Pouyan Salehi

CEO and Cofounder of @Scratchpad. Previously at @PersistIQ (YC S14). Grateful to be here.

[Pouyan Salehi @psalehi]

@joshelman @a16z Awesome to see - congrats!

[Pouyan Salehi @psalehi]

@eoghan @salesforce @fin_ai Incredible what you and the team accomplished! Nicely done.

[Pouyan Salehi @psalehi]

You could have this live by tomorrow afternoon.
- AI forward system infra for the GTM org (unified customer context across all your data, accessible to any LLM, for the entire GTM org)
- "second brain", a file structure system to capture your process and continually update it with learnings
- as for getting Claude co-work for everyone, that's mostly solved by the first item (a unified context graph connected to Claude), then supplemented with specific skills and workflows for each role.

Check out https://t.co/Qgah2wGvvZ. We've done this for 10+ companies in the last 3 weeks and can work directly with your team as well.

[Pouyan Salehi @psalehi]

@OpenAI @AnthropicAI 5/ That’s why we’re excited to introduce NexusGTM. We help revenue teams become AI-native in 4 weeks. Built for CEOs, CROs, and sales leaders who want AI embedded into how revenue work actually happens. https://t.co/q7TIzG0BUj

[Pouyan Salehi @psalehi]

AI transformation in sales is harder than it looks. In building @Scratchpad, I’ve worked with thousands of revenue teams. One thing is clear: most teams are still early in their AI journey.

[Pouyan Salehi @psalehi]

@OpenAI @AnthropicAI 4/ For sales, that means choosing the right use cases, shaping company data and workflows into context AI can reason over, evaluating quality, building feedback loops, and redesigning how revenue work gets done around AI.

[Pouyan Salehi @psalehi]

@ryaneshea This looks great! Nice work

[ClearskiesAI @ClearskiesAi]

Right now, someone on your revenue team is building a Frankenstein.

• Sheets + Claude + SQL contraptions.
• Brittle n8n workflows.
• Six tools open just to get a daily CRO brief.

Connectors alone don't fix it. Markdown files doesn't either.

What's missing? Context.

If your sales AI is still guessing, this is why:

https://t.co/ZDWoESclqy

[Pouyan Salehi @psalehi]

@danpres This looks incredible, congrats!

[Pouyan Salehi @psalehi]

https://t.co/tr2lKbk3sW

[ClearskiesAI @ClearskiesAi]

Models got really good, really fast. But, ask one anything specific about your business and watch it guess based on very limited knowledge it has.

That's a context problem, not a model problem and real work runs on context. That's why we're building the brain for revenue in Clearksies — the context layer for Revenue AI.

[Pouyan Salehi @psalehi]

A big congrats to @sygaldry_tech on their massive raise! AI progress is bottlenecked by power and cost. Sygaldry is building quantum-accelerated servers to deliver more compute per watt than GPUs alone, bending the cost and energy curve for AI. This is one of the most important problems to solve right now, and they're looking for exceptional people to help solve it. Exceptional team with open roles
https://t.co/4ugNfr3DyV

[Pouyan Salehi @psalehi]

And @karpathy made it even easier to apply this concept today with the idea in a gist format: https://t.co/ZcEY3bKaqu

[Andrej Karpathy @karpathy]

Wow, this tweet went very viral!

I wanted share a possibly slightly improved version of the tweet in an "idea file". The idea of the idea file is that in this era of LLM agents, there is less of a point/need of sharing the specific code/app, you just share the idea, then the other person's agent customizes & builds it for your specific needs.

So here's the idea in a gist format: https://t.co/NlAfEJjtJV

You can give this to your agent and it can build you your own LLM wiki and guide you on how to use it etc. It's intentionally kept a little bit abstract/vague because there are so many directions to take this in. And ofc, people can adjust the idea or contribute their own in the Discussion which is cool.

[Pouyan Salehi @psalehi]

AI has made startups incredibly fast at shipping. A tiny team can build what used to take an entire org.

But shipping speed isn't actually the advantage anymore. Everyone has access to the same tools.

The real advantage is learning speed. How fast you take in signals from customers, the market and turn them into decisions. That's what finding product-market fit actually is. A learning loop.

Most of us are still running that loop manually.

Inspired by @karpathy's post on LLM knowledge bases, I pointed this at PMF search.

[Pouyan Salehi @psalehi]

Karpathy's idea: collect raw data → LLM compiles a wiki → query against it → file outputs back so thinking compounds.

I applied this to finding PMF. Every customer call, competitive signal, market article, half-formed hunch goes into raw/. An LLM compiles it into a living strategy: positioning, buyer profiles, evidence, hypotheses.

Then it works for you:

"Where is our positioning weakest?" answered across all signals
Hypotheses tracked with real evidence for/against
Health checks catch contradictions and stale assumptionsEvery query gets filed back. Thinking accumulates.

We're a few days in. Already catching things we would have missed. A customer quote that contradicts our positioning, a pattern across calls we hadn't connected.

The old way: call → manual summary → update docs → context resets by next week. The new way: nothing resets. Signals compound.

The shift isn't "use AI to write docs." It's stop keeping strategy in your head. Feed the system, let it synthesize, decide from what it surfaces.

Fast flowing water finds the path.

[Pouyan Salehi @psalehi]

"Leverage is no longer about how much one organization can produce; it’s found in how much context people, teams, and institutions can coordinate across humans and agents.” - this is spot on, from @gabepereyra https://t.co/7iB4tJ72sR

[Pouyan Salehi @psalehi]

AI Ops is going to be one of the most important roles at companies. Context engineering. Agent orchestration. Debugging. Token mgmt. And so much more. The companies that are seeing meaningful impact across the org have at least one person focused on this.

[Pouyan Salehi @psalehi]

Giving LLMs the right context is one of the biggest gaps I'm seeing when deploying AI in sales (for meaningful use cases and driving high adoption across a team). @JasonSCui and Jennifer Li wrote a great piece that describes this challenge in more detail. And it's aligned with @ClearskiesAi is building - Context Infrastructure for Revenue teams that want to build with AI. Exciting times ahead.

[Jason Cui @JasonSCui]

https://t.co/nfnTaP1zLD