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aiguide_

Grant Miller

Verifiedactive
@aiguide_

GTM advisor to VC-backed tech companies | Talking AI, GTM, startups

509,594 followers · 161 following · Last polled 3h ago
Perf. Score
65.3
Rank #103
Value Score
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set rates to compute
Median views
5.3K
p25 3.1K · trailing 7d
Followers
510K
-0.0% 7d
ER (impr.)
2.98%
eng ÷ impressions
ER (foll.)
0.06%
eng ÷ followers
Est. CPM
—
needs a rate
WoW views
+52.5%
▲ rising

Rates & value · est. from 5.3K median organic views

Quote tweet
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no CPM
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rate age unknown (pre-audit import)

Trends

Follower growth
Median views / day
Engagement rate
View distribution · trailing-7d posts

Each blue dot is one organic post. The Performance Score ranks by the median (5.3K), not the mean (9.7K) — so a single viral post doesn't inflate a creator's reach. The p25 floor (3.1K) is the level 75% of posts clear.

Recent posts · ranked by views

PostPostedViewsLikesRepostsRepliesQuotesBookmarksER
if you're ambitious but lazy at night, this is a must read "you are asking the exhausted system to fix itself using the resource it already ran out of." read it, bookmark it, then read it againfrozen25d ago197K1.0K130301.7K1.44%
im begging you to read this: “Without feedback, 20 years of experience is just one year lived 20 times. With it, a few months can beat a career.”frozen26d ago177K1.5K197812.3K2.27%
if you want to advance your career you need to read this: (don't just bookmark it)
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27d ago
174K
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2.2K
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you're telling me you can now just paste your URL and get a full marketing campaign? this is insane.frozen28d ago56K18210212850.85%
insane value here read it, bookmark it, and read it againfrozen18d ago54K32032306741.90%
if marketing really is 80% of the success, here's where i'd spend the 80%: 1. get painfully clear on positioning. one sentence should tell me WHO this is for, WHAT it helps them do, and WHY i'd choose it over the alternatives. 2. steal your language from customers. sales calls, reviews, support tickets, Reddit, DMs. save the exact words people use for pains, objections + desired outcomes and write from those. 3. pick one distribution channel and get unusually good at it. X, YouTube, LinkedIn, short-form, SEO, whatever already has your buyers. depth beats being mediocre everywhere. 4. spend almost as much time packaging as creating. hook, title, thumbnail, first 3 seconds. nobody gets value from something they never click. 5. build around repeated problems, not random content ideas. if customers ask the same question 20 times, that's probably a post, landing page, ad, email + sales asset. 6. study your outliers. when one post gets 10x the normal reach or one ad crushes everything else, don't “move on.” figure out the topic, hook, format + audience behind it and make more. 7. turn one good idea into 10 pieces. article → X posts → video → clips → newsletter → carousel → sales email. good ideas should travel. 8. collect proof constantly. screenshots, customer quotes, numbers, before/after, use cases. marketing gets WAY easier when you don't have to manufacture credibility. 9. move people somewhere you own. social gets you discovered. email, community + your site let you reach them again without asking an algorithm for permission. 10. keep the loop running: customer → insight → content → attention → conversation → sale → more customer insight. making something great is only half the job. people have to know it exists.frozen6d ago39K61545951.0K4.37%
it's really that simple lolfrozen19d ago35K39542106353.09%
if you're young and want to get REALLY good with AI, read this: "it's the difference between asking AI to write your strategy and asking AI to stress-test the strategy you already built. you can be a passenger or a pilot."frozen25d ago33K20922103241.69%
i broke this video down into 15 steps. how to build a paid ads program from scratch: 1. pay on performance, not upfront. creators earn a % of gmv (ecom) or a % of ad spend (saas, since conversion cycles are longer). whisper flow pays 7% of ad spend 2. set your % based on your cac. too high blows up your ad account, too low and creators stop caring 3. add a smart retainer: a guaranteed minimum (e.g. $1k for 25 videos) that you top up if commissions fall short. once they out-earn it, they're on pure commission 4. use the retainer to recruit early. with no reviews or payout history on the platform, it's the reason top creators will bet on you 5. start with 4-5 creators, not hundreds. mercenary creators = thousands of identical talking-head videos. 6. recruit for gaps in your ad library (new formats, new icps, new regions), not just volume 7. find creators off-platform. ig keyword search ("ugc," "tech," "saas"), then dig through their followers and comments for similar creators. send 100-200 dms over a week 8. treat creators like a sales team. coaches, weekly calls with your media buyer, and open access to your calendar 9. run giveaways and bonuses they actually value: cash, camera gear, mics, meta glasses (bonus: better gear = better ads) 10. fly your top creators in for a retreat. face-to-face builds loyalty that calls can't 11. scale slowly: 5 → 10 → 20 → 40. whisper went from 5 to 50 active creators in 4 months 12. cap around 40-60 and only add killers after that. smaller groups feel more exclusive and creators see more opportunity there 13. pay a $100 referral bonus for creators at or above their level (good creators know good creators) 14. ban copycats. when creators replicate the top performers, meta clusters near-duplicate videos and suppresses reach 15. push new concepts constantly. the leaderboard winners got there by experimenting, not by remaking someone else's hit.frozen12d ago32K31612737983.58%
i'm 99.999% sure this is the best Grok Bot content workflow: I pulled the best parts from the Grok Bot systems behind 69.8M impressions, a 201K-view repurposed article + weekly X analytics agents and put them into one setup. here's how i'd build it: 1. every morning, scan 50-100 great accounts in your niche and save the posts outperforming that account's normal baseline. keep the source, hook, visual, format, topic, bookmarks + why people had a reason to open it. 2. before drafting anything, trace the source. check the original claim, whether it's current, who else is talking about it + whether the obvious angle has already been posted everywhere. one of the best Grok Bot setups I found uses separate bots to find the change, verify the claim, decide if it's worth covering, then draft. 3. take each strong source and make 5 fresh angles from it. quote post, breakdown, how-to, short reaction, visual post, etc. the 69.8M-impression system did this with posts that were already working, then picked a different wrapper for each account. 4. if you run multiple accounts, never give them the same version. one published system took the same Website-to-App idea, made 3 versions for 3 accounts, and all 3 crossed 1M views. 5. rank your own posts against YOUR median. tag topic, hook, format, length, media + whether it quoted a viral post or rode a live topic. weight bookmarks, reposts + replies heavily so a post with lots of empty likes doesn't fool the system. 6. every Monday, have Grok Bot pull the last 7 days and tell you the top 3 posts, what underperformed, which patterns keep winning + 5 ideas for the next week. keep the history in one spreadsheet so the analysis gets better over time. 7. repurpose after something proves itself. one Grok Bot workflow checks X for new original posts and automatically creates LinkedIn + Bluesky drafts. another turned a video with 83K views into an X article that reached 201K views. 8. use X as a research layer too. Grok Bot can watch competitor posts, pull people engaging with them, track complaints + buying signals, summarize a prospect's recent posts and reverse-engineer accounts whose content keeps working. 9. keep everything in draft mode. Grok Bot can find the source, research it, build angles, draft, repurpose + queue the work. you still decide what actually gets published. 10. put the whole thing on routines. morning discovery, nightly performance tracking, Monday analysis + repurposing when a post earns it. the cloud machine keeps running after you close your laptop. the morning output I'd want: • 3 sourced ideas worth looking at • 5 angles on the strongest one • 1 finished draft • any repurposing jobs earned by yesterday's winners2d ago29K25163037383.53%
