Founder - building managed company brains @ singlebrain, ad agency @singlegrain, Investor. Member: @YPO Beverly Hills Podcaster: Marketing School, Leveling Up

Joined April 2010
How to make your Grok Bots stop repeating the same mistakes Every correction becomes a rule the bots read before they work. 190 corrections in 3 weeks turned into 99 rules The full loop is in the image. How it works: 1. Log every correction the same day > the exact words, quoted > the asset it was about > the rule it maps to If a rule already covers it, mark it a repeat and make that rule more concrete 2. Give every rule an ID, a why and a tag > the rule in one line > the data or feedback behind it > which bots it applies to: X, newsletter, LinkedIn, graphics Every bot reads the shared rules plus its own tag before it starts work 3. Let results decide which rules stay > X posts get checked at 24h and 72h against the 30-day median > 2x the median, or bookmarks at 1% of impressions, is a win > under 0.75x is a loss > 3 straight losses in one format pauses it for 2 weeks 4. Run a daily check Our Bot Improver checks the rules every day. The daily loop check flags anything slipping, like a weekly Article with no approved draft by Wednesday 5. Rewrite the rules every Monday Our Chief of Staff bot fills a 30-minute review from the logs, then we confirm, add or retire rules. The number we watch is repeat feedback. The target is 0 Start with the last 3 things you corrected your AI on and turn each one into a rule
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How to stop Claude, ChatGPT or Grok Bot from shipping AI slop SEO pages (prompt included): Our Grok Bot's SEO drafts went from 58 to 86 out of 100 once our editor's notes became the grading rubric. This is the rubric we grade ours against. How it works: 1. Score every draft out of 100 on 8 checks The first 6 came from our editor and our grader. The last 2 are standard SEO practice. The points are my split > title pays off its promise (15) > every stat named and linked (15) > human voice, first person is fine (20) > every tool explained (10) > no fake or anonymous reviews (10) > passes Yoast's SEO checks (10) > answers the search in the first 100 words (10) > one first-hand detail (10) 2. Paste the grader prompt into Claude or ChatGPT It's in the first reply. Put your draft under it > it scores each check > it quotes the sentence that cost points > it gives you the 3 fixes worth the most 3. Fix and re-score Under 70, rewrite it. 70 to 89, fix what it flagged. 90 and up, ship it Run it again after every fix. Plug in any anti-slop skills your team already has 4. Let the person closest to the work own the rubric Ours is our editor. Her first note on the bot's drafts: "to be honest, this looks very AI" Give one person edit access to the rules first. Everyone else watches until they hold up Start with a page you already published and see what it scores -- The Prompt. Copy everything below into Claude or ChatGPT and paste your page at the end: "You are a strict SEO editor. Check the page below against these rules. Mark each one PASS or FAIL, quote the line that fails it, and write the fix. Any FAIL means the page goes back. 1. Title pays the promise. If the title promises a number or scale ("thousands"), the body shows a real number, or the title changes. 2. Named tools get a what + why. Every tool in the title or body gets one plain line on what it is and how it's used here. 3. No unverified case blocks. Remove anonymous reviews, quotes or case studies unless there's a real source and date. 4. Named stats are hyperlinked on the anchor (source name + date), not a bare "Source: ...". 5. Anti-robot voice caps. Max 1 colon-thesis opener per page. Hard limit on "do not / is not" lines and "It is not X. It is Y." antithesis. No filler slang. 6. Figure lead-ins. Every chart or image section gets one transition sentence under the header before the asset. 7. Tip piles need H3s. No disconnected tips under a fake "checklist" heading. 8. SEO gate. A primary keyword. Title tag of 65 characters or less (fail over 75). Meta description states the reader's job and pain. 9. Timestamped embeds. If a video says it, embed it at the timestamp instead of paraphrasing. Baseline: 1,500+ words, 6+ H2s, 3+ H3s, stats cited from the last 30 days, no invented numbers, video timestamps, a search-shaped headline. Don't lock these, just flag them for a person: Title Case on H2/H3s, image captions, table of contents placement, first person vs third person. Then grade the page from 1 to 100, list what would move the score most, and rewrite the intro."
