Standing out in the age of AI productivity
The connected world has been defined by 24×7 availability and activity. Websites are always on ready to service customers globally. Successful businesses have been defined by making money while you sleep. Productive business ran global operations with handoffs. Start day in Asia, have support in Europe and finish the day in the US. Early mornings and late nights ensured handoffs to communicate what was completed, and what was to be done next. In today’s AI driven world, the 24×7 stays local thanks to agents.
Limited by the ability to think of the ways to utilize the agents available to you. With Molt Bot and Claude agents, you are limited by the ability of your imagination on projects to undertake. From coding up simple agents together agents, to automate the mundane tasks that required logins and clicks, now AI agents can handle that in minutes and wait for your next command.
This means output is no longer limiting creation.
Companies have access to the same 10X level engineer who can code project requirements in no time resulting in immediate output. The backlog of ideas from customers, the medium bugs that should get resolved but never get prioritized are just hours of thinking the right prompt away from being solved. The code to create the feature or resolve the bug is handled by AI. The unit tests are run via AI QA agents, and the need to end workflow is modified to account for the new code addition.
With the creator economy available to all thanks to AI, thinking becomes the critical factor. How well you see the world, how well you understand people and how well you link people to the solution. Startups carve out a niche from the larger solutions do a part of the process extremely well. Then they add on adjacent solutions and over time become an encompassing solution. That leaves them open to not solving a slice of the workflow open to a competing startup to replicate the process.
What makes this work is that the user knows their problems the best, and now can create the tooling to solve their problems at scale with AI agents. No need to wait for the feature request to be implemented in version 3. Now everyone can create 100 of the similar solution. That doesn’t mean all solutions will be good or even usable. Understanding the limits of what can be done, what takes user interaction, and how to design the workflow so users understand and can interact with the solution easily will help differentiate the winners.
After creation, generation in the new AI world leaves the last and hardest challenge to scaling which is eyeballs and distribution. Like apps for Google Play or Apple, there is no shortage of simple apps. They differentiate on feature and over time some can scale, and some new ones can enter the marketplace and take footing. AI based apps will see the same challenge as they compete with similar functionality for a select user base. What will win will not be how fast the app developed, but rather how well the tool provides service to users. This goes back to how well thought out the initial design process was and its interactions with the AI tools.