you cannot compress an entire domain into one SKILL.md... the better structure is a skill graph: • one idea / technique per markdown file • YAML descriptions so the agent can scan before reading • wikilinks connecting related skills • MOCs that map bigger topic clusters • an index that points the agent into the graph then the agent loads context progressively: index → descriptions → relevant links → relevant sections → full files only when needed so a company skill graph could look like: company/ ├── customers/ ├── product/ ├── competitors/ ├── positioning/ ├── sales/ ├── marketing/ ├── processes/ └── decisions/ and those aren't isolated folders. customer objection → competitor comparison → positioning → sales response → product capability now the agent follows the chain based on whatever it's working on.frozen7d ago28K431341317124.33%
this role is going to become insanely important every company running agents needs someone responsible for what the agents know bad context scales just as fast as good automationfrozen25d ago27K21418202771.89%
so many people underestimate how much easier something is to sell when there’s a good story behind it. “Mastering storytelling is how you stop selling, and start subconsciously persuading people to do things you want them to do.” this is a MUST read if you sell anythingfrozen21d ago24K28643003632.83%
founders NEED to think about content like this: “if you nail content, it's the only marketing channel you'll ever need and one of the most scalable verticals.” this goes way deeper than posting. writing, packaging, taste, distribution, systems, hiring, team structure... if you're going to read anything today, read this.frozen11d ago23K1468403342.14%
this is such a weird new AI business opportunity: $300K data licensing deal → seller gets $300K → broker gets $18K on top learn how to package, price, and negotiate the data so buyers actually want it. bookmark this one.frozen15d ago21K20011303812.80%
i broke this video down into 15 steps. how Wispr Flow runs paid ads: 1. treat self-serve B2B like consumer marketing. if one person can buy the product, the ad shouldn’t feel like it was made for a 6-person buying committee. 2. steal from consumer ads. 75% of Wispr’s top 8 ads by spend were creator videos. 3. launch a LOT of creative. Wispr pushes ~500 new ads a month, and Eric says his job is now ~80% creative ops and 20% media buying. 4. keep 15-25% of spend for testing and put the rest behind proven winners. 5. tag every ad before launch by concept, angle, persona, awareness level, and format so you know WHY something worked. 6. when a concept + angle + persona combination wins, make 10 new executions around it instead of starting from zero. 7. test genuinely different concepts, not 10 tiny variations of the same ad. Meta needs new signals, not different colored versions of one idea. 8. stop judging ads by hook rate alone. hook means nothing if everyone leaves immediately after. 9. one Wispr ad had a 39.5% 3-second hook rate but only 14.3% made it to 25% of the video, so it still burned money. 10. score ads across hook, hold, CTR, and CPM instead of letting one metric decide what gets scaled. 11. build a creative leaderboard. Wispr uses a “Banger Score” so everyone can see which ads are actually outperforming. 12. make ads about things people already care about. one winner used Claude, Mac shortcuts, and an In-N-Out vs Shake Shack joke before getting into the product. 13. trust server-side conversion data over whatever Meta says it generated, especially when you’re selling B2B SaaS. 14. automate repetitive media-buying work with AI + APIs so your team can spend more time making better creative. 15. keep every learning in one shared marketing system so each experiment makes the next experiment smarter.frozen10d ago17K15510253653.10%
how I'd build a top 1% content system with Grok Bot in 30 minutes: - start with a scout bot that reads X every morning without an X API key. it pulls the top posts in your niche, breaks down why they hit, and saves the winning hooks and formats into a swipe file - set a daily routine that turns those viral posts into questions for you. "this post about firing your first client got 2M views. what's your version?" you answer with a quick text or voice note, and that's your spin on a format that's already proven - every answer gets saved to a knowledge base, so the system builds a library of your stories, opinions, and lessons and never has to write from nothing - make a second bot your voice. give it your 20 best posts and turn your writing style into a skill, so every draft sounds like you and not like AI - put the scout, the writer, and an editor bot in one group chat. the scout brings the format, the writer pairs it with your story, the editor tears it apart, and you only see what survives - have it make the visuals too, like thumbnails, carousel images, and short clips, so a post never stalls waiting on a designer - set a weekly routine that pulls your own post metrics, like impressions, likes, and replies per post, and logs them to a database so you see which topics and formats are actually growing you - close the loop: every Monday it reads last week's numbers, asks better questions based on what worked, and has the next week's posts drafted before you open your laptop wild how easy this is nowfrozen5d ago17K172121123683.29%
everyone should study this business becomes 100x easier when you know how to send a good cold emailfrozen17d ago16K29018102783.67%
if you're running a startup, you should have a system watching your market all while you sleep. customers, competitors, pricing, launches, buying signals, complaints, hiring, content. here's the 24/7 research system i'd build: 1. make one research database with 6 buckets: CUSTOMERS, COMPETITORS, MARKET, PRODUCT, GTM, CONTENT. every finding needs a source, date, company/person, category + one sentence on why it was saved. 2. start with customer truth. feed it sales calls, support tickets, reviews, Reddit, G2 + customer interviews. pull exact pains, objections, desired outcomes, feature requests + the words customers keep repeating. 3. watch every serious competitor. track homepage copy, pricing, launches, changelog, job posts, partnerships, customer complaints + new positioning. save the OLD version too so you can see exactly what changed. 4. monitor buying signals around target accounts: funding, hiring, new executives, expansion, new markets, tech-stack changes, product launches + anything else that suddenly creates a reason to buy. 5. watch the market itself. follow founders, investors, researchers, customers + niche publications. save repeated ideas, new categories, new tools + anything multiple smart people start talking about at once. 6. build a product-feedback loop. cluster feature requests and complaints by frequency, account, revenue + urgency. “17 customers asked for this” is a lot more useful than a Slack message saying someone wants dark mode. 7. add content research as one input. watch 30-50 accounts your buyers already follow, save outlier posts + repeated questions, and track which topics keep getting attention before your company talks about them. 8. keep claims attached to sources. a tweet saying “X grew 400%” stays CLAIMED until verified. don't let one confident post quietly become company knowledge. 9. dedupe aggressively. if 12 sources repeat the same thing, keep one main finding and attach the others as supporting evidence. research should get sharper as it grows, not noisier. 10. connect findings to the company. competitor launches new pricing → GTM. customers repeat one complaint → PRODUCT. buyers keep asking one question → CONTENT / SEO. the useful part is where the information should go next. 11. send one morning brief with a hard cap of 10 items: 3 customer insights, 2 competitor changes, 2 market shifts, 2 GTM opportunities + 1 thing worth investigating. if it takes 20 minutes to read, the system failed. 12. every Friday, make it answer 5 questions: what changed this week? what kept repeating? what did customers care about most? what should we test next? what are we probably underestimating? 13. keep a permanent knowledge base behind it. PEOPLE, COMPANIES, TOPICS, DECISIONS + PROJECTS. today's research should still be findable six months later when it suddenly becomes relevant. 14. tie the research to whatever the company is deciding right now. pricing decision? pull competitor changes, customer objections + lost deals. launch coming up? pull buyer language, recent category shifts + competitor messaging. the database is only useful if it helps with an actual decision.frozen5d ago15K12391812522.65%
