All Things Marketing, Fundraising, Investing, & Sales | $250mm funded across 600+ projects | Co-founder @Crowdcreate_us
California
Joined August 2014
- Tweets1.2K
- Following909
- Followers974
- Likes6.5K
Who can I hire to do this for me at my marketing agency?
BACKLINKS MAXXING with Claude Code
69 backlink tactics behind 133k AI mentions for distribb.io
Ranked:
S TIER
1. Exchange relevant editorial links
2. Join a relevant business network to find editorial link partners.
3. Match links with the surrounding topic to make each reference useful.
4. Link to the answer readers need to give each placement a purpose.
5. Log published sources and destinations to track delivered links.
6. Get into the lists buyers read
7. Find competitor roundups to locate publishers covering your category.
8. Check AI's cited roundups to find sources used in buying answers.
9. Find a missing buyer need to give list authors a reason to add you.
10. Send a tested feature or fresh example to support your proposed addition.
11. Send the author your exact addition to make the edit easy to assess.
12. Refresh your roundup entries to keep the product details accurate.
13. Publish statistics people can cite
14. Choose a question your buyers need answered to make the research useful.
15. Publish original statistics to give writers a source they can cite.
16. Explain the sample and method to make each statistic checkable.
17. Write each finding as a complete sentence to make it easy to quote.
18. Keep research URLs stable to preserve links when findings change.
19. Link research to relevant product pages to help readers try the tool.
20. Answer journalist requests
21. Show real experience in your profile to help reporters assess you.
22. Check Qwoted requests to find reporters who need your knowledge.
23. Filter by topic and deadline to find requests you can answer.
24. Lead with a direct answer to give the journalist a usable quote.
25. Add an original number or firsthand example to support the quote.
26. Include your research page to let the journalist verify the answer.
27. Log requests and replies to avoid pitching the same request twice.
A TIER
28. Find link opportunities through competitors
29. Inspect competitors' linked pages to find resources publishers cite.
30. Read the sentence around each link to learn why the author added it.
31. Add missing evidence to give those publishers a useful new source.
32. Pitch the specific missing answer to show what your resource adds.
33. Recover links you already earned
34. Find unlinked brand mentions to ask editors to link readers to the source.
35. Search for reused charts and quotes to find missing source credits.
36. Restore removed pages with live backlinks to make those links useful.
37. Redirect old URLs to equivalent replacements to restore reader access.
38. Build free tools that earn links
39. Find a repeated buyer calculation to choose a useful free tool to build.
40. Ask Claude to build a calculator to answer the buyer's question.
41. Test normal and unusual inputs to check the tool's answers work.
42. Give the tool a permanent page to give publishers a place to link.
43. Offer the tool to relevant guides to give their readers a shortcut.
B TIER
44. Replace broken and outdated resources
45. Find dead competitor URLs with backlinks to locate broken references.
46. Read archived pages to learn what readers expected from the dead URL.
47. Publish a matching replacement to give editors a working source.
48. Send the broken link and replacement to make the repair easy.
49. Find guides naming closed tools to offer a current replacement.
50. Build the visual an article is missing
51. Find text-heavy guides to locate explanations that need a visual.
52. Offer a graphic for a named section to give the author a clear use.
53. Ask before making graphics to spend time on interested publishers.
54. Use the author's checked facts to make a graphic they can trust.
55. Send the image and embed code to make publishing and source credit easy.
56. Turn another author's article into a video
57. Find guides missing a demo to offer a video their readers could use.
58. Pitch a short video for one section to explain exactly what you will make.
59. Record the steps after the author agrees to produce something they want.
60. Send the finished video with source-credit wording to make adding it easy.
C TIER
61. Earn links through tools you use
62. List software you use to find vendors that could feature your story.
63. Document your workflow and result to give vendors a customer story.
64. Send the case study to the right editor to propose a customer feature.
D TIER
65. Claim relevant business listings
66. Find eligible supplier directories to make your business discoverable.
67. Complete eligible government profiles to help buyers find your business.
68. Add your website where allowed to help directory visitors reach you.
69. Keep listing details consistent to help people recognize your business.
Jeffrey Maganis retweeted
BACKLINKS MAXXING with Claude Code
69 backlink tactics behind 133k AI mentions for distribb.io
Ranked:
S TIER
1. Exchange relevant editorial links
2. Join a relevant business network to find editorial link partners.
