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You're Invited: Investing Moves to Boost After-Tax Returns
You've worked hard to fund your portfolio — your investment strategy should work just as hard to maximize your after-tax returns.
On September 17, join Range's CFPs and CPAs live for the practical moves that put more of your returns back in your pocket.
What we'll cover:
Investment moves to maximize your after-tax returns
How tax-loss harvesting can lower the taxes you owe
When direct indexing works (and when it doesn't)
How to build a diversified portfolio that reduces tax drag.
Range is all-in-one AI wealth management — tax, investments, retirement, and estate in one place. Bring your questions for the live Q&A. Free to attend, and seats are limited.
This webinar is for informational purposes only and does not constitute investment advice or a recommendation to buy, hold, or sell any security. Forward-looking statements involve risks and uncertainties. Past performance is not indicative of future results. Range defines "high earners" as households with income over $300k.
GM to the Top 1% ☕
I counted eleven significant model and agent platform releases inside a twenty day window last month. Not announcements. Releases, with changed capabilities and changed interfaces.
I know a rep who watched demo videos for six of them. He can tell you what each one does. His pipeline looks exactly the same as it did in June.
Saturday is the right day to say the unpopular version of this. Almost none of the hours you have spent learning AI tools have produced revenue, and the reason is not that you picked wrong.
💡 TOOL FLUENCY IS A DEPRECIATING ASSET
Here is the math nobody runs. If the tools in your category meaningfully change every eight to twelve weeks, then knowledge of a specific interface has a half life shorter than a sales cycle. You are acquiring a skill that expires before the deal it was supposed to help you close.
That is not an argument for ignoring the tools. It is an argument for being deliberate about which layer you invest in, because there are two and they behave completely differently.
The interface layer is what changes. Which menu, which button, which product name, which company got acquired this quarter. It looks like learning. It feels productive. It is worth close to nothing in twelve months.
The instruction layer is what compounds. Knowing how to describe a buying committee precisely enough that a machine produces something you would actually send. Knowing what context a model needs before it can be useful about an account. Knowing what to ask for and how to tell whether the answer is good. That skill moved cleanly from every model generation to the next one, and it will move to the next one after that.
The sellers who look fastest right now are not the ones who tried the most tools. They are the ones who got very good at asking, on a small stack they stopped changing.
🔧 THE THIN STACK
Four moves. Twenty minutes on a Saturday.
1. Cap the stack at three: One general model, one thing that touches your CRM, one research surface. Anything beyond three is a hobby. Write down your three and stop evaluating.
2. Freeze it for a quarter: No new tools until December. Every switch costs you two weeks of relearning and buys you a marginal capability you will not use.
3. Build a personal prompt library: Take the five things you do weekly and write the instruction once, properly, with your context in it. Save them somewhere you will actually open. This is the asset that survives the next eleven releases.
4. Measure output, not adoption: At the end of each week, name one thing that reached a customer because of the stack. If you cannot, the problem is your instructions, not your tools.
🎯 THIS WEEK'S HOMEWORK
Pick your three and write them down. Then take the single task you repeat most often, whether that is post-call summaries or account research or a follow up you keep rewriting, and build one good reusable instruction for it. One. That single artifact will outperform every demo video you watch this month.
❓ QUESTION OF THE DAY
How many AI tools are you currently using, and how many produced something a customer saw last week?
Reply with both numbers. The gap between them is the whole conversation.
See you tomorrow.
Edward
Founder, Morning Sales
P.S. Building a good prompt library from scratch is a weekend you probably do not want to spend. The 500 AI Sales Prompts manual is mine, already built and already tested against real enterprise cycles, organized by the moment in the deal where you need it. Model agnostic, so it survives the next release cycle. 27 dollars: https://store.edwardgorbis.com