The Grok Bot That Has Self Improvement! Your Grok Bots are telling you exactly where their time and tokens go. I show you how to listen in and have them grow and improve. I run a lot of Grok Bots, and I asked the obvious question: which of them actually earn their keep? So I built a weekly usage audit. You upload your bot usage export and it turns the raw trace into a clear map: - Which Grok Bots and runs eat the most tokens, broken down by day and by size - Which runs keep repeating while saying almost nothing new - Which runs give me a real decision, and which just rehash what I already know - Concrete fixes for each one: cap the sources, skip the "nothing changed" recap, switch hourly checks to on-change, merge routines that overlap - A clear line between work Grok Bot can fully own on a schedule and the calls that still need my judgment Every number shows its math. Nothing gets guessed or padded. Each change can be tested against next week's export, so you can see what actually worked. This report can be fed back to your CEO Grok Bot and make great use of the feedback. This isn't about cutting back on Grok Bot. It's about making every token go toward something you care about. And you help Grok Bot learn. A full step-by-step guide along with the Grok Bot you can copy and paste. Get it: The usage file records every turn the Grok Bot took, grouped by time and token count. One morning’s slice can show a cluster of runs, each between roughly 74K and 145K tokens, executed within minutes of one another. That sequence is the external trace of work the bot already performed under the instructions it already holds. Exporting the file and asking the Grok Bot to read it forces a comparison between the roster that was set and the turns that actually ran. High-token clusters often come from a research routine that reloads the same sources on every step, or from a coordination step that writes and then processes a wrap-up note even when the delta is empty. One pattern that appears is a single routine that hits a context ceiling and forces a second worker for one morning; another is a set of small runs whose combined wrap-ups account for a larger share of the week than any individual task. The arithmetic in the file shows which patterns dominate and which do not. The Grok Bot that executed those routines already carries the record of the goals that were stated, the tactics that recur, the skills that were called for, and the interests that reappeared across prior exchanges. The CSV does not add new facts about those aims. It supplies the measured sequence of how the existing model was applied. Each report give you and Grok Bot paths to better and better outcomes. It basically always works. Asking Grok Bot to restate what it already knows from the history, then to map the costly or repetitive runs onto those aims, is reinforcement of the picture it holds rather than the introduction of new information. Grok Bot is checking its accumulated record against the turns the system logged. The practical step is to give the Grok Bot a standing instruction that treats each weekly export as one more input alongside the history it already carries. Each report optimizes Grok Bot to better understanding of you and itself. Grok Bot self improves… Get it:

NVIDIA CEO JENSEN HUANG SAYS HE BELIEVES MOST PEOPLE IN GERMANY WILL MOSTLY WORK INSIDE A DIGITAL TWIN OF THEIR COMPANY, BUILDING DIGITAL CARS WITH DIGITAL BRAINS, WITH AI ROBOTS BUILDING ROBOTIC CARS INSIDE ROBOTIC FACTORIES

Regulatory certainty in crypto markets shouldn’t come with an expiration date. I’m committed to working across the aisle to establish clear, durable rules of the road that provide lasting regulatory certainty and stand the test of time. More on @Bankless: