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The real opportunity in agentic supervisory services: make it easy
The LinkedIn experiment confirmed what the quadrant makes clear. Most offerings are either complex systems that take years to show value or easy tools that barely matter. The real opportunity lies in the easy and high value quadrant, where solutions reduce the burden to value and deliver results quickly. The future of work will belong to offerings that combine simplicity with impact, adopted in days, scaled across teams, and delivering meaningful results without unnecessary overhead.
Every day, my LinkedIn feed is filled with big promises. This platform will revolutionize work. That one will redefine productivity. Another claims to change everything about how organizations run. The sheer volume of “transformative” products is staggering. But if we are honest, very little of it feels actionable. Where do you even start?
The problem is not that the tools lack potential; there is a ton of super cool stuff going on. But it is that most of them are complicated, fragmented, and hard to implement. Enterprise control towers, for example, promise high value but demand months of integration, consulting, and customization before a single manager sees benefit. I recently did a deep dive on Microsoft Viva and published some of the absurdities of making that decision. On the surface the options look clear, but the sheer number of features, tiers, and stakeholder considerations turn it into a maze that few companies can navigate with confidence.
On the other end, we have niche automation startups. They are easy to try but ultimately low value, solving one small problem without moving the needle. Somewhere in between are basic monitoring and dashboards. These often prove costly, brittle, and limited in what they reveal, making them hard to justify in the long run.
To cut through this noise, I have been mapping solutions into a simple quadrant of value versus complexity:
- Hard Implementation, High Value: Enterprise control towers. Enormous promise, enormous effort.
- Hard Implementation, Low Value: Basic monitoring and dashboards. Costly, brittle, and often delivering little insight.
- Easy Implementation, Low Value: Niche automations. Quick wins that rarely scale.
- Easy Implementation, High Value: This is the opportunity. A system that delivers enduring value while being simple to adopt.
Most of the industry is crowded into the first three categories. But the quadrant that matters most and has the biggest potential for transformation is Easy Implementation with High Value, and I believe it is glaringly underserved. The challenge is not inventing more complex systems. It is making high valuable systems easy to start, use, and trust.
A Quick LinkedIn Experiment
To test this framework, I ran a simple experiment. I took the last 25 posts from my LinkedIn feed on September 30 and sorted them into the value versus complexity quadrant. Out of those, I identified 17 that were actually selling a product or service. The results were striking. Most of the noise fell into the low value categories, while a heavy share landed in the hard and high value camp, large systems that promise transformation but require massive investment to implement.
But four stood out in the top right quadrant of easy implementation and high value:
- Agentic Commerce Protocol (ACP): This is an open standard co-developed by OpenAI and Stripe that enables businesses to sell seamlessly through AI agents by providing a common language for transactions, making it an easy-to-adopt infrastructure that opens up the massive, high-value new sales channel of AI-led commerce.
- Claude Sonnet 4.5: This is a frontier AI model from Anthropic that delivers high-performance in complex tasks like coding and finance, making it high value by allowing autonomous work that can be accessed and deployed easily via API or existing Anthropic tools.
- Paid.ai: This is a new pricing infrastructure platform that fixes the core problem of charging for AI agents by moving away from the cumbersome “per-seat” model, providing an easy solution to a high-value existential threat to all SaaS companies in the AI era.
- Monetization Operating Model (Metronome Webinar): This is a conceptual offering focused on intentionally building a monetization system as a full-on organizational operating model, which is easy to adopt as a strategic shift but delivers high value by optimizing a company’s highest leverage point—how it makes money.
I would be willing to bet these four are the keepers. They represent just 24 percent of the total but they reduce the burden to value, and they are easy to adopt. And perhaps the most important metric of all is not simply value on its own, but the ratio of burden to value, what I call time to value. The faster organizations can see results without massive overhead, the faster they can embrace the future that everyone keeps promising.
Why This Matters
The LinkedIn experiment confirmed the quadrant in practice. Most of what fills the market falls into low value commentary or complex systems that are difficult to justify. The loudest voices continue to promote enterprise scale towers that require years of work before producing benefit, while countless smaller players promise easy wins that barely move the needle.
The real signal is in the easy and high value quadrant. These are the rare offerings that reduce the burden to value, deliver results quickly, and create room for long term impact. They are simple to start, easy to use, and powerful enough to matter. The four examples from my feed showed exactly that pattern, and they reveal where the future is already forming.
The lesson is clear. The future of work will not be decided by the most complex systems or the most expensive software. It will be decided by the solutions that combine high value with simplicity, that can be adopted rapidly, scaled across teams, and deliver meaningful results without armies of consultants.
The opportunity is straightforward: make it easy, make it valuable, and organizations will finally be able to realize the future that has been promised for years.
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