Welcome to the Dealmakers Digest
Hey there, I’m Shavaye.
I’ve spent my career inside deals... partnerships, joint ventures, the cross-border kind where two companies from different worlds try to build something neither could alone. Dealmakers Digest is where I write about how great deals actually get made, in plain language, for anyone who wants to understand the game. You don’t need a finance degree to read anything here... every company and every term gets introduced like you’ve never heard of it, because maybe you haven’t.
What you’ll get:
One full deal breakdown a month: the players, the deal, the principle behind it, and a personal principle from my own years at the table. Short notes through the week when something catches my eye. And a shared vocabulary (you’ll see Posture and Structure at the bottom of my posts) so “this looks like a good deal” stops being a feeling and starts being something you can check.
That checking part matters to me. I score deals in public, before anyone knows how they turn out, and the scores stay on the record... the hits and the misses both. The full scoreboard arrives with the next issue on 17 August.
Every deal, scored in public. Before we know how it turns out.
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How I use AI here
Short version: the research and the tooling lean on AI. The writing and the thinking don’t.
It runs the numbers. I built something called the Deal Reaction Engine. It reads deal announcements and tracks what happened to the share price afterwards, and it has now been through five years of them across every industry on the S&P 500. I built it with Claude (an AI assistant made by Anthropic) running on a mac mini under my desk. There was never a version of this where I read and coded all of that by hand… that’s the honest reason it exists.
It finds the source material, and it builds the tools. Press releases, filings, transcripts. The charts, the deal cards, the ledger site. That’s research and software, not writing.
It doesn’t write. Every sentence here is mine. When I came back after a long gap I had a couple of drafts sitting in a folder that weren’t good enough, and the option of letting a machine fill the space was right there. I didn’t take it. If the ideas aren’t mine, there’s no reason for you to read them instead of just asking a chatbot yourself.
It doesn’t form the opinion, and it doesn’t pick the deals. What a deal actually means, which part of the structure is doing the work, whether a partnership is built to last. Those come from time spent inside deals and they’re mine to get right or wrong.
It doesn’t go near your data. Your name, your email, what you read. None of it gets fed into an AI tool at my end.
Every number, name, date and quote gets checked against the original source before it goes out. AI is fast and confident and occasionally wrong, and a confident wrong number is worse than no number at all. Where I get something wrong I’ll fix it and say what changed.
Where AI did something specific to a piece, like processing a dataset, there’s a line at the bottom of that piece saying what it did and what I did with it. Where it didn’t, there’s no label. A disclosure on every single piece stops being transparency and starts being noise.
Last updated: 5 August 2026