3. Match links with the surrounding topic to make each reference useful.
4. Link to the answer readers need to give each placement a purpose.
5. Log published sources and destinations to track delivered links.
6. Get into the lists buyers read
7. Find competitor roundups to locate publishers covering your category.
8. Check AI's cited roundups to find sources used in buying answers.
9. Find a missing buyer need to give list authors a reason to add you.
10. Send a tested feature or fresh example to support your proposed addition.
11. Send the author your exact addition to make the edit easy to assess.
12. Refresh your roundup entries to keep the product details accurate.
13. Publish statistics people can cite
14. Choose a question your buyers need answered to make the research useful.
15. Publish original statistics to give writers a source they can cite.
16. Explain the sample and method to make each statistic checkable.
17. Write each finding as a complete sentence to make it easy to quote.
18. Keep research URLs stable to preserve links when findings change.
19. Link research to relevant product pages to help readers try the tool.
20. Answer journalist requests
21. Show real experience in your profile to help reporters assess you.
22. Check Qwoted requests to find reporters who need your knowledge.
23. Filter by topic and deadline to find requests you can answer.
24. Lead with a direct answer to give the journalist a usable quote.
25. Add an original number or firsthand example to support the quote.
26. Include your research page to let the journalist verify the answer.
27. Log requests and replies to avoid pitching the same request twice.
A TIER
28. Find link opportunities through competitors
29. Inspect competitors' linked pages to find resources publishers cite.
30. Read the sentence around each link to learn why the author added it.
31. Add missing evidence to give those publishers a useful new source.
32. Pitch the specific missing answer to show what your resource adds.
33. Recover links you already earned
34. Find unlinked brand mentions to ask editors to link readers to the source.
35. Search for reused charts and quotes to find missing source credits.
36. Restore removed pages with live backlinks to make those links useful.
37. Redirect old URLs to equivalent replacements to restore reader access.
38. Build free tools that earn links
39. Find a repeated buyer calculation to choose a useful free tool to build.
40. Ask Claude to build a calculator to answer the buyer's question.
41. Test normal and unusual inputs to check the tool's answers work.
42. Give the tool a permanent page to give publishers a place to link.
43. Offer the tool to relevant guides to give their readers a shortcut.
B TIER
44. Replace broken and outdated resources
45. Find dead competitor URLs with backlinks to locate broken references.
46. Read archived pages to learn what readers expected from the dead URL.
47. Publish a matching replacement to give editors a working source.
48. Send the broken link and replacement to make the repair easy.
49. Find guides naming closed tools to offer a current replacement.
50. Build the visual an article is missing
51. Find text-heavy guides to locate explanations that need a visual.
52. Offer a graphic for a named section to give the author a clear use.
53. Ask before making graphics to spend time on interested publishers.
54. Use the author's checked facts to make a graphic they can trust.
55. Send the image and embed code to make publishing and source credit easy.
56. Turn another author's article into a video
57. Find guides missing a demo to offer a video their readers could use.
58. Pitch a short video for one section to explain exactly what you will make.
59. Record the steps after the author agrees to produce something they want.
60. Send the finished video with source-credit wording to make adding it easy.
C TIER
61. Earn links through tools you use
62. List software you use to find vendors that could feature your story.
63. Document your workflow and result to give vendors a customer story.
64. Send the case study to the right editor to propose a customer feature.
D TIER
65. Claim relevant business listings
66. Find eligible supplier directories to make your business discoverable.
67. Complete eligible government profiles to help buyers find your business.
68. Add your website where allowed to help directory visitors reach you.
69. Keep listing details consistent to help people recognize your business.
"Hey Claude, implement this for me" that's it... View article
Jeffrey Maganis retweeted
This is how you do it btw
Granola, a $1.5B company, increased monthly new users from AI search by 4,600% in JUST 7 months.
here’s the genius AEO workflow behind it:
1. They started with buyer decisions, not keywords
-> Granola mapped the questions people ask before choosing an AI meeting tool
-> Then they turned those same decisions into both Google keywords and AI prompts so they could measure where the brand actually showed up
2. Every lost prompt got diagnosed before anything was created
-> If Granola wasn’t showing up, they first asked why
-> Was the right page missing?
