Matt asked to see Claude Code, I Showed Him How to Get Outcomes Instead
An hour. Three tabs: every Chili-palooza attendee scored, every brand from my playbook archive, his Monday call list.
My friend Matt Braley was at Chili-palooza last week with me.
He texted me. He wanted to see Claude.
Most people, when they say that, they want a demo. Watch me type a prompt. Watch the cursor blink. Watch a paragraph of marketing copy appear. Then they nod. Then they go home and don't change anything.
That's not what I do anymore.
I told Matt to come over. We sat down. I opened my laptop. I said, "What do you actually need."
He's a CRO. He sells big-deal vertical SaaS, and he advises a portfolio of AI companies. He was at a conference and wanted to follow up with people. He wanted leads — not in general, leads scored against him.
Sixty minutes later he walked out with one Google Sheet. Three tabs. Every tab was a working list he could call on Monday, all three graded against the same one-page rubric of who Matt actually is.
This is what showing Claude looks like now.
The three tabs
First, the rubric. Before any of the three tabs, we built one file: matt_profile.md. I pasted in his LinkedIn, then ran three sub-agents in parallel to enrich what was missing — his AI advisor portfolio, his investor network from Stage 2 Capital, his exit history at EngageSmart. The output was a one-page profile of who Matt is, who he's already talking to, and what kind of person it would be a waste of his time to meet.
Every score on every tab grades against that file. Same rubric, three populations. That's the only reason any of this means anything.
Every attendee at the conference, scraped and enriched
Matt sent a screenshot. Some WhatsApp group from the conference had dropped a link: ████████████████████████████.lovable.app. Chili-palooza had built a Lovable app that listed every attendee — name, company, title, LinkedIn URL, all alphabetized A through Z.
Claude OCR'd the URL out of the screenshot. Loaded the Lovable app. Walked every letter section A–Z. Pulled 138 attendees into a CSV with name, title, company, and LinkedIn.
Then enrichment. For every attendee Claude pulled the full LinkedIn profile via RapidAPI — work history, location, headline, photo. Then the company side: what the company does, headcount, funding stage. Then FullEnrich for cell phone and personal email on every row.
That's one tab. 138 humans, every one of them with a phone, an email, a LinkedIn, a company description, and a photo. Matt didn't make this. He didn't pay for this. Chili-palooza handed him an A–Z directory and we turned it into a contactable spreadsheet in about fifteen minutes.
Every Series A–D vertical SaaS startup that raised in the last year
This tab has nothing to do with the conference. This tab is about the rest of Matt's year.
I host 501 public go-to-market playbooks at playbooks.blueprintgtm.com. Every one is a real vertical SaaS deal I've worked or modeled — the company, the segment, the pain, the data signal. Three years of pattern library.
I asked Claude: take all 501. Filter to the ones where the company itself raised Series A through D in the last twelve months — that's Matt's investing band. Find the CEO, the founder, the CRO, the president. Find their email. Find their phone. Score every one of them against Matt's same rubric.
It's an eight-stage pipeline. Each stage writes a checkpointed CSV so I can re-run any step. Stage 1 loads the 501. Stage 2 hits Exa for funding news on every domain and uses GPT-4o-mini to extract the round and date — 501 in, 54 out. Stage 3 resolves each surviving domain to LinkedIn via Blitz. Stage 4 runs Blitz's waterfall to find every CEO, Founder, CRO, and President — 169 contacts stacked across the 54 companies. Stage 5 enriches each contact's LinkedIn profile via RapidAPI. Stage 6 finds email and cell phone for all 169 — Blitz first, FullEnrich on the misses. Stage 7 grades every one with Sonnet 4.6 against Matt's rubric — fit score, fit band, the talking point. Stage 8 writes a tab on the same Google Sheet.
Matt's not getting a list. He's getting an ordered queue. The top is the call he should make Monday morning. The bottom is the people he should skip. Every row already has the talking point. He doesn't have to think about it. He has to dial.
Every conference attendee scored against Matt — five swarm agents, six minutes
Back to the 138 attendees. Out of 138 people, who should Matt actually walk up to.
