I see a lot of people debating what counts as strong AI. But when I look at the actual capabilities of current AI systems, it seems clear we already have it.
Let’s look at the facts:
First, we have AI models scoring over 2700 ELO in competitive coding. That’s better than most human experts, including OpenAI’s Chief Scientist. These models write complex software solutions faster and more accurately than top human programmers.
Second, AI agents are making businesses drastically more efficient. They handle customer service, automate workflows, and optimize operations in ways that were impossible just a few years ago. The impact on productivity is measurable and substantial.
Third, we now have models that let anyone build business-ready internal tools without knowing how to code. This democratization of software development shows AI can understand and implement complex business logic independently.
Most telling though: we have models that can watch other AI systems, analyze their performance, and update their own reward functions to get better results than human-designed solutions. This self-improvement capability is exactly what many people claimed would be a key marker of strong AI.
I’ve written before about the various levels of AI agents and their capabilities (https://adam.holter.com/the-5-levels-of-ai-agents-from-basic-chatbots-to-self-improving-systems/). The systems we have now check most of the boxes for what experts historically defined as strong AI.
The reality is that strong AI isn’t some far-off theoretical milestone – it’s already here in practical form. The question isn’t whether we have strong AI. The question is what we’re going to do with it.
These systems may not match every sci-fi vision of artificial general intelligence, but they demonstrate general problem-solving abilities across multiple domains. They can learn, reason, and improve themselves.
Instead of debating definitions, we should focus on understanding and effectively using the powerful AI capabilities we already have. The future isn’t coming – it’s here. And it’s time we adjusted our thinking accordingly.
