Week 2. You read this fluently now. Pull anything new — then we get to work, because today the work is real.
That was the craft. This week, you point that craft at a real paying project.
No more sandboxes. This week you take a real application-security engagement from the very first email all the way to a delivered, professional product — and you do it the way it actually happens: building the thing as you sell it.
Most people bolt AI onto an old way of working: traditional → augmented → AI-native, one painful step at a time. You get to skip straight to native. You've never done this the old way, so you have nothing to unlearn. Every part of the business — finding work, pricing it, building it, delivering it — gets designed as an AI-native system from day one.
Discussion: it's a slow Friday, you're not a salesperson, and this is money on the table. What do you actually do with this?
That's the point. Sales is friction — the right tone, the right price, the right next move, all under uncertainty. When you feel that friction, the move isn't to fake confidence. It's to reach for AI — and reaching for it means building a repeatable method, not a one-off lucky reply. That's the whole game this week.
An AI dug all of this out of public sources in minutes. And the tell: Frank called yours a "competing proposal" — there's already a price anchor on the table.
You can't price a project without boundaries, and you can't draw boundaries without knowing the cost — in time and tooling. And here's the twist: you don't have a finished product sitting on a shelf. You're building it as you sell it. So before any proposal exists, you have to come find me — and learn the requirements.
I do this on nearly every project. The difference is I have tradecraft and similar past projects to fall back on. You don't — yet. So you'll feel the gap, and you'll close it the AI-native way: discover the requirements, estimate the cost, then price.
You're AI-natives. Your clients are not. A business client expects security, professionalism, and a deliverable they can actually consume:
The full findings, formatted, branded, defensible.
The higher-level read for Jessica and the principals.
Proof of every finding, walked through in person.
Alongside the PDFs, ship a machine-readable deliverable: a structured tree of folders, markdown files, and an index that an LLM can be pointed at and consume directly — no human reading the PDF required.
We're not building the perfect app-sec methodology this week. The point is to feel how many facets go into delivering any real product:
Prospecting, proposal, product, delivery — underneath all of it runs one continuous loop: capture what worked as a reusable method. The prospecting reply becomes an agent. The proposal becomes a template. The report becomes a house style. That's how I leveled up my own game right before this exact project — and it's the habit you've been banking all week.
This discussion — the friction, the story, the facets.
Run the back-and-forth. Hit the wall. Come learn the requirements from me and pin the scope.
Write the proposal we'll mock-execute, set up the project plan, share it all with me. App-sec method if time allows.
You can't sell yet — so build the method that lets you. Reach for AI, hit the wall on scope, and come find me for the requirements. By the end of today you'll have a real proposal for a real project. Log your time in Harvest.