Chief Marketing Officer @AIVM_Network | Helping Build @Heybrainio | Senior vibe curator @Chain_GPT | Head of Incubations @ChainGPT_Labs
Joined November 2013
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Today, we're launching AIVM Brain: the first-ever enterprise-grade AI brain
for people & agents.
It combines first-class AI memory, connected to your entire company stack, with governed access built in.
All fully powered by AIVM infrastructure.
Early access → brain.aivm.io
We're entering the next phase of growth at @Heybrainio, and I couldn't be more bullish on the team we're putting together.
We're already serving thousands of users, and now it's time to take our content and distribution to an entirely different level.
I've been trying to get Chris on board for a while now. I've watched his work in Web3 from afar, and he's easily one of the most talented marketers I've come across.
At a time when AI marketing is flooded with recycled launch videos, generic demos and the same narratives on repeat, Chris understands something a lot of marketers overlook:
Great content makes people feel something.
He has an incredible ability to combine creativity, storytelling and human emotion into content that people genuinely connect with.
Now we get to bring that talent into HeyBrain.
Extremely excited to have him joining us!
My next chapter has started.
I’m very excited to share that I have joined @Heybrainio as marketing lead.
We turned Claude into a VC outreach machine.
400+ VCs in our pipeline on day one of pressing go.
Fundraising research is the worst part of raising. Ask any founder. It's weeks of spreadsheets, half-read portfolio pages, and cold notes that all sound like they came off the same template. So we handed it to Claude and just chatted:
→ "Find seed and Series A funds backing AI infra."
→ "Drop anyone who backed a direct competitor."
→ "Rank by thesis fit and recent deals."
→ "Draft a first note to each. Cite why them."
Here's the catch though. Claude on its own would've written me 400 versions of the same generic email. Every VC has read that email. Probably this morning.
The part that made it work was the brain behind it. Before a single prompt ran, Claude already knew our deck, our traction, our ICP, our competitor map and how we actually talk, so every note says why this fund, in our voice, with the source attached.
And nothing goes out without me. I read it, I edit what needs editing, I hit approve.
Weeks of fundraising admin. Done in a day. Kinda unfair, honestly.
Jay retweeted
ChainGPT’s knowledge graph on @Heybrainio is absolutely insane.
Every dot is a piece of our company’s knowledge.
Everything we know, finally connected in one place.
Jay retweeted
Unstoppable combo
Brain + Claude + Higgsfield is insane for creating viral AI UGC.
I ran an AI influencer account for Brain. The results after 2 weeks still don't feel real.
0 → 7,000 followers
750,000 views
10,000+ comments
From 13 videos. Every one of them did between 34K and 200K views.
Here's the setup.
The creator is AI. Higgsfield keeps her face consistent, so she's the same person in video 1 and video 13.
Claude writes the hooks, but never from a blank prompt. It writes them from a brain that already holds:
→ 52 viral reels we broke down hook by hook
→ The formats that pulled 280K to 1M+ plays in our niche
→ Our real product screens, so every demo is the actual product
That's all I gave it. Research, hooks, product screens.
Every video I posted ran the same recipe. A 3 second hook from the creator ("Wasted 10hrs on Claude until I found this"), a screen recording of the real thing, then "comment BRAIN for the link".
Only the first 3 seconds ever change.
Here's the catch. Anyone can make an AI face with Higgsfield now, so the face isn't the edge.
The edge is the brain behind her. When your AI starts from what already went viral, the hooks land on the first try.
I wrote up the whole playbook: the research, the hook formulas, the prompts, and how the creator stays consistent.
Brain + Claude + Higgsfield is insane for creating viral AI UGC.
I ran an AI influencer account for Brain. The results after 2 weeks still don't feel real.
0 → 7,000 followers
750,000 views
10,000+ comments
From 13 videos. Every one of them did between 34K and 200K views.
Here's the setup.
The creator is AI. Higgsfield keeps her face consistent, so she's the same person in video 1 and video 13.
Claude writes the hooks, but never from a blank prompt. It writes them from a brain that already holds:
→ 52 viral reels we broke down hook by hook
→ The formats that pulled 280K to 1M+ plays in our niche
→ Our real product screens, so every demo is the actual product
That's all I gave it. Research, hooks, product screens.
Every video I posted ran the same recipe. A 3 second hook from the creator ("Wasted 10hrs on Claude until I found this"), a screen recording of the real thing, then "comment BRAIN for the link".
Only the first 3 seconds ever change.
Here's the catch. Anyone can make an AI face with Higgsfield now, so the face isn't the edge.
The edge is the brain behind her. When your AI starts from what already went viral, the hooks land on the first try.
I wrote up the whole playbook: the research, the hook formulas, the prompts, and how the creator stays consistent.
