A community for tech leaders who want to level up, connect, and have a little fun.
We built the event we’d actually want to attend: an ongoing monthly series and community for CTOs, engineering leads, and technical founders. And if you’re going to come out for the evening with us, you might as well have a good time. That’s why we start with an icebreaker or game, then we’ll hear from a real practitioner for 30 minutes, followed by plenty of time for networking, drinks, and apps (the kind you can eat). We look forward to seeing you.
We’ve all been in a great room – the kind where the conversation keeps going well past when it was supposed to end, and you leave with two or three connections that actually mean something. Those rooms don’t happen by accident. They happen because someone put the right people together and gave them something real to talk about from the minute they walked in.
“Everybody’s got a chatbot on their roadmap. They’re not seeing the whole picture because they can’t see it.”
– CTO & AI advisor, 26-portfolio growth equity firmThe panels aren’t working. The sponsored thought leadership isn’t working. What actually works is putting sharp people in a room, giving them something to talk about – something that isn’t a business card exchange – and then getting out of the way. That’s what Actual Intelligence is built to do.
So we start every session with a game. Not a trust fall. A murder mystery – where talking to strangers is literally the only way to solve it. Suspects are planted in the audience before doors open. Paul sets the scene, announces the crime, and gives the room 30 minutes to find the culprit. You have to introduce yourself to do it – that’s the whole point. By the time the speaker takes the floor, everyone’s already laughed together. That’s not an accident. That’s the whole design.
The mystery scenario changes. The speaker changes. The topics change. But the structure stays the same – because it works. Short enough to respect your evening, open enough to let the real conversations happen.
Every session opens with a tech murder mystery. Paul sets the scene and plants suspects in the room. You have 30 minutes to find the criminal – which means introducing yourself to everyone. The crime scenario changes each time. The game is always the same.
One practitioner. One topic they’ve actually lived. No slides, no vendor pitch – just an honest account of what happened, what they learned, and what they’d do differently. The topic rotates every session based on what the room needs to hear.
Open networking with the speaker, the host, and the room. The energy is already there from the first two parts. These conversations tend to keep going long after the venue closes.
The people on stage have actual receipts. They’ve hired the engineers, made the calls under pressure, and lived with the outcomes. No talking heads. No sponsored speakers. The keynote slot is programmed when the right person and the right topic align – not when the calendar says it’s time.
Army veteran, DC entrepreneur, and technology services executive. Co-founded Victory Square Partners in 2019 and has grown it to 200 team members and back-to-back Inc. 5000 rankings. Member of Mindshare (class of 2024).
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Started as a software engineer, rose to architect, served as CTO of Parature through its acquisition by Microsoft. Now leads advisory engagements helping growth-stage companies build AI roadmaps and ship faster without sacrificing judgment.
LinkedInWe program the speaker when the right person and the right topic align. The keynote for the next session is in final confirmation. Get on the invite list to be notified when it’s announced.
Get notifiedWe don’t lock the topic in advance. Every subject here came directly from CTOs, engineering leads, and technical founders on calls we run every week – in their own words, describing their actual problems. We pick the topic that matches the room we can convene and the speaker who lived it. No theme quarter. No content committee. Just what the room actually needs to talk about.
Every AI initiative that stalled in the last 18 months stalled for the same reason – the system underneath it was never built to move. Stored procedures, manual release gates, untrusted internal APIs.
If you ignored CI/CD a decade ago you survived. If you ignore AI infrastructure debt right now, you don’t. The investment is small. The compounding gap isn’t.
Feeding AI into a broken operating model doesn’t accelerate the business – it accelerates the dysfunction. Conflicting ground truth, accountability gaps, decision latency.
The gap between “AI on the roadmap” and “AI in front of customers” is where most companies are quietly stuck – and the board doesn’t know it yet.
In-house AI development sounds like control. It costs three teams, two years, and a talent market that doesn’t favor you. The founders who killed the experiment can explain why.
