, nor what they can and can’t do to transform a business.

I’ve had the privilege of leading global teams, driving SaaS transformations, and delivering meaningful outcomes. I’ve seen firsthand how technology waves come and go, from the early days of web software to mobile, cloud, and subscription models, but what’s happening now with AI is fundamentally different. It’s not just a new tool; it’s a new paradigm for how businesses think, operate, and create value.

And so, earlier this year, I made a decision: If I wanted to lead in this new era, I needed to go deep.

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SEO Alone Is Dead: It’s Time To Embrace AIO

Online marketing is undergoing a dramatic transformation. For over two decades, Search Engine Optimization (SEO) and the tyranny of being “above the fold” have been the cornerstone of online visibility. Then came the viral power of social media optimization (SMO), focusing on “sharability”. The rules of the game are changing once more: AI assistants like ChatGPT, Perplexity, and even Google now directly answer millions of queries, often without redirecting users to your content! This article outlines the history, best practices, and future strategies to ensure your brand remains visible, whether in search results, social feeds, or AI-generated answers.

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GenAI for Business Leaders: Strategic Lever or Cognitive Trap?

Generative AI (GenAI) and large language models (LLMs), such as GPT-4o, have swiftly revolutionized our work dynamics. They have emerged as indispensable business tools, reshaping the modern corporate landscape. These advanced AI systems promise transformative benefits, driving unparalleled productivity, innovation, and profitability. Despite the complex challenges that come with their adoption, companies embracing GenAI are on the brink of a transformative era. The success of this journey hinges on intentional oversight, robust governance frameworks, and a strategic balance between automation and human judgment. How prepared is your organization to harness the full potential of this transformative era?

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Seeing the Forest and the Trees: Why Leaders Need a Systems Mindset

close up of a tree trunk in lush forest

Leading a business is like running a control center. Every switch, gauge, and flashing red light represents decisions, external forces, and a network of human relationships. It’s tempting to jump from crisis to crisis, putting out fires. But without stepping back to see the whole system, leaders risk missing the bigger picture. Problems persist, and root causes remain untouched.

Systems thinking shifts focus from firefighting to foresight. It reveals hidden bottlenecks, delays, and inefficiencies. It helps leaders make smarter decisions by understanding how changes ripple across an organization.

My introduction to systems thinking came when I decided to attend an elective course at university. What I learned about seeing the bigger picture and inter-connectedness has shaped my thinking ever since. This mindset has helped me always consider how decisions ripple through organizations over time.

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Time to go beyond Product-Led Growth – think Customer Journey

In recent years, PLG, or Product-Led Growth, has become a significant buzz in the tech world, and rightfully so. Products that delight customers and fuel growth loops are essential. If your offering can’t deliver considerable value to your users, if your product isn’t resolving major pain-points, or isn’t providing big WOWs over the alternatives where it matters, then you’ve got (lots of) work ahead. But with the rise of digital channels, customers interact with businesses in multiple ways that drive the overall experience. Only focusing on the product or go-to-market-led growth is no longer enough – it’s time to prioritize the whole Customer Journey (CJ).

It isn’t about Product-Led, OR Sales-Led, OR Marketing-Led Growth. It’s all the above simultaneously. It’s about Customer-Led Growth. It’s about delivering an end-to-end experience at every touchpoint of the customer life cycle that feels like one, delighting the user at every step.

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Leveraging Lean Startup in established organizations

As organizations mature and become more complex, aversion to risk increases, resulting in a slow decision process. Yet the world around is not standing still, and the speed of change continues to accelerate. Nimble young businesses, who live by the Lean Startup approach of building, measuring, and learning, move from nothing to a product customers love in what appears, from an established company perspective at least, virtually no time.

If both have strategic clarity around the vision, startups leave established organizations in the rear-view mirror because they optimize for simplicity and velocity. Startups practice the lean methodology to avoid spending time on things that ultimately won’t deliver value. They prevent waste by learning early and quickly where they are wrong.

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V1 innovation within a V+1 org

Startups are optimized towards launching version 1.0 offerings, identifying product-market fit, and putting in place the best go-to-market organization to attract new customers. Once the “magic” happens (or should I say the challenging work pays off), when users and products find each other in a happy place, the growth loops evolve towards retention in addition to the original focus purely on acquisition. As the company matures, there is a natural tendency to increasingly drive the business towards delivering incremental products, focusing on the existing target audiences. After all, that’s where the revenue has come from historically, so why not concentrate the R&D and go-to-market investments on what we know best and minimize financial risks? Larger companies sometimes have a hard time going after something unproven that will take investing multiple years to become a meaningful part of the revenue. It could even take market share away from existing offerings!

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Where in the org is Product Marketing?

As companies evolve, they (sometimes) take the time to reflect on the best teams’ structure to achieve their strategies and goals. For most groups, the roles and responsibilities are self-contained within that function. For example, while the sales team organization to deliver the expected results might change significantly over time, from an inside-sales structure to heavy OEM or direct-to-consumer focus, the boundaries remain within “sales” – I can’t name any examples of companies beyond the Seed stage where the R&D leader manages the enterprise sales team. Yet, for one role, defining its location in the org-chart is not as clear… and that challenge is fundamentally described in the function name: Product Marketing.

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It’s not your opinion, it’s your expertise that matters

Everyone has plenty of them, and sadly, many of us are not afraid of sharing them regularly. Not only that, but they often have absolutely no relation with reality. Problematically, the more authoritative your position, the more significant their effect. Yes, I’m referring to opinions. Yet ultimately, what matters is expertise, not opinions.

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