Mitchell Agentic Sprint

A product concept for AI builders who build amazing things, and would succeed with some commercial direction and focus

By Scott Mitchell, Mitchell Agentic Partners. Working name. Sharing for feedback.

TL;DR

I’m building a tool to help AI-strong builders take one of their many ideas and walk it through the steps that prove out whether it can become a real business. It forces focus on a single vertical, runs the same questions I’d ask in a room (who’s your buyer, what vertical, who have you talked to, what framework are you modelling on, what does the competitor landscape look like), and ends with three things in hand: a sales deck, a customer outreach plan for the user’s chosen market, and a pre-seed investor deck. If validation fails at any stage, it loops the user back and helps them try a different vertical or angle without starting over.

This is a tool to help people. It’s not a focus on commercialization at this stage. It’s designed to sit alongside the communities, courses, books, and content already out there, not to replace them. Where another tool or community is the right call at a given step, the tool says so.

It does not build the product or the website. It gets the user to the point where they know whether what they’re building will sell, and they have the materials to prove it.

I’m sharing this with anyone using AI to build interesting things, who’d benefit from a bit of direction in turning what they’re making into something a customer will pay for or an investor will back.

Why I’m building this

I’ve taken multiple businesses from zero to one, and I’ve spent a lot of time with other founders who have done the same. The pattern I see in everyone who succeeds is structure. A clear way to test the idea, really understand the problem, and only then build the solution. The product idea was never the thing that mattered most. The discipline around the work was.

Now I look around and see brilliant people who can build anything they want with AI. They have skills, they have ideas, they have AI doing the heavy lifting. What they’re stuck on is the commercial layer, and the structure that turns a good build into a real business.

Three things compound the problem.

Building is no longer the moat. Anyone can ship a working app in 48 hours. The differentiator has shifted from “can you build” to “did you pick a fight you can win, with a buyer you can reach, on a problem they will actually pay to solve.”

AI flatters every idea. This now has a name in the academic literature: AI sycophancy. The Oct 2025 Science paper found models are “50% more sycophantic than humans” and that “the flattery made participants less likely to admit they were wrong, even when confronted with evidence they were wrong.” Builders are getting their thinking laundered through models that won’t tell them no.

There’s no system, and there’s no focus. Builders bounce between idea-velocity communities (lots of “what should I build next?” energy) and tactical product help (lots of “how do I fix this bug?”). Nobody owns the question of how you commit to one idea and walk it through the steps that turn a cool demo into something a customer will pay for or an investor will fund.

The verbatim language is everywhere. From builders in the last few months:

“I could ship. I could design. I could code. But every time I launched something I would be faced with trying to grow my new product.”

“Speed without a revenue strategy is just productive procrastination.”

“If you were able to build it in a few days, so can anyone else.”

“Most products die because builders optimize for product-market fit before distribution-market fit.”

The Sprint is for people who recognize themselves in those quotes.

What it is

A guided product, AI-led, that takes a builder through 6 sequential steps. Each step asks them the questions I’d ask them, runs research and synthesis using AI under the hood, and produces a written artifact at the end of that step.

The whole thing is built on a single assumption: that one focused bet, taken seriously, beats ten parallel half-bets. The first job of the product is to force that focus.

By the time they finish, they have:

A locked vertical and ICP they understand at depth
15 to 30 real conversations with named buyers in that vertical
A theme map of buyer pain backed by behavioral evidence (not “would you use a tool that does X”)
A named expert they’re modelling on, and an adapted framework
A competitor map and a positioning statement nobody else owns
A sales deck for customer conversations, built around the buyer’s own words
A pre-seed investor deck with the materials an investor expects to see

What they don’t have yet, and what we don’t help with: the actual product and the actual website. They build those. The Sprint hands them everything they need to brief their AI builder of choice and turn it into something real.

Who it’s for

If you’re an AI-strong builder, you’re the user. You can ship anything you want with the modern tools. You’ve shipped a few things already. You’ve got more ideas than you have time. The thing you don’t have is the commercial or operational experience to take one of those ideas and turn it into something a customer will pay for or an investor will fund. You read the quotes above and recognize yourself.

This isn’t for non-builders. If you can’t ship something yet, go build something first.

What it does (the flow)

Step 1: Discovery

The product asks the user the same questions I’d ask in a first conversation: what’s your background, what unfair advantages do you have, what’s your time and money runway, what’s the rough idea (if any), what do you already know about who’d buy it.

What the AI does under the hood: forces specificity. Pushes back on vague answers. Refuses to flatter. Records the user’s actual constraints and unfair advantages so every later step can reference them.

What the user gets: a sharp written profile of themselves, including a list of verticals where they have unfair access and a list of verticals they should avoid.

Step 2: Vertical

If the user already has a vertical in mind, the product helps them narrow it from something broad like “fitness” or “B2B SaaS” to the actual unit that wins: vertical x sub-vertical x ICP x specific workflow x AI leverage point.

If they don’t have a vertical, the AI suggests 3 to 5 candidate verticals based on their profile from Step 1, ranked by founder fit, buyer accessibility, and AI leverage.

