A GROK ENGINEER JUST SHOWED HOW TO MAKE AGENTS IMPROVE THEMSELVES AFTER EVERY RUN
most agents lose the useful part when a task ends: the mistake, the correction, and the reason the final version actually worked
grok runs two loops at once → one handles the real task → another studies the result → extracts the lesson → saves it for the next run
instead of growing one massive prompt, feedback becomes small reusable knowledge files. bad decisions get corrected once, while useful patterns survive across future tasks
over time, research, coding and review all inherit what previous runs learned without retraining the model or rebuilding the agent from scratch
this is where grok stops feeling like something you keep correcting and starts behaving like a system that compounds what it learns
Get started now for free. No friction, no guesswork, just clear financial calculations built for real estate and note investing. Start here: https://t.co/ysmCCI2HYI
Most real estate deals die not from bad properties, but from bad math. If you can't model the cash flow, you can't make the decision. A thread on fixing that.
The investors who consistently win are not smarter. They simply have better information, run faster, and trust their numbers. TVM gives you that foundation on every single deal.
Most real estate investors lose money not because they pick bad deals. They lose because they cannot do the arithmetic fast enough to know a bad deal from a good one.