-> Did the page already exist but fail to answer the question properly?
-> Was there a crawl/indexing problem?
-> Or was AI getting the answer from third-party sources that barely mentioned Granola?
3 They separated “missing page” from “weak page”
-> This sounds obvious, but it changes the entire content strategy
-> If a relevant page already existed, they improved that page instead of publishing another article targeting the same question
-> New pages were only created when there was actually a gap
4. They stopped treating every technical SEO issue like it mattered equally
-> Crawlability, indexing and performance problems were prioritized based on whether they affected pages tied to real buyer demand
-> A technical issue on a page connected to an important buying question came before cleaning up random site-wide warnings
5. They studied the exact third-party sources AI was already trusting
-> For prompts Granola lost, they looked at the Reddit threads, review sites, articles, directories and other pages showing up instead
-> The question wasn’t just “how do we get more backlinks?”
-> It was “which sources are shaping this specific recommendation, and why are competitors represented there better than us?”
6. They used a simple framework for every important source:
-> OWN: pages Granola controls directly
-> CLAIM: profiles and listings they can take ownership of
-> EARN: editorial mentions, reviews and community discussions they have to deserve
-> CONTEST: outdated or incorrect information they need corrected
-> Different source = different action
7. Reddit became part of the search strategy
-> Instead of posting everywhere, they focused on communities much closer to the product and buyer
-> The same buyer questions being tracked in AI search were used to decide which conversations were actually worth joining
8 They measured Google and AI separately
-> A page could rank better on Google and still barely move in ChatGPT
-> AI mentions could rise while organic traffic stayed flat
-> So Granola tracked both systems independently instead of assuming SEO performance meant AEO performance
9. Then they reran the same questions and scaled what actually moved users
-> measure the gap
-> diagnose why it exists
-> make one specific change
-> rerun the prompts
-> track whether visibility and activated users moved
-> double down on what worked
the result:
-> monthly new active users from AI search increased 4,600%
-> non-branded AI citation rate increased 558%
-> non-branded mention rate increased 739%
-> organic sessions increased 134%
Granola didn’t win AI search by JUST publishing more blogs & content like every other company
instead they built a system for figuring out exactly what they were missing, choosing the right fix, and measuring whether it actually brought in users. then after that just iterating and doubling down on what worked
AI search is now one of their biggest acquisition channels.
and it should be one of yours too!
if you want us to run an audit for your company and make you rank #1 in AI search,
reply “audit”
How everyday people can make money with AI. This is the small business moment for local businesses to start making money.
Jeffrey Maganis retweeted
Apollo analyzed 5.36M sales activities targeting C-suite execs.
Here’s what gets CEOs to reply:
Jeffrey Maganis retweeted
I am so serious when I say this would beat most GTM engineers' best campaigns.
Jeffrey Maganis retweeted
A founder of a startup I funded had these brass plaques made to put up over his and his cofounder's desks. (He's Build Stuff, she's Talk to Users.)
Jeffrey Maganis retweeted
Incredibly emotional watching this because I’m painfully aware that “the good old days” are right now.
At 42 I have a perfectly imperfect life with a wonderful wife and two great kids. I don’t long for my younger years. I want to freeze time right now.
Jeffrey Maganis retweeted
I just saw this @ycombinator's batch literally only has harness startups or hardware startups
So the proof is in the pudding
In the most early adopting tech pioneering place that's Silicon Valley new startups aren't even building software anymore
And it's debatable if anyone will actually need a custom harness or it won't just be generically offered by the AI frontier companies
So software is mostly dead and hardware it is
Well worth a watch. The only software in current YC cohort is domain specific harnesses, but maybe even harnesses are general purpose. In which case, folks, VC backed software startups are largely dead. ht @levelsio
Jeffrey Maganis retweeted
Google is indexing and ranking Linkedin posts on your personal profile
When you make a Linkedin post, you can open this post, and click Copy link to post (three small dots in upper right corner).