your brain is basically a skill tree. you can max out business, marketing, or coding and still get stuck because everything around it is underleveled. when the same problem keeps beating you, stop dumping points into the same stat. instead just read this and fix that.frozen27d ago14K10911001481.92%
if you're ambitious but feel lazy during the daytime, you need to see this an agent can now: - follow up on an unpaid invoice - call a vendor to check pricing and availability - coordinate a meeting - book the travel you've been putting off this actually CALLS people. not just giving you instructions on how to do it. useful when you have energy to build, but none for the calls, bookings, and follow-ups you keep putting off. see how far you can get with thisfrozen24d ago13K5121100.15%
going to be cooking up infinite viral posts now https://t.co/IjAACfUVjf2d ago13K905201511.92%
if you're still giving one agent one huge task, steal this setup: GOAL → SPLIT → WORKERS → VERIFY → MERGE → OUTPUT 1. define the exact outcome first. the graph should know what “done” looks like before it creates any workers. 2. split the job into pieces that can actually run in parallel. research, compare, check, find gaps, test assumptions, etc. 3. give each worker ONE job. smaller context, clearer instructions, less overlap. 4. run the workers at the same time instead of making one agent research everything sequentially. 5. add a verifier that reads the outputs, checks sources, catches contradictions + sends weak work back. 6. merge only the useful results into one final answer instead of dumping every worker's output into the context. 7. save the graph once it works. next time, the system can reuse the same structure instead of rebuilding the workflow from scratch. this is a much better way to think about agents than “write a better prompt.”frozen4d ago12K10512001682.35%
this article buried a really good 30-day system for building an audience: week 1: build an idea museum. save posts that already performed well, ideas you personally care about, notes from books, conversations, videos + anything else you may want to write about later. keep proven ideas and personal ideas separate so you can combine them later. week 2: pick 3 mid-sized creators in your space and study their best posts. save the outliers, figure out why they worked, then take one proven idea each day and write 5 different angles on it before posting the strongest one. week 3: keep posting and watch the replies + questions closely. repeated questions are a strong signal that people want you to go deeper on something. week 4: pick one of those repeated questions and turn it into a simple one-page guide. use it to collect emails, then expand it into something larger if people clearly want more. then keep the loop running. you’re using proven content to find topics, your own perspective to make them worth following, and audience response to decide what to make next.21h ago12K1279402353.15%
this is a content masterclass CONTENT is the most important thing in 2026, and this guy is teaching you how to set it up for FREEfrozen9d ago12K1159302072.82%
me thinking I was behind because I never learned the entire no-code automation stack then Claude Code happened https://t.co/1HdHsV021hfrozen15d ago11K2343080.33%
if you're trying to build distribution from zero, save this: 1. decide what people are buying into BEFORE you post. get clear on who you are, what you believe, who it's for, why they should care + where the story is going. every post should feel like another chapter of the same story. 2. work backwards from the end. if your end state is “voice replaces typing,” your content can keep reinforcing why typing is slow, why voice is better, how the behavior is changing + what the future looks like. one clear destination gives you years of things to talk about. 3. pick 1-2 channels. don't start with X + LinkedIn + TikTok + YouTube + a podcast + newsletter. pick where your audience already is, where your format fits, and where you can realistically stay consistent. 4. give every channel a job. X = ideas + network. short-form = reach. YouTube = depth + trust. newsletter = owned audience + conversion. podcasts = borrowed audience. community = retention. 5. build all 3 types of distribution over time. RENTED = X, TikTok, YouTube, LinkedIn. OWNED = email, newsletter, website, community. EARNED = podcasts, collabs, other people's audiences. rented gets attention, owned keeps it, earned expands your reach. 6. spend WAY more time packaging. most people spend ~95% making the content and 5% getting people to consume it. get closer to 50/50. hooks, titles, thumbnails + the first 3 seconds matter because a great idea with bad packaging still dies. 7. make every piece understandable immediately. bold claim, clear outcome, curiosity, specificity. if someone has to decode what the post is about, you've already lost them. 8. learn the native format of each platform. the same idea shouldn't look identical everywhere. X rewards concise ideas, YouTube needs title + thumbnail + retention, LinkedIn can carry more personal context, short-form has to win immediately. 9. when something hits, DO IT AGAIN. one outlier is data. make 5 more around the same topic, format, hook mechanism or audience problem. “we already posted about that” is how people abandon winners too early. 10. make every channel feed another. X → newsletter. YouTube → X. short-form → YouTube. podcast → newsletter. content shouldn't end on the platform where someone found you. 11. turn one good idea into everything. one article can become 5 X posts, a thread, a YouTube outline, 3 short videos, a newsletter, a carousel + podcast talking points. you don't need 50 new ideas. you need more distribution from the good ones. 12. eventually move people somewhere you own. algorithms change, reach disappears, accounts get restricted. an email list is still there. followers are nice. distribution you can reach again tomorrow is better.frozen6d ago11K11812911843.09%
Sports Illustrated waking up to 10,000 DMs offering millions for their SI domain... https://t.co/goU7AFZtrwfrozen23d ago10K1203060.20%
the list of things AI voices “can't do” is getting VERY short and somehow this is still the worst they'll ever be...frozen19d ago10K16400150.35%
this is an insane product over 1 MILLION impressions in under 24 hoursfrozen24d ago9.7K200050.07%
if you actually want to change your life, this is vital to internalize: "If you want a specific outcome in life, you must have the lifestyle that creates that outcome long before you reach it." you won't regret reading thisfrozen23d ago9.1K44700601.22%
personal branding got WAY more valuable once everyone got access to the same AI read it, bookmark it, give it to your AI, then read it againfrozen19d ago9.1K57820931.76%
Luna 6 should be all over your marketing stack... It's by FAR the best price to performance model out there.frozen1mo ago9.0K510020.09%
Google just killed 100,000 video game devsfrozen15d ago8.6K14220110.34%
a very strong niche skillset = money it really is that simplefrozen29d ago8.5K18110300.59%
if you want to get REALLY good with AI agents, internalize this: “you are not allowed to do one-off work.” do it once prove it works turn it into a skill automate it if you have to ask for the same thing twice, you failedfrozen24d ago8.1K22410280.68%
if you sell software, stop writing SEO for people who are “learning.” write for people who are choosing. this founder got roughly HALF his signups from ChatGPT after publishing around those buying questions. here's the playbook i'd copy: 1. build a list of questions someone asks right before spending money. “[competitor] alternative,” “[tool] vs [tool],” “best [category] for [use case],” “[category] for [specific buyer],” “[tool] pricing,” “is [tool] worth it.” 2. run those questions through ChatGPT in a clean session and save every source it cites. track the query, cited URL, page type, company mentioned + whether your brand appears. after 30-50 queries you'll start seeing the same sites and formats repeatedly. 3. sort the queries by buying intent. someone searching “what is CRM software?” is learning. someone asking “best CRM for a 10-person agency” is choosing. write for the second person first. 