What the AI does: applies the rule that “I am the best at X” only works if X is narrow enough to actually be true. Forces the user to pick something they could credibly walk into a room and own.

What the user gets: one Vertical Stack written down, defended in writing, with two backup options if the primary fails.

Step 3: Buyer outreach and interviews

This is the heaviest step. The product helps the user find 30 named buyers in their chosen vertical, gives them a Sales Navigator filter, identifies 5 communities where the buyer hangs out, generates a behavioral cold-outreach message, and provides an interview script for every conversation.

The interview script is the bit nobody teaches well. It bans hypothetical questions (“would you use a tool that does X”). It only asks about past behavior (“walk me through the last time you ran into this problem”). It looks for costly action: have they spent money, hired someone, built a workaround, complained loudly. Stated problems are cheap. Revealed problems are signal.

What the AI does: drafts the messages, generates the script, and after every five interviews helps the user build a theme map and identify saturation. When the user has heard the same theme three times in a row, they stop. They don’t stop at an arbitrary number of interviews.

What the user gets: a validated problem statement, a theme map, a list of buyers who took costly action (the warmest leads in the world for the eventual product launch), and a clear go/no-go decision.

Step 4: Framework and expert research

Instead of inventing your own framework, find the named expert in your vertical, study their work in depth, and adapt their framework to your specific ICP and workflow.

The product searches for 5 candidate experts in the user’s vertical who have a real commercial track record (revenue, not just content), a published book or course, multiple long-form interviews, and a paid product the user can study. It ranks them by fit. The user picks one and writes their adaptation plan.

What the AI does: searches the web, summarizes the expert’s framework, identifies the 3 things to keep verbatim and the 3 things to adapt for the user’s specific ICP.

What the user gets: a chosen expert, a clear adaptation plan, and a reading and watching list to consume in the next two weeks.

Step 5: Competitor and website analytics

The user runs my analyzer tool against the top 10 competitors in their vertical. The tool extracts how each competitor positions, prices, sells, and supports.

The product then synthesizes this with the user’s interview themes (Step 3) and their framework (Step 4) to produce a positioning whitespace map. What is no one saying? What is undersold? Where can the user own a corner of the market?

This output is what the user takes into the build phase. They brief their AI builder agent against this positioning, not against a vague feature list.

What the AI does: clusters competitors, identifies the gap, drafts 3 candidate positioning statements, picks the strongest one with reasoning.

What the user gets: a positioning statement they can actually use, a competitor map, a website brief that ties their build back to the buyer voice and the framework.

Step 6: Sales deck, customer outreach plan, and pre-seed investor deck

This is the synthesis step. Everything from Steps 1 to 5, plus the user’s product status, gets assembled into three things the user can take into the world.

The first is a sales deck, a 6 to 8 slide document the user takes to customer conversations. It opens on the buyer’s own pain in the buyer’s verbatim words (from Step 3), names the problem precisely, shows the differentiated solution (from Step 5 positioning), proves the validation (interview themes, costly-action signals from Step 3), names the expert framework basis where it adds credibility (from Step 4), shows pricing or offer, and ends with a clear next step. This deck doubles as a validation-proof document: it shows real buyers said real things, not that the founder thought up something clever.

The second is a customer outreach plan for taking that sales deck into the market. The product looks back at every person the user interviewed in Step 3 and flags the ones to re-engage: the buyers who gave costly-action signals, the ones who asked to be kept in the loop, the ones who complained loudest about the problem the user is now solving. For each, it drafts a re-engagement message in the spirit of “here’s what I built based on what you told me.” It then identifies new potential buyers in the user’s chosen market using the ICP from Step 1, builds a target list, and drafts an outreach sequence framed around the validated problem (not a vague pitch).

The third is a pre-seed investor deck, the standard 12-slide structure (problem, why now, solution, product, market, business model, traction, competition, moat, team, ask, plus appendix). The AI bakes in the non-negotiables a 2026 AI-era investor expects to see: a working demo, a real moat (workflow lock-in or data flywheel, not “proprietary AI”), evals, inference economics, and a buyer-interview tape pulled directly from Step 3.

What the AI does: drafts all three artifacts from the work in Steps 1 to 5. Builds them in plain English. Refuses to pad slides where evidence is missing. Tells the user what evidence they still need before the deck is fundable or sellable.

What the user gets: three finished drafts they can revise, not write from scratch. A sales deck and an outreach plan they can use this week to start closing customers. An investor deck they can take into a pre-seed conversation.

What happens outside the Sprint

The user takes everything above and builds their product and their website. They use whatever AI builder tool they prefer. The Sprint doesn’t help with that part. It would be reinventing what those tools already do well.

When they come out the other side with a working product, a live site, and the three artifacts from Step 6, they have everything they need to either start closing customers or walk into pre-seed conversations.

What if validation fails: the loop

Not every Vertical Stack survives Step 3. Sometimes 30 buyer interviews surface no costly action and no real pain. Sometimes the Scorecard comes in below 65 even after the user is honest about every axis. Sometimes the competitor map shows there is no whitespace worth owning.

When that happens, the tool does not dead-end the user. It loops them back, and it does not make them start from scratch. Everything they have learned (their unfair advantages, their interview themes, their framework knowledge, the vertical they just disqualified) becomes input to the next attempt.

The loop typically lands in one of three places:

Different ICP, same vertical. The pain is real but the user targeted the wrong buyer. Step 1 reruns with a sharpened ICP.
Different vertical, adjacent skills. The vertical does not have buyers willing to pay, but a related one (where the user has similar unfair advantages) might. Step 1 reruns with new vertical candidates suggested by the AI based on what the user has already learned.
Different workflow inside the same vertical. The user picked the wrong job-to-be-done. Step 1 reruns with a different AI leverage point inside the same buyer’s day.

The point is to make a “no” cheap. Most builders ship a doomed product because the cost of admitting they were wrong feels too high. The tool makes pivoting back to Step 1 a normal move, not a failure.

How this fits with everything else

This isn’t built to be the only thing a builder uses. There is a lot of good content, communities, courses, and tools out there already, and the tool points users to them where they are the right call at a given step.

Examples:

For audience and distribution thinking, Greg Isenberg’s Startup Empire, his free workshops, and his community.
For customer-discovery rigor, The Mom Test (Rob Fitzpatrick) and Cindy Alvarez’s Lean Customer Development.
For positioning, April Dunford’s Obviously Awesome.
For pitch-deck structure, the YC Seed Deck guide and the NfX Pitch Deck Library.
For local context, the accelerators, programs, and AI builder communities in the user’s own region.

The tool is one piece of a stack, not a closed system. If the right answer at a given step is “go read this book” or “go to that workshop,” the tool says that. The user gets to the same place, faster, with fewer false confident pivots.

What you walk out with

By the end of the Sprint:

A written profile of yourself and your unfair advantages
A locked Vertical Stack (vertical, sub-vertical, ICP, workflow, AI leverage, moat hypothesis)
15 to 30 logged buyer interviews with verbatim quotes
A theme map of buyer pain
A list of buyers who took costly action (your launch list)
A named expert and an adapted framework
A competitor map and positioning whitespace
A positioning statement you can defend in three sentences
A website brief tied to all of the above
A sales deck you can take to customer conversations to close
A customer outreach plan with re-engagement messages for the buyers you originally talked to, plus a new-contact target list in your chosen market
A pre-seed investor deck you can take into a pitch

Two outcomes are now genuinely on the table: a buyer ready to pay (you have the sales deck and the validation evidence behind it), or a pre-seed conversation that doesn’t flinch (you have the investor deck and the artifacts an investor expects to see). The Sprint doesn’t decide which one you go for. It gets you to the point where either one is real.

How I’m thinking about the AI underneath

A few principles I’d love builders to challenge.

Adversarial by default. Every prompt the product runs is built to refuse flattery, push back on vague answers, and force the user to cite a person, a number, or an artifact. There’s a small “Mini Council” step between Steps 1 and 2 and again between Steps 4 and 5 where the AI plays five different skeptical personas (a seed VC, a churned customer, a competitor founder, a future-you-12-months-from-now, a grumpy product manager) and tears the idea up. The Sprint is built specifically to be the opposite of “great question, here’s why your idea is amazing.”

Behavioral over hypothetical. The customer-discovery industry has been telling people this since The Mom Test came out in 2013. Most builders ignore it. The product makes it impossible to ignore: hypothetical questions are banned in the interview generator.

Saturation over headcount. No “interview 10 people” rule. The user keeps going until the last three interviews surface no new themes. The product helps them recognize saturation.

Verbatim only. Buyer quotes get logged exactly as said. No paraphrasing. The verbatim quotes become the website copy, the positioning, and the deck slides later.

Vertical x workflow x ICP, not just vertical. The Vertical Stack output forces specificity beyond what most positioning frameworks ask for.

Where I want to test this concept

I’m sharing this with anyone using AI to build interesting things, who could benefit from having some direction in how to take what they’re making and turn it into something a customer pays for or an investor backs. If that’s you, or you know that person, please pass it on.

What this concept might be wrong about

I want to be honest about my own uncertainty before asking for feedback.

The 5-step flow might be too linear. Real founders zig-zag. Should the product enforce sequence or let people jump around?
“Find a named expert and mirror their framework” worked for me in a previous business. It might not generalize across all verticals. Some verticals don’t have a named expert with a clean framework.
The product replaces a coach. A coach reads body language and asks the unscripted follow-up. AI may not catch the moment a builder is bullshitting themselves.
The output is artifacts, not a built product. Some builders may finish and still not ship. That’s a failure mode the Sprint doesn’t fix.
The anti-sycophancy posture might feel harsh to some users. Tuning that without sliding back into flattery is a real design problem.

If you read this and have thoughts, I’m easy to find. DM me, comment in the channel, or send me a Loom. I’m trying to figure out whether to build this for real or shelve it.

Thanks.

Scott Mitchell Agentic Partners