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Marc Andreessen says the gap between what AI-native startups and incumbents think AI can do is the widest he’s ever seen: "The AI-native early stage startups have just a completely different view on what they can do with AI than the typical incumbents in almost any industry, almost without exception." "AI is just racing ahead in capability even week by week... There are going to be a lot of industries that are really up for grabs in a fundamentally more profound way than maybe has been the case in the past." "The founders are gonna have a level of superpowers coming from the use of these tools and these technologies that they just simply haven't had in the past... Had I had Astra and Netscape in 1994, like, oh my God. Like, Ben, what would you and I have been able to do at Netscape?" "Those entrepreneurs are gonna color way outside the lines. We already see this. They're not gonna think of themselves as like, 'I'm just a software company,' or, 'I'm just a hardware company,' or even, 'I'm just an AI company.'" @pmarca @bhorowitz
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You have to pre-screen aggressively for AI-nativeness in your hiring process now. Apologize upfront for being direct and say you are looking for a very specific individual. The person in the image has ‘experience’, but unfortunately lacks the adaptability and curiosity to make it work with us. Remember, you’re hiring the top .2% of people right now who know how to leverage AI for work. It’s harder, but it’s worth it. See the video for our Grok Bot talent @bot.
If you want to hire AI-native talent, use this Grok @bot. Only .2% of people are considered 'AI-native', so how do you find them? Hint: it's not going to be traditional talent managers because they're just too slow. Our talent bots: • Manage our applicant tracking system (ATS) • Pre-screen based on our criteria (e.g. 2 promotions ideally at 2 different companies; avg 3 year tenure) • If they're interested, we send 7 pre-screening questions and apologize in advance, saying we are only looking for AI-native individuals • Then we use Jev to eval based on their responses • Best ones get shortlisted for a real screening call This re-imagines the hiring process by saving both sides a ton of time. Around 37.5% of people respond to the 7 pre-screening questions, and only 4% pass the screen In the video below, you’ll see the actual workflow and the early report, including zero graded passes and zero bookings on a new run. Just remember that someone still has to check the permissions, missed runs, and missing records, then keep improving it. It ain't all sunshine and rainbows right now, but it will be soon. Bot link in first comment. 00:00 Why talent is the X factor 01:19 How Grokbot and Jev fit together 04:02 Inside the recruiting workflow 05:43 Sourcing, screening and outreach 08:00 Why I keep the hiring decision 10:54 The seven screening questions 14:00 Reading the funnel report 15:13 Why you need a bot manager 15:47 What’s working 16:10 What still needs work
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Steal this. We open-sourced an SEO panel: 10 AI experts that grade your SEO plan out of 100 before you put budget behind it. Drop it into Claude Code or whatever agent you use, then say... "Read this file. Before you show me any SEO plan, have all 10 experts score it out of 100. Under 90, rewrite the weak parts and score it again, up to 3 rounds. Show me the final score and every change." The panel includes a technical SEO specialist, a competitive analyst and an AI search specialist who checks whether the plan accounts for AI Overviews, ChatGPT citations and Perplexity. It docks points for vague advice like "optimize your content." The ROI expert makes the plan clear a 4:1 return bar.