4. build the missing commercial pages on your own site. alternatives, comparisons, use cases, pricing, integrations + specific buyer pages. one page should answer one clear buying decision extremely well. 5. don't write fake comparison pages where you magically win every row. include pricing, screenshots, real limitations, who each option is best for + where the competitor genuinely wins. the page should still be useful if the reader never buys from you. 6. add something the other pages don't have. original data, a calculator, real product screenshots, a decision table, a benchmark, customer examples, a demo. another 1,500-word AI article saying the same thing gives nobody a reason to cite you. 7. make the important information easy to retrieve. put prices, differences, features, limitations + answers in actual page text. use descriptive headings, keep pages crawlable, add internal links, and make sure structured data matches what the visitor can actually see. 8. make sure ChatGPT can access the site. check robots.txt/CDN rules and don't block OAI-SearchBot. OpenAI says public pages can appear in ChatGPT search and specifically recommends allowing its search crawler. 9. don't only watch your own domain. if ChatGPT keeps citing a third-party “best tools” page, comparison, Reddit thread or industry guide for a valuable query, that page matters too. work out why you're missing and whether you legitimately belong in it. 10. track the traffic all the way to money. ChatGPT referral links include utm_source=chatgpt dot com, so record landing page → signup → qualified user → paid customer. “we got cited 400 times” means very little if none of those people buy. 11. when one page starts bringing customers, expand around the SAME intent. “X alternative” → “free X alternative” → “X vs Y” → “best [category] for [use case]” → “[category] for [buyer].” don't go back to publishing random traffic articles. 12. rerun the important questions every month. save which brands + URLs appear, which disappeared, and what new sources started getting cited. then update the pages tied to actual buying decisions. and don't waste the first month looking for some secret GEO markup.frozen6d ago8.1K8921311523.17%
you can now give Claude Code an ICP and have it build the lead list for you... without opening Clay. this is the workflow I use and how you can too: 1. install Treg in Claude Code /plugin marketplace add superdesigndev/treg /plugin install treg@treg 2. give it your ICP 3. have it: • find matching companies • find 2-3 decision makers at each • waterfall their work emails • verify the emails • enrich the accounts • score every lead • save the final list to CSV then paste this: “Build me a list of 100 [ICP] companies in [market]. For each company: • find the 2 most relevant decision makers for [problem] • find + verify their work emails • include title, company, domain and LinkedIn • score each lead 1-100 for ICP fit • explain the score in one sentence • exclude anyone without a verified work email • do not invent missing data Rank the final list by fit and export it as a CSV.” that’s an entire prospecting workflow inside Claude Code. wild.frozen16d ago7.9K26421651.24%
if making money still feels like guessing, read this: “Reps = data points = pattern = money. The more feedback you get, the faster you learn. The faster you learn, the better you get at recognizing what actually works.” study this and change your lifefrozen21d ago7.9K601200541.60%
if you're building AI and don't want to fall behind, watch this. 45 minutes on context + harness engineering and how always-on agents actually work. probably the most useful thing you'll watch this weekend.frozen11d ago7.3K34600921.82%
if you use AI for work, this is one of the most important things you’ll read all year - read it - bookmark it - send it to your AI agent - read it again most companies won’t get the gain from “using AI” they’ll get it from reorganizing around it26d ago7.2K16021200.54%
anyone doing a launch on X should read this and bookmark it crazy valuefrozen12d ago7.1K23010300.76%
how to build a top 1% Claude Code setup in 30 minutes: save this and do it in order. 1. MAKE YOUR CLAUDE.md run: /init then open CLAUDE.md and add: • what the project does • important folders • build command • test command • lint command • coding rules • files Claude shouldn't touch • what counts as “done” keep it short. if Claude needs to know it on almost every task, put it here. 2. MAKE 4 SKILLS create: .claude/skills/ start with: • build-feature • fix-bug • code-review • write-tests each skill should tell Claude: • what to inspect first • what steps to follow • what commands to run • what needs your approval • how to know the task is finished any prompt you keep rewriting should probably become a skill. 3. CONNECT YOUR TOOLS add the MCPs Claude actually needs. start with things like: • GitHub • your docs • issue tracker • database • browser don't connect everything. if you're constantly copying something into Claude by hand, connect THAT. 4. AUTOMATE THE BORING CHECKS use hooks for things that should happen every time. examples: after editing code: → format + lint after changing logic: → run tests before finishing: → typecheck before committing: → run validation don't rely on Claude remembering these. 5. ADD 3 SUBAGENTS make: • researcher • reviewer • test-agent researcher: finds the relevant files + explains how the system works. reviewer: checks the change for bugs, regressions + bad assumptions. test-agent: looks for missing cases + runs the important tests. keep each one narrow. 6. FIX YOUR PERMISSIONS auto-allow the boring safe stuff: • read files • search • git diff • lint • tests keep approval for: • deploys • production changes • secrets • destructive database commands • anything irreversible you want less permission spam without giving Claude the keys to everything. 7. GIVE THE PROJECT MEMORY make: docs/decisions.md docs/status.md docs/known-issues.md decisions.md: why important choices were made. status.md: what's being built + what's left. known-issues.md: bugs, failed approaches + things not to repeat. have Claude update these after long tasks. this stops every new session from starting from zero. 8. MAKE A TINY EVAL SET save 10 real tasks your repo should handle well. examples: • add a small feature • fix a bug • change an API • write missing tests • refactor something without breaking behavior give every task a validation command. then when you change your CLAUDE.md, skills, hooks or agents... run the same tasks again. you'll know if your setup really got any better. your repo should now roughly look like: project/ ├── CLAUDE.md ├── .claude/ │ ├── skills/ │ ├── agents/ │ └── settings.json ├── docs/ │ ├── decisions.md │ ├── status.md │ └── known-issues.md └── evals/ that's it. the goal is simple: stop re-explaining your repo to Claude every day.frozen7d ago6.8K23131531.19%
now try telling me Grok won't be the best model within the next 3 years lolfrozen7d ago6.7K3431050.65%
Ctrl + C Claude Opus 5.5 Ctrl + V Enter That's the formula to become richfrozen28d ago6.3K9100180.44%
marketing engineers might be the highest-leverage marketing hire in 2026. the best ones can run more experiments than entire teams. i broke the playbook down into 12 rules: 1. build the company brain before you build agents. customer fit, offers, voice, founder opinions + failed campaigns should live in files every agent can read. 2. start agents read-only. let them learn from HubSpot, Stripe, Slack, Gong + analytics before they earn permission to change anything. 3. give every campaign an ID and carry it through ads, emails, UTMs, CRM deals + revenue so you know which marketing brought customers who actually paid and stayed. 4. make customer language your first agent. feed it 20-50 sales calls and pull the exact phrases buyers use to describe their problems, then rerun it every week. 5. build a buying-trigger agent around moments that create demand: funding, hiring, new locations, product launches, expansion + other changes that suddenly make your product relevant. 6. only write outbound when you can clearly explain why NOW: “this event creates this problem, and our product solves it in this specific way.” if that sentence is weak, skip the account. 7. build search around questions people ask right before they buy. combine Search Console, sales calls + what ChatGPT, Claude and Perplexity recommend when buyers ask about your category. 8. make your creative agent test different REASONS to buy, not 50 tiny variations of one ad. pain point, customer story, worked example, demo, comparison, founder take, etc. 9. name every experiment by what it’s testing. “dinner-angle_ugc_v2” creates a reusable lesson when it wins. “video_final_7” tells you nothing. 10. build a closed-lost agent that rereads every lost deal, records the real reason + reopen condition, then brings the account back when that condition changes. 11. make every performance report end with a decision: KEEP, KILL, CHANGE, or TEST. wire it through to revenue, retention + churn so cheap customers who leave don’t look like a win. 12. every rejection should improve the system. bad ad → update the brief. wrong customer → update customer-fit. confusing offer → save the lesson so the next run doesn’t repeat it. the loop: customer truth → experiment → result → lesson → better experiment. whoever runs the most GOOD experiments learns the fastest.frozen9d ago6.0K936701243.84%