Millions of jobs will just disappear and 99% ppl have NO idea.
Jay retweeted
We've just witnessed the future of how you can track your AI spend across agents
This is absolutely insane 🤯
Jay retweeted
We built Brain because we needed it.
Three companies, overlapping teams, and every AI session starting from zero. Re-explaining the same context, every day, to every model.
The hard part was never search. It was letting people and agents reach company knowledge without quietly handing everyone access to everything.
That's what shipped.
Introducing @Heybrainio, the shared AI brain for you, your team and your agents!
AI is moving from isolated sessions into persistent, multi-agent systems.
Brain gives humans and agents a shared operational layer:
→ persistent memory across sessions
→ shared skills across the team
→ governed context + identity-aware access
→ MCP access for agents
→ shared state that compounds as people and agents work
The bigger unlock is multiplayer AI.
A human can teach the Brain once and every agent can use it.
One agent can create context another agent picks up later.
Teams stop rebuilding the same knowledge inside isolated AI sessions and start operating from a shared intelligence layer.
Human ↔ agent.
Agent ↔ agent.
Team ↔ Brain.
If you’re a solo builder, a small team, or a large enterprise and want to get a Brain running, DM me.
Jay retweeted
Today, we’re launching Brain into general availability.
One AI workspace for your entire company, people, agents, models, tools, and knowledge, all working together with permissions, privacy, and governance built in.
Multiplayer AI is now open to everyone.
haven’t used Devin and probably never will
I still don’t see what it gives me (or our team) that Claude Code + Hermes agents can’t already cover
no hate to Devin or anyone using it
I just haven’t seen the capability gap that would make me switch
Devin is the best software product I have ever used hands down
We are:
- 2 veteran engineers (inc me) and 1 PM
- 100% code is generated by Devin
- 7x the pace of pre Devin
- $8M ARR now
: )
if you’re a founder and you don’t use your own product every day, that’s a red flag
you HAVE to be your own harshest power user
agree with Mark here:
this is why I think harness quality eventually matters more than obsessing over which frontier model is #1 this month
your workflows, context, tools, evals + traces compound with every production run
that accumulated operational knowledge becomes the real asset
To truly understand AI agents, you need to understand the harness. And it's not the model.
I went deep on how a working agentic system actually gets assembled, and it clicked. Here are the notes:
Easy Mode: WTF is a harness
- The harness is everything wrapped around the model that turns a chatbot into an agent that does real work
- An agent is not a model. It's a controlled workflow: trusted context + bounded tools + evaluation + human judgment + operational ownership
- The model is the smallest, most swappable part. The harness is all the rest
- Recipe is simple: instructions + scoped context + tools + a verifier + guardrails
- Example: a research agent that answers an operational question. It confirms who's asking, plans a bounded analysis, pulls only approved data, runs trusted calculations, cites its evidence, and stops when confidence is too low
- That's the whole point of a harness. It makes the answer traceable and safe instead of plausible prose
Hard Mode: WTF is actually inside it
- A working agent sits inside 6 layers, each answering one production question
- Trigger: work starts from an event (a file lands, a message arrives, a schedule fires), not a human pressing a button
- Orchestration: the loop, memory, retries, loop limits. How far the agent is allowed to go is a config setting, not code
- Tools: numbers that must never vary run as fixed logic behind the agent, so it returns the same figure every time. The model doesn't improvise your KPIs
- Trusted context: where truth lives and what the agent is allowed to see. This is ~80% of agent success. Context quality is the ceiling, not model power
- Control: golden sets, guardrails, approvals. The agent advises, a named person decides
- Runtime: traces, cost dashboards, audit. Once this exists, a model swap is just configuration
God Mode: WTF makes the harness the moat
- The durable asset is the harness: workflow knowledge, tools, context, evals, controls. Models and platform services change underneath it
- Hyperscalers give you the foundation (hosting, identity, networking). They don't give you your business-specific harness. That's the source of advantage
- Improvement is a loop: real production runs, corrections become new tests, the eval set and the agent both get sharper
- Harness engineering is the cheap place to start: tweak prompts, tool definitions, model choice, model combos, long before you fine-tune anything
- Traces are the receipts. See a bad outcome, read the trace, find the wrong step, change the harness so it never repeats
- Highest-leverage act in the whole thing: a human writing down what good looks like. Everything else compounds on top of that
The model gets the hype. The harness gets the results.
79% of teams already have company knowledge spread across 2+ systems.
at the same time, 57% of AI-fluent teams are already deploying their own agents + skills.
those two curves are about to collide pretty hard.
agents can only be as useful as the context they can reliably access.
if your company knowledge is fragmented, stale or permissioned differently across 10 tools, your agents inherit every one of those problems.
this is basically why we started building Brain.
