There is a dangerous illusion in watching your registration counter go up every morning when nobody is actually sticking around to use the product long-term. We realized our leaky bucket was wasting weeks of engineering effort on acquisition channels that brought in zero active users. Once we tied our team's goals to activation milestones instead of raw signups, everything changed. If you went through this same wakeup call, what specific metric finally forced your startup to focus on activation over volume?
If a model can escape, the sandbox was never actually a sandbox. Network policies were too loose, shared services created side channels, privilege boundaries were theater. No amount of prompt engineering fixes a misconfigured egress rule
So, been running a AI startup for more than a year now and the one thing i always thought or was puzzled was when naturally customers think AI should be cheaper than human hours even though AI's throughtout or the benefits is 100x. So we have been doing it the 'cost+' pricing way, but to be very frank this is working and is helping us be in control of the margins, but also exploring outcome based pricing in certain use cases. Will have this thread open to have discussions around this topic, also if i find newer ways or use cases where outcome based pricing works, happy to explore.