Claude Sonnet 5.5 is the model I'd put EVERYWHERE... 30%+ faster. Up to 30% cheaper per task. And surprisingly close to Opus 5.5 on a lot of real work. Here are 10 workflows I'd use it for: 1. Build + QA landing pages Give Sonnet: • ICP • Offer • Brand guidelines • Customer language • Examples you like Have it build the page, open it, then check: • Mobile layout • Forms • CTA placement • Broken sections • Copy consistency • Weird spacing It’s fast enough to keep iterating instead of stopping after draft #1. 2. Turn every sales call into action The second a call ends, give Sonnet: • Transcript • CRM history • Deal stage • Account context Have it: • Update the CRM • Pull objections • Draft the follow-up • Choose relevant proof • Create next steps No rep should spend 15 minutes doing admin after every call. 3. Run campaign analysis every morning Feed it: • Spend • CTR • CAC • Creative • Pipeline • Revenue Then ask: • What changed? • What broke? • What deserves more spend? • What should be killed? • What should we test next? Not another dashboard. An actual daily decision layer for marketing. 4. Generate + analyze ad variations Give it your winning creative. Have Sonnet create variations across: • Hook • Angle • Offer • CTA • Format • Audience Then feed the performance data back in and have it find which combinations keep winning. Now creative generation and analysis are one loop. 5. Research every important account Before a rep touches an account, Sonnet can pull together: • Company • Product • Recent changes • Hiring • CRM history • Previous outreach • Relevant case studies Then return: • Why now • Likely pain • Best angle • Proof to use • What NOT to say Do this automatically for every account that matters. 6. Build decks + proposals This is one of the use cases Anthropic specifically highlighted. Give Sonnet: • Call transcript • Account research • Existing deck template • Pricing • Case studies And have it build the actual client-ready deck. Not an outline. The deliverable. 7. Mine customer conversations Run every: • Sales call • Support ticket • Review • Survey • Churn interview Through Sonnet. Continuously extract: • Pain points • Objections • Buying triggers • Desired outcomes • Exact customer language Your messaging gets better every time a customer talks. 8. Build internal GTM tools Sonnet 5.5 made a HUGE jump in agentic coding. Use it to build the boring tools you normally buy another SaaS for: • Lead routers • CRM utilities • Campaign QA • Reporting tools • Enrichment workflows • Internal dashboards Then let the same agent maintain them. 9. Run high-volume support + ops agents This is where the speed really matters. Let Sonnet handle: • Support replies • Escalation decisions • Internal requests • Document processing • Research • Routine browser work Anthropic says Zendesk saw tickets processed 20% faster in testing. At enough volume, that compounds fast. 10. Make Sonnet the default, Opus the escalation This is probably the setup I'd actually use. Start the task on Sonnet 5.5. If it hits: • Ambiguity • High stakes • Deep strategy • Very complex coding • Important final review → send it to Opus 5.5 Sonnet does the work. Opus handles the moments where the extra intelligence actually changes the outcome.frozen24d ago5.8K701070.26%
if you're ambitious with AI, read this twice: "AI is making the shallow parts of work cheap. the edge is becoming the depth you only get by staying." read it, bookmark it, then read it againfrozen22d ago5.8K711090.31%
Alexandria is an insanely well thought out name for an SI Library just saying https://t.co/qZoGdOjz2efrozen29d ago5.6K410010.11%
you're telling me Polar can now take 30 seconds of typing and turn it into what they say is 100 hours of GTM work..? > find accounts that match your ICP and research each company > find the decision makers and enrich the leads, work that normally takes an SDR's whole week >check replies and prep the follow-ups on its own all of that without a person copying rows between five tabs and a spreadsheet and once it works, you save the workflow and run it againfrozen29d ago5.5K500030.14%
your competitors are changing pricing, messaging, products + positioning all week. you shouldn't have to manually notice. here's how i'd build a 24/7 competitive intelligence agent: 1. make a competitor list with only the companies that actually matter. include their website, pricing page, changelog, docs, careers page, X/LinkedIn, review pages + any founder accounts worth watching. 2. save a baseline before monitoring anything. homepage copy, pricing, packages, features, target customer, positioning, integrations + major claims. without the old version, “something changed” isn't very useful. 3. check the highest-value pages daily: homepage, pricing, product pages + changelog. compare the new version against the last saved version and keep the actual diff. 4. watch product launches separately. new features, integrations, APIs, model support, acquisitions + partnerships can change how you position against them overnight. 5. track hiring because it tells you where they're investing before the product catches up. 8 new enterprise AEs, a head of partnerships, 4 ML engineers or a first international GM all say something different. 6. collect customer complaints from G2, Reddit, X + support communities. cluster repeated complaints by product area, customer type + frequency. competitor weaknesses are much more useful when customers keep saying the same thing. 7. watch pricing closely. save new tiers, limits, discounts, free-plan changes, usage caps + packaging. pricing changes can tell you which customers they're moving toward or away from. 8. keep a positioning history. every time the homepage headline, category, ICP or main promise changes, save the old + new version. after a few months you can see where the company is trying to move. 9. connect every finding to a decision. pricing change → sales battlecard. repeated complaint → product opportunity. new enterprise push → positioning review. new integration → partnership or roadmap question. 10. score alerts before they reach you. HIGH = changes pricing, product, ICP or sales motion. MEDIUM = meaningful launch, hiring pattern or repeated complaint. LOW = normal content, minor copy edits + noise. 11. send one daily brief with only the important changes. company, what changed, source, old vs new + which team should care. everything else stays searchable in the archive. 12. once a month, have it compare every competitor across pricing, positioning, product, hiring + customer complaints and show which direction each company is moving. after a few months you don't just know what competitors look like today. you have a history of every important move they made.frozen4d ago5.4K20270441.34%
if you're building a second brain for AI, STOP overcomplicating it: “one topic per file. CLAUDE.md is the map the agent follows to navigate your knowledge.” plain markdown + a good map is ALL that you need. read this before you build another bloated knowledge system.frozen20d ago5.3K10200140.49%
“What we fear doing most is usually what we most need to do.” cold email is such a perfect example of this. 999 people can ignore you. yet you only need 1 right person to change your life https://t.co/nzDDBNNMW1frozen20d ago5.3K22100100.62%
