Several of the SaaS founders I've been talking to lately want to build their company AI-native from the start. They want their employees to fully embrace AI for all the work they do. Not as an optional tool sitting next to Notion. Woven into how the actual job gets done, end to end. But they are even more ambitious than that. They want those same people to build closed loops and workflows around what they do. Not only using AI as a copilot. Actively outsourcing and replacing parts of their own jobs. So they can move on to do better and smarter things. The harder work. The work only a human can do. The work most SaaS teams never get around to. This is exactly the thesis we have at Maskin, and exactly what we help companies do.
Dmytro Nych
4w
There's an interesting shift happening: The most valuable employees may become the ones who can continuously redesign their own work. Not because they know every AI tool, but because they know where friction exists and how to turn repetitive work into repeatable systems.
Denis Milko
4w
I think the keyword here is workflows, not AI. AI-native companies aren't just adding AI to existing processes. They're redesigning the way work gets done. If the underlying workflow is inefficient, AI will simply help you execute an inefficient process faster.
Jasu Jaranka
4w
I am in the process of launching an AI-native company and I also see the benefits and risks associated with using the different AI models. On one hand I can extend my knowledge to areas where I am not so proficient and in the other hand I can automate things which make sense. Risks are obvious and maybe not so obvious to everyone. I've seen a lot of discussion about safeguarding your work, as if you are using a private account with any of the frontier models, all your work can be ingested and taken by the companies running those models. I've also seen a lot of security risks, vibe coded apps leaking customer information, poisoned chats leaking private information, consumption getting out of hand and skyrocketing your costs, automating processes and introducing compliance risks, the list is ever growing. I have the feeling many companies don't pay enough attention to first define guardrails and compliance principles, maybe just because they don't know how. EU AI Act is also around the corner and that will pose again pressure on companies to get their act together. Using just local models is not easy either. You might control the box, but the outcomes are still your responsibility. You still need guardrails and compliance.
The companies that gain the most from AI won't just adopt new tools they'll redesign how work gets done. AI-native organizations are built around better workflows, freeing people to focus on judgment, creativity, and higher-value decisions.
This mirrors what I've seen building AI-native workflows myself — the real unlock isn't the copilot phase; it's when the team starts asking, 'Why does a human need to be in this loop at all?' That question changes how you scope the entire product.