This will take you to the search engine friendly version of your post, that Google can index.
Google use the first 6 to 12 words in the post content, to create the SEO title you see in the Google serps.
What that means for SEO is, these pages rank extremely well for those first 6 to 12 keywords.
So if you want visibility on page one for your branded search terms, use LinkedIn posts as one of the most important weapons in your parasite seo playbook...
#linkedin #seo #parasiteseo
Jeffrey Maganis retweeted
theres a method you learn in YCombinator to compress a month of GTM research into 3 hours.
you dont ask Claude to “research the market.”
instead you feed it:
30+ competitor fully indexed websites
10+ earnings call transcripts (biggest incumbents)
100 customer reviews
10+ Reddit thread full of complaints (if u can find them)
then, after that you ask claude:
“what does every successful player in this market understand that customers never say out loud?”
then ask:
“what are the assumptions this entire market is built on, and what would have to be true for each one to be wrong?”
15 minutes later, you’ll have:
-the blind spots
-the consensus
-the ideas relevant to customers that nobody’s talking about
then get Claude to attack the idea like a great investor.
“what’s the strongest version of this argument, and where does it still break?”
3 hours later, you’ll have a (very initial) GTM strategy that feels like it comes from someone who’d spent a decade in the market.
use Claude like a tireless research partner with no ego about being wrong
develop ur intial hypothesis, then go out into the market and start having real customer convos to validate it
(you can use tools like Origami to quickly build customer lists to target)
Jeffrey Maganis retweeted
Big news for local businesses📍
You can now link your @GoogleMyBiz Profile directly to Google Analytics 📣
Track local interactions, calls, bookings, & direction clicks right in GA for a complete, cross-channel view of your performance. Stay up to date → goo.gle/4xsqNsU
This is programmatic SEO done right.
Zapier cracked the SEO game and built a $310M+/year business from it
open Google
search:
“Slack to Google Sheets automation”
“Gmail to Notion integration”
“Shopify email automation”
you’ll see Zapier every time
they turned thousands of tiny use cases into thousands of pages
each one solving a problem right when someone searches for it
you could do the exact same thing
take what your product already solves, and turn every single use case into its own page
now every search becomes a chance to acquire a new user
Could the AI bubble pop? Our marketing agency has been approached by these Open Source AI Foundations and see this opportunity to openly steal market share from the AI incumbents and hyper scalers. Their approach? Target the AI developer communities to start making the switch now
The most basic way AI could blow up imo. I'm not saying it does but this is the most obvious way I can see it happening
- Per seat subscriptions are massively subsidized. The flat fee was priced way below what heavy usage actually costs
- For real business use you have to move to the API anyway. Data protections, work integrations and compliance officer approval
- On the API you pay metered rates, and businesses are burning credits way faster than the per seat pricing ever led them to expect
- This is everywhere right now. Internally for us, Codex users, Uber torching its entire 2026 AI budget in 4 months, the Microsoft comments. Just go try an API
I shared more on this here: xitter.gq/Shaughnessy119/status/…
- And I don't think most businesses have the money to keep paying increasing API rates without a real change to how they operate (caps needed)
- Because they have a cheap alternative. They can reach open source models through any aggregator (OpenRouter, Venice, Baseten, Together) and still get strong privacy. Venice private data centers, or E2EE/TEE serving GLM 5.1.
More on open source inference provider raises here: xitter.gq/Shaughnessy119/status/…
- And the discount is enormous. DeepSeek V4 codes within a hair of Opus on SWE bench at roughly 1/30th the price, and the cheapest open models run closer to 1/100th
- Chinese labs open source frontier grade models. The model is the single biggest cost an inference provider has, and they get it for free
- This idea dies if China goes closed source. That is actually bullish web2 AI labs, because if everyone is closed you pay up for the best intelligence. China goes closed source if they are tired of giving away an asset and they want the revenue and data flow to train new models
- Is this showing up in web2 AI lab revenue yet? No. Revenue is off the charts. Anthropic went from 9B to 47B run rate in five months
- So go forward, what happens?
- I think revenue slowly starts leaking to the open source inference providers (see Venice usage, OpenRouter's $113M raise, Baseten is raising at $11B or triple its valuation in three months, on revenue that went from $200M to $600M annualized in a single quarter)
- It doesnt move overnight, but it caps the labs ability to raise prices, and margins are already deeply negative. OpenAI is reportedly running near negative 122%
- With margins that bad there is no cash flow, so the labs are fully dependent on outside capital to buy GPUs, train models, and keep subsidizing usage (I.e. see Google tapping $80b equity sale, granted 30b for employee RSU taxes. Clearly they think Equity is overvalued or you wouldn't sell it)
- The break comes when that capital stops. Pricing is capped so margins cant improve, and the moment investors lose conviction on payback, the whole flow reverses
- Why would they lose conviction on payback? Back to the start - the inability to improve margins or get businesses to pay more
- This is also limiting, if we start making new drugs with AI or create entirely new businesses, you better believe people will pay up to the max for AI usage
Jeffrey Maganis retweeted
THE MODERN CREATIVE FLYWHEEL
How To Achieve Volume + Quality
Your brand needs a staggering amount of content to succeed in 2026.
like 10,000 pieces per month.
The problem most founders experience is quality erodes as quantity scales up.
This is solvable with 2 methods.
1st, a Creator Army.
You have to manage creators actively and engage with them as if they're employees.
Motivation, incentives, growth opportunities
Example: Commissions
Most brands look at creator commissions as a "cost" on their P&L
Yet the top brands on TikTok Shop / Meta understand that higher commissions = better output
Better output = lower acquisition costs, higher scale
So on the front end maybe it looks crazy to give a creator 30% of all sales from their video WITH ad spend behind it..
But you're already giving Meta 80% of Opex anyway.
Why not invest in the thing actually driving growth?
Sadly even when a video goes crazy..
You need to constantly nudge creators.
Competitions, weekly meetings, IRL activities
All things that keep them motivated and excited to promote your product.
Its an arms race and your competitors are willing to do anything for better content.
2nd - Find a "Viral Phrase"
At 10,000 videos per month, you want as much confidence in each angle as possible.
The simplest way to do this is identify a viral phrase.
Viral Phrases allow you to quickly articulate your product's value prop and differentiation.
Examples include...
"Cortisol Lemonade"
"Nature's Zempic"
"BBL Leggings"
"Korean Botox"
"New Face Card at 40"
Basically something you can tell creators to make that isn't a full script - just a headline.
The rest of it can be up to them.
My fav way to recruit these creators is @sideshift_app or @euka_ai
And use Trybe for meta ad spend mgmt
Last if you wanted this info 6 months ago before it started getting more saturated...
Watch @onlysweatequity
Jeffrey Maganis retweeted
Anthropic is paying up to $400,000 a year for an events role.
They're looking for someone to own the execution of brand experiences that translate Anthropic's values into physical moments.
This person will produce everything from intimate thought-leadership gatherings to large-scale industry activations.
The top AI research lab in the world recognizes that to cross the chasm and reach everyday consumers, they need to lean into hospitality. They need to create visceral, unforgettable IRL experiences that make complex technology feel accessible and human.
They understand that digital channels are getting increasingly saturated. Every feed is flooded with AI content... every inbox is overflowing.
The massive opportunity now is offline, analog, in-person.
The companies that win in the next decade won't just have the best product but the most emotional in-person presence and the most compelling storytelling.
If you're in events, experiential marketing, or brand activations, this is your moment. The biggest tech companies in the world are betting on you.
Jeffrey Maganis retweeted
Sleeping <6h a night for 2 weeks reduces cognitive performance equal to 2 nights of total sleep deprivation.
Looking to start a peptide company and replicate Medvi's success?
I just found their same supplier, and know how to rank #1 for "peptides for sale" on Google/ChatGPT.
Comment "peptide marketing" below for the contact info and list.