the best use of AI might be creating your own opportunities. Jay Yang's playbook is simple: “The fastest way to the life you want is to help the people who already have it.” here's how i'd actually use AI to do that: 1. PICK 20 PEOPLE not just rich people. people whose: • work you respect • life you actually want • ideas you agree with founders, creators, operators, investors, whoever. make a list. 2. BUILD A RESEARCH FILE ON EACH ONE give AI their: • website • X account • newsletter • podcast appearances • YouTube • product • recent launches then ask it to map: • what they care about • what they're building • what they repeat constantly • where they're spending time • what seems neglected • what their team is hiring for 3. FIND THE GAPS don't ask: “how can i provide value?” too vague. ask: “what work around this person/company looks important but underdone?” examples: • weak landing pages • inconsistent content • no short-form clips • poor SEO • bad outbound • no competitor research • ugly decks • no automations • messy CRM • weak ad creative 4. MATCH THE GAP TO SOMETHING YOU CAN LEARN FAST you do not need to already be world-class. pick something AI makes much easier to get competent at: • copy • research • video • design • coding • automation • outbound • SEO • content then spend a week actually learning it. 5. BUILD BEFORE YOU ASK this is probably the highest-leverage part. don't email: “i'd love to help with content.” make: • 5 rewritten posts • a landing page teardown • 3 new ad concepts • a competitor report • a working automation • a redesigned deck • a small tool • an SEO opportunity map now the pitch has proof attached. 6. USE AI TO MAKE THE RESEARCH BETTER, NOT THE MESSAGE WEIRDER don't have an agent dig through 8 months of posts just to write: “loved your post about leadership!” everyone can smell that now. use the research to understand the person. then write the message like a normal human. 7. USE ALL 4 WAYS IN Jay calls this the Contact Quadrant: 1:1 + warm → referral 1:1 + cold → email / DM 1:many + warm → useful public content 1:many + cold → public pitch / teardown don't bet everything on one cold email. 8. TURN YOUR PITCH INTO CONTENT if you made a full teardown for a company and they never reply... post it. “here's how i'd rebuild X's onboarding” “7 ads i'd test for X” “how i'd grow X's SEO” now one failed pitch can still: • grow your audience • show your skills • attract another founder • become portfolio proof 9. KEEP A SIMPLE OPPORTUNITY CRM track: • person • company • why you picked them • problem you found • thing you built • date contacted • reply • follow-up • result AI can keep this organized and tell you who deserves another touch. 10. TAKE A LOT OF GOOD SHOTS one person can ignore you. 20 can ignore you. but if you: research 100 good people find 100 real problems build 100 useful things make 100 thoughtful pitches you are probably not ending the year in the same place you started. 11. SAVE EVERYTHING YOU LEARN every attempt should leave you with: • a better skill • better proof • better taste • better connections • a better offer • better understanding of what people pay for that's why this compounds even when the answer is no. 12. LET AI REMOVE THE BORING PARTS research transcripts competitive analysis drafting coding design variations CRM updates follow-up reminders keep the parts that actually require you: choosing who matters spotting the real opportunity judging quality building trust taking the shot the basic loop: find someone living a version of the life you want study what they need build something useful put it in front of them repeatfrozen7d ago5.1K52410832.73%
how to give an AI agent a company brain in 30 minutes: save this and build it once. 1. START-HERE.md this is the first file every agent reads. put: • what the company does • who it sells to • current priorities • important products • where the rest of the context lives keep it to one page. 2. customer-fit.md write down who actually buys + stays. BAD: “B2B SaaS companies” BETTER: “20-200 person SaaS companies with a small sales team, founder-led GTM, and ACVs above $10k” include: • best customers • bad-fit customers • buying triggers • common objections • reasons people churn 3. offers.md give the agent the exact commercial reality. • products • pricing • packaging • guarantees • approved claims • things you CANNOT promise • what requires approval this stops it from inventing an offer that sounds good but doesn't exist. 4. voice.md don't write: “professional but friendly” give it examples. add: • 5 pieces you love • 3 pieces you rejected • why each one worked / failed • words you use • phrases you hate • formatting rules examples teach way more than adjectives. 5. founder-opinions.md this is one of the most valuable files. write down what the founder actually believes about: • the market • customers • competitors • pricing • product • hiring • the future every company can access the same models. they can't access your founder's brain. 6. competitors.md for every real competitor: • what they sell • pricing • positioning • strengths • weaknesses • where you win • where they win add source links + dates. don't let a 9-month-old pricing page quietly become “current.” 7. decisions.md whenever the company makes an important decision, save: DECISION: what we chose WHY: why we chose it REJECTED: what we considered instead DATE: when this happened 3 months later the agent can understand WHY the company works the way it does. 8. failed-experiments.md save the expensive mistakes. examples: • free audit attracted companies too small to buy • LinkedIn generated leads but almost no closed revenue • enterprise trial was too long • this ad angle pulled the wrong ICP one line here can stop an agent from repeating a $20k mistake. 9. evidence/ this is where NEW information goes first. sales calls support tickets customer interviews analytics research competitor updates meeting notes important rule: agents can ADD evidence. they cannot turn evidence into company truth without approval. a random customer complaint should not rewrite your positioning. 10. projects/ give every active project its own page: goal owner status decisions blockers next step related files now the agent can answer: “what are we working on?” without reading 6 months of Slack. your company brain should look something like: company-brain/ ├── START-HERE.md ├── company/ │ ├── customer-fit.md │ ├── offers.md │ └── competitors.md ├── brand/ │ ├── voice.md │ └── founder-opinions.md ├── decisions/ │ ├── decisions.md │ └── failed-experiments.md ├── evidence/ └── projects/ then give your agents one rule: read START-HERE.md first. pull the files relevant to the job. don't guess when the answer isn't there. that's enough to make almost every agent you build after this noticeably better.frozen6d ago5.1K203120431.53%
if you’re busy all day but still feel like nothing important gets done, read this: “Your attention doesn't only affect what you get done today. It affects what becomes familiar, what grows, and what slowly disappears from your life. What you return to, again and again, becomes your life.”frozen22d ago5.0K18300170.76%
distribution IS the future right nowfrozen13d ago4.9K822020.29%
this is a genius move lolfrozen23d ago4.8K410020.15%
did OpenAI Dots just replace Grok Bot? > Dots work 24/7 for you > learn from your feedback > have their own computer, browser and can be connected to over 4k apps > They’re powered by Astra > Included in your Pro plan, without drawing down on any of your usage. this is HUGE for marketing teams.frozen23d ago4.7K931060.40%
if you want to make money with AI, this is a MUST read one accountant took a job that used to take 180 hours a year and got it down to 15. buy the customers + trust then use agents to completely change the economics of the businessfrozen23d ago4.7K6000100.34%
if you're building agents for real companies, internalize this: “Agent value = usefulness × correctness × timeliness ÷ noise × risk × interruption cost.” a good company brain knows when your agents should act and when they should shut upfrozen20d ago4.5K7211120.51%
Meta's ads team is not sleeping tonight they spent 15 years charging brands per thousand impressions to reach people who scroll right past the ad Relay just launched and deletes the part where you pay for reach AI makes the content, and 50,000 creators post it to audiences that already trust them, instead of brands buying a slot in the feed the consequence is their entire paid social line is now a worse version of a post from someone you actually follow…frozen21d ago4.5K1043070.53%
AI companies need to STOP selling “AI.” buyers do not wake up wanting agents, copilots, workflows or automation. they want: • more pipeline • lower CAC • faster sales cycles • fewer support tickets • less headcount doing repetitive work • more revenue per employee sell the problem disappearing. not the technology making it disappear.frozen12d ago4.4K10220110.57%
if you use AI to write anything, this is a MUST read: “Solving a mystery and writing a mystery are two very different things.” that explains SO much about why LLM writing still feels like LLM writingfrozen22d ago4.3K411030.21%
Alex Hormozi has one of the simplest frameworks for figuring out why an offer isn’t selling: Value = (Dream Outcome × Perceived Likelihood) / (Time Delay × Effort) before rewriting your landing page or buying more ads, check these 4 things: 1. DREAM OUTCOME what does the customer actually want? “8 weeks of sales coaching” is the product. “book 15 qualified sales calls” is the outcome. simple, sell the second one. 2. PERCEIVED LIKELIHOOD how sure are they that YOU can get them there? increase it with: • case studies • specific proof • guarantees • demonstrations • a clear process 3. TIME DELAY how long until they get something they care about? find a way to give them a win earlier. day 1 > week 4. 4. EFFORT how annoying is your product to actually use? remove: • setup • learning curves • unnecessary steps • manual work • decisions they shouldn’t have to make if an offer is struggling, I’d audit these 4 variables before touching the copy. a stronger offer makes every channel downstream way easier.frozen16d ago4.2K12110110.59%