This is where I stopped touching the keyboard and let agents do it. Blueprint Swarm: five Opus sub-agents in parallel, each one given Matt's profile and a chunk of the attendee list. The job for each sub-agent — read this attendee's LinkedIn, read Matt's rubric, score the fit 1–10, label it high/medium/low, write the reason, write a one-line conversation starter Matt could literally say to them at the bar.
Five agents, 138 attendees. About six minutes wall-clock.
Output: 33 high, 65 medium, 40 low. Every row had a paragraph of reasoning and a tailored opener. "Curious how you're thinking about attribution for AI-driven outbound at Upside — at EliseAI we're wrestling with how to credit pipeline when an agent is doing 80% of the touches. Where does Upside draw the line?" That kind of opener. Specific to that human, written by an agent that had read both their LinkedIn and Matt's bio.
Then Claude built a mobile-responsive HTML leadbook out of it. Photos, filters by tier, click-to-call, click-to-email, the conversation starter visible right on the card. Modeled after a leadbook I'd built for a previous client. Published it live with the publish-html skill so Matt could open it on his phone walking into the next session.
That's the third tab — same data, ranked, with the talking point.
What this is not
This is not a demo.
A demo is when you show someone the tool and they leave with a story. "Jordan showed me Claude. It was cool."
This is when you show someone the tool and they leave with the work. "Jordan and I built three lists. I'm calling forty of these people on Monday."
The difference is whether the thing you made survives the meeting.
Most demos don't. The screen goes dark. The slides go away. Nothing changes on Monday. ← OPUS LOVES THIS FUCKING PATTERN!
What we did survives because Matt has it on his laptop. He has the GitHub repo — I invited his braley-ai handle so he owns the code. He has the Google Sheet shared to his email. He has a published HTML leadbook on his phone. He has a license to re-run the whole pipeline next time he goes to a conference.
The asset doesn't depend on me being in the room.
The hour
I want to be specific about the hour.
We didn't write any code by hand. I didn't pull up a notebook. We didn't open a Python file together.
I told Claude what we were doing. Claude scraped the Lovable app. Claude built the enrichment pipeline. Claude spun up the swarm. Claude wrote the HTML leadbook. Claude built the eight-stage playbook pipeline. Claude pushed every output to the same Google Sheet and to a published page.
I sat next to Matt the whole time and narrated. "OK now we're scraping the directory. Now we're enriching contact data. Now the swarm is reading his profile. Now we're scoring 138 people against him in parallel."
Matt didn't need to learn anything. He needed to see the shape of it.
That's what showing Claude is. You sit next to someone. You tell the agent what you both want. The agent builds the thing. The other person watches the shape of the work and goes, "Oh. That's how this is supposed to feel."
Why I'm writing this down
Because most of you, when somebody asks to see your tool, you still do a demo.
Stop.
Ask them what they need. Build it while they watch.
If you can't build it in an hour, your tool isn't ready. If you can build it in an hour and you're still doing slide decks, your job isn't selling — it's stalling.
The shift is small and total. Demos are about you. Builds are about them. One ends with a thank-you email. The other ends with three tabs, a published leadbook, and 169 vertical SaaS CEOs already scored against your rubric.
Matt's calling forty people on Monday. He didn't see Claude. He used it.
That's the only version of "showing Claude" I do anymore.
What Annual Adds
This one was free. Paid gets the build. Annual gives you the tools that run it.
Every tool I ship. Edge Copilot installs to your Claude Code — talk to all my knowledge, every method, every data source. Current: Edge Copilot, AutoClaygent, Agent 7, Who to Target and What to Say, Blueprint Cloud, Technology Finder, Video List Extractor, Competitor Monitor. Whatever ships next is included.
All 3 courses: GTM Engineer, Pain-Qualified Segments, The Inversion.
Weekly office hours.
Run /edge install agent-swarm once your license key arrives — the swarm I used to score Matt's 138 attendees drops into your Claude Code in one command.
License key hits your email.
→ Go annual — $2,499/yr · Start at $50/mo (most readers start here)