One technically-fluent leader carrying the whole AI transformation isn’t a strength – it’s a single point of failure. What happens when they’re saturated, recruited away, or out for two weeks?
Junior staff want Claude turned loose on everything. Senior leadership wants guardrails. The fight inside your firm is the same fight inside every firm – and most companies are losing both sides of it.
The pricing models procurement knows how to evaluate were built for a world that doesn’t exist anymore. Headcount has no relationship to outcomes. T&M is breaking on both sides of the table.
If you sell delivery hours today, the AI-era version of your pricing model is a different model – not a discount on the old one. The founders who already made the transition can tell you what broke first.
There is more budget for AI delivery than at any point in the last decade – and almost nobody in the buying seat trusts the vendors in front of them. The buyer-side post-mortems are damning.
Hallucinated citations in expert-witness reports. Fabricated case law in legal briefs. AI in regulated domains isn’t an efficiency tool – it’s a liability surface. What changes when the cost of being wrong is professional sanction?
You can run the model. You can show the output. But can you explain it upward – to the board, the investors, the regulators? Most executives can’t, and it’s stalling internal AI adoption more than any technical limitation.
You own the data. You have the customers. You should be defensible. So why is a competitor with a $9.99 LLM license eating your lunch? The story of data assets that never became products.
Federal AI guidance. Extended Producer Responsibility. State-by-state compliance fragmentation. The regulatory clock is moving faster than the tooling roadmap – and “we’ll get to it” stopped being a viable answer two quarters ago.
The shift from artisan AI delivery to industrialized AI delivery. Why “we use Claude for everything” is not a strategy. What the workforce, the workflow, and the leadership look like when AI work is treated like a manufacturing line.
The new bottleneck in AI delivery isn’t engineers – it’s the people who can translate executive intent into agentic specifications. They don’t have a job title yet. They’re carrying the whole offering on their backs.
Your pricing model lives in a document. Your pricing realization happens wherever the relationship allows. Until a pricing authority exists separate from the account owner, outcomes pricing drifts back to hourly billing on every relationship-sourced deal.
A $2B SaaS company watching purpose-built AI tools replace its product one workflow at a time. The pattern reshaping every SaaS market – not as a frontal assault, but as a flank.
We’re intentional about who gets in – because the quality of the room is the whole point. If you lead a technical team, own an AI roadmap, or are actively building something, you’ll find your people here. The more honest you’re willing to be about what’s actually going on in your organization, the more you’ll get out of it.
CTOs, VPs of Engineering, heads of product, and senior architects at growth-stage and mid-market companies. People who own a technical team, an AI roadmap, or a delivery problem they haven’t solved yet. This is the core of the room.
Founders and co-founders who came up through engineering and are now navigating the AI build-vs-buy question with real money on the line. They bring a different kind of urgency to the conversation – and a different kind of honesty.
Fractional CTOs, technical advisors, and PE or VC partners who see the same AI implementation failures across dozens of companies. They come because the cross-pollination is the whole point – and because they need the peer network too.
You won’t get a drip sequence. You’ll hear from a real person – usually within 48 hours. Whether you want a seat at the next session, a conversation before it happens, or a slot on the stage to tell your own story, there’s a path below. Interested in co-hosting or bringing your community? Reach out the same way.
Get on the invite list. When the date is locked and the lineup is confirmed, you’ll be the first to hear about it. Tell us which topics you’d want in the room and we’ll make sure the programming reflects it.
You’ve got a specific situation – an AI initiative that stalled, a team decision you’re not sure about, a build you’re about to start. A 30-minute call before the next session puts you in the room better prepared and better connected.
You’ve lived one of the topics on the menu and you’d consider telling the real version from the stage – not the polished case study, not the roadmap slide. No deck required. Just what happened, what broke, and what you’d do differently. Pitch it here.
You have a specific situation worth a real conversation before you show up. Tell us what you’re working on and we’ll schedule a 30-minute call before the next session.
No slide decks required. Just the truth about what happened and what you’d do differently. Pitch it here and we’ll set up a 30-minute prep call.