Vercel now resolves 91% of support with an agent. And that's not the only team: All inbound qualification → agent A lot of outbound → agents RevOps questions → data science agent And they've raised sales quotas every 6 months. what happened to the humans? Support started finding actual product problems + writing PRs. BDRs moved into complex enterprise prospecting + testing new plays. Sales reps started carrying more revenue per person. this is a pretty insane look at what lean GTM teams are becoming.frozen14d ago4.2K331010.19%
chat is a terrible interface for anything that should be clicked, moved, compared, or explored. OpenUI lets Opus 5.5 turn those answers into live interfaces using components you control. charts, maps, sliders, tables, forms, dashboards... here's how to build it: 1. start with OpenUI. it lets the model choose from components YOU define: cards, charts, maps, tables, forms, buttons, etc. the model decides what the answer needs, but it never writes arbitrary website code. 2. run the starter: pnpx @openuidev/cli@latest create --example open-intelligent-ui that creates the project, installs everything + gives you a working generative UI app. 3. connect a model through OpenRouter. add LLM_BASE_URL, LLM_API_KEY + LLM_MODEL to .env. now you can swap between Opus 5.5, Gemini, Muse Wonder, Qwen, GLM, Kimi or whatever else you want. 4. run npm run dev and open localhost:3000. ask for something that SHOULD have an interface, like “plan a day in San Francisco.” if it gives you a map/cards instead of paragraphs, it’s working. 5. define the components your product actually needs. SaaS analytics? charts + tables. travel? maps + itinerary cards. finance? sliders + calculators. sales? account cards + pipelines. keep the component set narrow enough that every answer still looks like YOUR app. 6. let the model choose the interface at runtime. one prompt might return a chart, another a table, another a form. you don’t need to hard-code a separate screen for every possible request. 7. add a model picker while testing. the same prompt can produce very different UI quality across models. in the article, Opus 5.5 was the most reliable across the tests. 8. compare models on real product prompts, not generic benchmarks. try the exact things your users ask for: budget allocation, order analysis, travel planning, account research, reporting, etc. 9. keep validation in the loop. OpenUI’s hosted path can catch/fix small model mistakes before rendering. going directly through a model API shows you the raw output, including failures. 10. start with ONE workflow your users already ask for constantly. if they keep asking for a report, turn it into a dashboard. if they keep asking for comparisons, turn it into interactive cards. if they keep asking for plans, give them something they can edit. the easiest way to make an AI product feel 10x better is by giving it a better interface.frozen5d ago4.2K12260210.98%
that was quick... i was inactive for 3 years and came back and just over a month later i am eligible to get paid again this is what a good content strategy can do work on yours https://t.co/tVlBvCHpQsfrozen29d ago4.0K310010.12%
you’re telling me this is $1,500 CHEAPER than the new 64GB DGX Spark??? Core is $3,499 and you get: • RTX Pro 4000 Blackwell • 24GB GDDR7 VRAM • 64GB DDR5 • fully local models • context that builds 24/7 • connects to your apps, files + devices • a proactive agent that can act without waiting for a promptfrozen17d ago3.8K501050.29%
GTM Engineer might be the highest-ROI hire in GTM right now. David Politis says one killer person making $100k-$120k can have the output of ~20 RevOps / marketing ops people. they're building: • micro-segmentation • custom data pipelines • account research • personalized decks • internal GTM tools • workflows the CRM can't do and they're building in a WEEK what companies were stuck on for months. if you're young and trying to figure out where AI creates new careers... I'd study this role very closely.frozen14d ago3.8K700090.42%
this is nuts: Vercel COO Jeanne Grosser just explained what their GTM org looks like after actually putting agents to work. • 91% of support gets resolved by an agent • ALL inbound qualification is handled by an agent • a lot of outbound is agent-run • RevOps questions can go straight to their data science agent and the humans moved up the stack. support now spends more time finding real product problems + writing PRs. BDRs spend more time on complex enterprise prospecting + testing new plays. sales reps are carrying more revenue per head. so if you're building a GTM team right now, stop asking: “where can AI save us 20%?” start asking: “what work can agents completely absorb so our best people can move up a level?” this 3-minute clip is probably one of the clearest looks at where GTM orgs are heading.frozen15d ago3.8K8120100.56%
i broke this brand masterclass down into 15 rules. how to build a brand people actually care about in 2026: 1. find brand-market fit before chasing growth. people should instantly understand what you stand for, who it’s for, and why they should care. 2. own a category if you can. being the only obvious option is much stronger than being slightly better than 50 competitors. 3. decide what emotion your brand should create: smart, early, belonging, confident, inspired, rebellious, etc. 4. tell the story publicly. share what you’re building, what you believe, what’s working, and what you’re struggling with. 5. make the audience the hero. every piece of content should give them something worth their attention. 6. keep the same story everywhere. the format can change by platform, but the positioning and emotion shouldn’t. 7. build both founder-led and brand-led content. the founder builds trust; the brand account scales product distribution. 8. use TOF content to get discovered, MOF content to build trust, and BOF content to turn that trust into customers. 9. your content pillars should sit at the overlap of what your audience cares about, what you’re credible on, and what naturally connects to your product. 10. package the same idea differently for each platform. X, YouTube, short-form, newsletters, podcasts, and communities all reward different behavior. 11. treat social as rented distribution. use it to find people, then move them into channels you actually own like email, newsletters, or community. 12. don’t confuse audience with community. community needs identity, shared beliefs, recognition, rituals, and a place people can actually interact. 13. start collecting emails from day one. even if the newsletter isn’t perfect yet, owned distribution compounds. 14. every organic post should have a job: get new eyeballs, build trust, or convert. 15. study and repackage your winners. one good idea should become multiple formats instead of dying after one post.frozen10d ago3.7K18230321.47%
if you're a creator who doesn't want to depend on brand deals or platform payouts to make money from your audience, read this: “You have a $100,000 digital product stuck in your head. Or in your hard drive. Or in your workspace.” one of the best step-by-step breakdowns I've seen on turning what you already know into something people will actually buy. make sure you bookmark it.frozen13d ago3.6K20110181.10%
this is insane: Higgsfield had a customer go from a $99/month subscription to a $6M/year deal in 6 MONTHS... if you want to understand where AI video is actually heading, watch this 3-minute clip. Alex Mashrabov says DTC companies are rebuilding their entire GTM around AI: • hundreds or thousands of ads every week • constant creative testing • AI-generated short-form content at scale and the revenue already reflects it. just over 50% of Higgsfield's revenue now comes from businesses. less than 10% comes from mobile. his conclusion is pretty clear: they're never going to win by fighting for $20/month subscriptions. the real market is companies rebuilding how they create + distribute content.frozen10d ago3.6K16220150.97%
