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The Context Layer For Revenue.

United States
Joined December 2025
Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)Photo by ClearskiesAI (@ClearskiesAi)
Replies here kept asking three things about Deal Bot: does a human sign off on each exception, is there an audit trail, and what happens when the terms change after approval. We built a version that answers all three. A named person approves. Every fact in the packet links to the call, email or CRM field behind it. Each approval is tied to the proposal version, so new terms reopen it. Runs on @ClearskiesAi: x.ai/bot/4gX322bIrhcyhAR_J-E… teapaw.org/bot/status/21151307600…
Our sales operations team built Shared Bots that help reps move deals faster. Account Intel Bot updates the CRM after calls. Quote Bot prepares proposals and order forms. Deal Bot reviews non-standard terms and routes exceptions for approval.
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The greatest salespeople knew their customers. Now your AI can too. Grok @Bot + Clearskies, the context layer for revenue. Get the plugin link in the comments.
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ClearskiesAI retweeted
Getting a team using AI in single-player mode is mostly easy now. And products like @bot are making a huge difference. Making agents multi-player, doing meaningful customer work for the whole team, is the hard part. Why and how to close the gap, in The Signal w/ @brendanjshort: thesignal.club/operationaliz…
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The Context Layer for Revenue now includes Intercom. Support conversations now sit on each customer account next to CRM, calls, and email. Before a QBR, ask Claude, ChatGPT, Gemini, or Grok Bot what's open in support. Unlimited GTM use cases. Try it out: app.clearskies.cc
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The Context Layer for Revenue now includes @github. Issues, PRs, and releases now tie to the customer accounts they affect. Before a renewal, ask Claude, ChatGPT, Gemini, or Grok Bot if the customer's bug shipped. Unlimited GTM use cases. Try it out. Build with Clearskies free and connect GitHub: app.clearskies.cc
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We concur. To plus this: Buy your infrastructure, build and OWN your intelligence.
"Buy your infrastructure, build your intelligence" -@kylecnorton In the AI-era, it's no longer about "build vs buy." It's build AND buy. Like a sandwich...
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ClearskiesAI retweeted
5/ The companies that pull ahead will operationalize AI across the whole revenue org, not a few power users. @ClearskiesAi gets you there faster. No per-seat licenses. Free to start: clearskies.cc If this is top of mind, DMs are open.
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Give ChatGPT real revenue work. Clearskies is now in the ChatGPT plugin directory. Type @Clearskies to run pre-call prep, pipeline review, and deal status on your full context: CRM, calls, email, and Slack. One click, no setup.
🤖 Made with AI
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Would you stake the number you commit to your board on a Claude or ChatGPT answer? Would you coach a rep on it? Not while it's stitching it together from one tool at a time. Wrote up how to make revenue AI trustworthy, and where doing it yourself breaks down: clearskiesai.substack.com/p/…
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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: clearskiesai.substack.com/p/…
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Every revenue team is going to have a brain. The only question is whether you build it yourself or let Clearskies build the context layer for you — so your team spends its cycles on outcomes, not infrastructure.
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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.
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ClearskiesAI retweeted
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.
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ClearskiesAI retweeted
That customer's vision? That's exactly what @ClearskiesAi is. A unified Customer Context Graph — calls, CRM, email, Slack — with GTM Agents built on top. So "just ask" actually works.
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