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If you want to hire AI-native talent, use this Grok @bot. Only .2% of people are considered 'AI-native', so how do you find them? Hint: it's not going to be traditional talent managers because they're just too slow. Our talent bots: • Manage our applicant tracking system (ATS) • Pre-screen based on our criteria (e.g. 2 promotions ideally at 2 different companies; avg 3 year tenure) • If they're interested, we send 7 pre-screening questions and apologize in advance, saying we are only looking for AI-native individuals • Then we use Jev to eval based on their responses • Best ones get shortlisted for a real screening call This re-imagines the hiring process by saving both sides a ton of time. Around 37.5% of people respond to the 7 pre-screening questions, and only 4% pass the screen In the video below, you’ll see the actual workflow and the early report, including zero graded passes and zero bookings on a new run. Just remember that someone still has to check the permissions, missed runs, and missing records, then keep improving it. It ain't all sunshine and rainbows right now, but it will be soon. Bot link in first comment. 00:00 Why talent is the X factor 01:19 How Grokbot and Jev fit together 04:02 Inside the recruiting workflow 05:43 Sourcing, screening and outreach 08:00 Why I keep the hiring decision 10:54 The seven screening questions 14:00 Reading the funnel report 15:13 Why you need a bot manager 15:47 What’s working 16:10 What still needs work
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Introducing Claude for lead triage. Your agent can now pull, enrich, and rank your new leads across HubSpot and Apollo. Hot, Maybe or Drop, with one reason each. SingleBrain Gateway: read-only, pay per call. Link below 👇
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Gateway: gateway.singlebrain.com/?utm… The prompt. Paste all of it into Claude, ChatGPT, Cursor or Claude Code. Part 1 sets up the Gateway and guides you while you connect HubSpot. Part 2 runs the triage: "Set up SingleBrain Gateway: gateway.singlebrain.com/llms… Then help me get HubSpot connected: walk me through opening the Gateway dashboard and connecting HubSpot there, and wait until I confirm it's done. Then triage my new HubSpot leads using the SingleBrain Gateway: 1. Check HubSpot is connected with hubspot_list_owners. If it's not connected, tell me what to do in the dashboard and stop. 2. Pull contacts created in the last 24 hours with hubspot_query (POST /crm/v3/objects/contacts/search, filter createdate GTE <24h ago in epoch ms, sort newest first, limit 10). If there are fewer than 3, widen to 30 days. If there are still 0, say there are no new leads and stop. For each contact, get the associated company's name, domain, industry, employee count and revenue. 3. If revenue or headcount is missing, call apollo_organization_enrich once per unique domain, at most 3 calls. 4. For each lead, make one jev_evaluate call with the lead's facts as state and these noul questions: (a) is this an agency or consultancy rather than a brand that buys marketing, (b) does this person control or influence marketing spend, (c) does this person own the marketing function, (d) is annual revenue likely over $1M (only if revenue is still unknown). 5. Rank: Drop if (a) is 0.6 or higher. Otherwise Hot if (b) and (c) are both 0.6 or higher, Maybe if only one is, and Drop if neither is. 6. Use llm_chat on a cheap model to write the ranked list in plain text: Hot, then Maybe, then Drop. Put each group heading on its own line. No markdown, no tables, no decimal scores. One line per lead: name, company, a short reason, then three yes or no labels, e.g. Agency: no. Controls spend: yes. Owns marketing: yes. A label is yes when its score is 0.6 or higher. Agency uses (a), Controls spend uses (b), Owns marketing uses (c). Add a one-sentence follow-up angle under Hot leads only. Read-only: don't write to HubSpot and don't send anything."
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Claude can build your lead list now. We asked for VPs of Marketing at B2B SaaS companies and got 20 verified work emails back for $0.99. No Apollo seat. No Clay contract. One key, pay per call. Prompt below 👇
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Jev Images is a big deal for marketing and sales, and almost no one is talking about it. We're talking running AI visibility audits for $.007 or ad creative gap analyses for $.004. Or imagine if you released this as a lead magnet tool and tens of thousands of runs a month, how many more qualified leads would you get? This type of work was unfeasible before due to costs - if you wanted to run ten thousand, the bill might've been $200k to $1M/mo. AI unlocks work that was undoable before because it just wasn't possible. What an unlock by @typesafeai Jev. See use cases below: 00:00 What Jev Images can do 01:16 Tennis feedback 02:51 AI visibility: the 6-of-60 example 04:32 Homepage audits and grades question 06:03 Calibrating the audit 06:56 Mockups and gaps on our own site 08:13 My Jev usage and spend 08:59 The free audit tool idea 11:18 Better sales follow-ups 13:22 What I tried on the tennis court
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If you want to hire AI-native talent, use this Grok @bot. Only .2% of people are considered 'AI-native', so how do you find them? Hint: it's not going to be traditional talent managers because they're just too slow. Our talent bots: • Manage our applicant tracking system (ATS) • Pre-screen based on our criteria (e.g. 2 promotions ideally at 2 different companies; avg 3 year tenure) • If they're interested, we send 7 pre-screening questions and apologize in advance, saying we are only looking for AI-native individuals • Then we use Jev to eval based on their responses • Best ones get shortlisted for a real screening call This re-imagines the hiring process by saving both sides a ton of time. Around 37.5% of people respond to the 7 pre-screening questions, and only 4% pass the screen In the video below, you’ll see the actual workflow and the early report, including zero graded passes and zero bookings on a new run. Just remember that someone still has to check the permissions, missed runs, and missing records, then keep improving it. It ain't all sunshine and rainbows right now, but it will be soon. Bot link in first comment. 00:00 Why talent is the X factor 01:19 How Grokbot and Jev fit together 04:02 Inside the recruiting workflow 05:43 Sourcing, screening and outreach 08:00 Why I keep the hiring decision 10:54 The seven screening questions 14:00 Reading the funnel report 15:13 Why you need a bot manager 15:47 What’s working 16:10 What still needs work
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This
Marc Andreessen says the gap between what AI-native startups and incumbents think AI can do is the widest he’s ever seen: "The AI-native early stage startups have just a completely different view on what they can do with AI than the typical incumbents in almost any industry, almost without exception." "AI is just racing ahead in capability even week by week... There are going to be a lot of industries that are really up for grabs in a fundamentally more profound way than maybe has been the case in the past." "The founders are gonna have a level of superpowers coming from the use of these tools and these technologies that they just simply haven't had in the past... Had I had Astra and Netscape in 1994, like, oh my God. Like, Ben, what would you and I have been able to do at Netscape?" "Those entrepreneurs are gonna color way outside the lines. We already see this. They're not gonna think of themselves as like, 'I'm just a software company,' or, 'I'm just a hardware company,' or even, 'I'm just an AI company.'" @pmarca @bhorowitz
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Jev Images is a big deal for marketing and sales, and almost no one is talking about it. We're talking running AI visibility audits for $.007 or ad creative gap analyses for $.004. Or imagine if you released this as a lead magnet tool and tens of thousands of runs a month, how many more qualified leads would you get? This type of work was unfeasible before due to costs - if you wanted to run ten thousand, the bill might've been $200k to $1M/mo. AI unlocks work that was undoable before because it just wasn't possible. What an unlock by @typesafeai Jev. See use cases below: 00:00 What Jev Images can do 01:16 Tennis feedback 02:51 AI visibility: the 6-of-60 example 04:32 Homepage audits and grades question 06:03 Calibrating the audit 06:56 Mockups and gaps on our own site 08:13 My Jev usage and spend 08:59 The free audit tool idea 11:18 Better sales follow-ups 13:22 What I tried on the tennis court
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Steal this. We open-sourced an SEO panel: 10 AI experts that grade your SEO plan out of 100 before you put budget behind it. Drop it into Claude Code or whatever agent you use, then say... "Read this file. Before you show me any SEO plan, have all 10 experts score it out of 100. Under 90, rewrite the weak parts and score it again, up to 3 rounds. Show me the final score and every change." The panel includes a technical SEO specialist, a competitive analyst and an AI search specialist who checks whether the plan accounts for AI Overviews, ChatGPT citations and Perplexity. It docks points for vague advice like "optimize your content." The ROI expert makes the plan clear a 4:1 return bar.
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We're hiring across 13 roles Don't apply if: - You're an engineer and AI writes less than 95% of your code - You're in any other role and AI does less than 70% of your tactical work - You spend $0 of your own money on AI - You "would love to learn AI" - You won't share your screen to show what you're building - You can't name who you're learning from Do apply if: - Most of your daily work already runs through AI - You can walk us through your daily AI setup without notes - You spend your own money on AI every month - You can name a task you stopped doing by hand in the last 6 months - You can tell us when your AI work broke and what you changed - You'd send a 10-minute unedited Loom of you doing real work - You're on X 3+ hours a week If that's you, Apply in the first reply.
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