this launch is WAY bigger than "AI privacy"... for the last three years, every AI assistant has worked the same way you type a message, it travels to a data center, a giant model answers, and a copy of the conversation stays on someone else's server (incredibly dangerous if someone gets access) that one design choice shaped everything about how we use AI: - privacy became a setting you have to go find, instead of something built in - your chats can end up stored, reviewed or used to train the next model - every answer costs the company server time, so you pay a subscription and still hit message caps - it stops working the second you lose signal we accepted all of that because the good models were too big to run anywhere else that's the part that just changed a free model running on a Mac through Loci now outscores Claude Opus 4.6 on the Artificial Analysis Intelligence Index for everyday writing, summaries, files and planning, the laptop you already own is enough once the AI runs on your own hardware, the rest of the trade-offs fall away with it your chats stay on your device, so there's nothing to train on and deleting a chat deletes it there are no servers to pay for, so it can be free with no cap. and it keeps answering on a plane or in a dead zone local AI has existed for a while, but it lived in apps built for tinkerers what Loci is doing now is the piece that makes it mainstream: putting it inside iMessage, WhatsApp, Telegram, Discord and Slack, the places people already talk all day the honest truth though... the hardest reasoning problems still need the biggest cloud models, and a phone runs a smaller model than a high-end Mac so I don't think the cloud goes away i think the default flips your personal, everyday AI runs on your own machine, and the data center becomes the thing you call for the heavy lifting that's a very different industry from the one we've been building toward, and I'm curious how fast the big players respondfrozen5d ago3.6K1844090.98%
if you're trying to make yourself more valuable in tech, read this article: “Anyone can learn to write, but no one wants to because they know it takes a long time to perfect.” AI made average writing incredibly cheap. being able to think clearly, develop taste, and communicate like an actual human is becoming MORE valuable.frozen11d ago3.5K11120140.80%
this should be tattooed on every AI builder’s forehead: “Reading one good answer tells you nothing about the next hundred.” the rest of this breaks down how to actually know if an AI system works: • what to eval • how to grade it • when LLM judges lie to you • how to measure agent reliability • why benchmark wins can mean nothing for your product save this one. you’ll want to come back to it.frozen14d ago3.5K29410422.18%
ChatSEO hit its first $50K month 11 months after launch, with 95% of the revenue coming organically. the playbook is basically 5 rules: 1. sell where people already search. Google, Reddit, X, TikTok, YouTube. start with the queries buyers are already typing instead of hoping the feed gives you reach. 2. steal formats, not content. find 3-5 accounts in your niche that consistently win, study 20-30 posts from each, and save the hooks, formats, CTAs + angles that keep repeating. 3. earn trust before you sell. tutorials, breakdowns, numbers, full systems. give people enough useful stuff that by the time they see the product, they already know you’re worth listening to. 4. keep the CTA simple and consistent. one line, same place, every time. don’t bury it and don’t turn the post into an ad. 5. recycle every result. viral post → run it again later. strong idea that missed → new hook. real number → turn it into content on every other platform. if i was launching a new product tomorrow, i’d do exactly what they recommend: - pick one platform. - find what people search. - study what already works. - post every day for 3 months. - turn the first real result into the next piece of content.frozen4d ago3.4K13110231.11%
ElevenLabs took webinar pipeline from ~$100K to $8M+ in H1. Luke Harries breaks down the exact system behind it: • turn what already works into a repeatable process • template every step • automate the bottlenecks • map who gets invited, how they show up, the content, and follow-up • set goals big enough that the old process can’t get you there watch these 3 minutes very closelyfrozen17d ago3.4K410080.39%
i broke this video down into 15 things. how Wispr Flow builds founder-led content: 1. run organic + paid together. Hector uses organic to test messaging quickly and see what resonates, then paid gives you a way to put money behind the messaging that works. 2. paid by itself can get people to take action, but those people might barely know or care about the company. that’s the first company he draws on the board. 3. organic can make people know you, love you + care about what you’re building, but attention alone doesn’t guarantee they take action. that’s the second company in his example. 4. the strongest setup does both. build the audience and trust organically, then use paid to push the people who already care toward the product. 5. founder-led content can turn someone who has never seen your product into a fan who knows the founder, understands the mission + actually cares where the company goes. 6. founders have an advantage because they already have the stories. the battles, ups, downs + reasons behind what they’re building give them something much better to talk about than constantly selling the product. 7. prioritize YouTube. Hector says it has the longest half-life of the major content platforms and a good video can keep generating views + customers 5, 6, 8 or 10 years later. 8. compare that with fast social feeds. he says posts on X, Instagram or TikTok can get their run and be basically dead within 24-48 hours. 9. YouTube can have the best ROI for a founder because you can block out a couple hours, bring a videographer along while you work + capture content from what you were already doing. 10. watch time builds trust. when people spend a long time watching a founder, they get to know them much faster than they would from a few short posts. 11. the first major content hire is a Head of Content. Hector looks for someone who understands social platforms and has grown an audience themselves, with a rough cost of $10K-$60K/month depending on skill + track record. 12. underneath that, he puts video at roughly $7K-$15K/month, short-form around $1K-$3K/month, and a dedicated YouTube team around $5K-$25K/month. 13. YouTube needs specialists because there are too many places to lose: title, thumbnail, opening seconds, research, story + the rest of the video. he says you can make something with Hollywood-level production and still lose if the packaging sucks. 14. the content team needs to understand the company deeply: mission, vision, where it’s going, pivotal founder moments, struggles + why the founders are obsessed with the problem. Wispr spent about a month with an agency building the company/founder story before deciding what stories to tell. 15. build the content roadmap like a product roadmap. product launches, new features, founder moments, ambassadors, news, wins + low moments all become chapters. then package them into formats like vlog/documentation or educational content, prioritize quality over quantity on YouTube + keep testing new formats.3d ago3.3K15120191.12%
AI SEO goes wrong way earlier than most people think. “Everything downstream of a guess is a guess.” Claude can write pages, add internal links, generate schema, analyze exports, and run the same checks every week. but it does NOT know your: • search volume • rankings • impressions • live SERP • competitors taking your traffic give the model real data first. then let it do the work. this article is basically a full operating system for doing that properly.frozen9d ago3.3K6020170.76%
this is WILD: Legora says it became the fastest company ever to go from $0 → $100M with a direct sales motion. Patrick Forquer joined at ~$3.5M. they exited last year at $70M. hit $100M at the start of this year. and he says TWO GTM decisions mattered most: 1. treat the pilot like the sale when you're creating a category, customers don't already know what “good” looks like. so Legora made the pilot elite: • education • adoption • ROI • use-case discovery • responsiveness • actually delivering value before the contract most customers tried before they bought. 2. hire 2 post-sale people for every 1 pre-sale hire implementation. change management. ongoing transformation. because as he puts it: “unless people actually implement and use it… all the ARR, our growth doesn't matter.” a lot of AI companies obsess over getting the deal. Legora obsessed over making sure the product actually became part of how the customer worked. this 4-minute clip is probably one of the best GTM breakdowns I've seen from a company scaling this fast.frozen12d ago3.2K822080.63%
if you're launching a product in the next 30 days, steal this 4-week launch calendar. WEEK 1 start broad and beginner-friendly. teach the problem, explain why it matters, and introduce the product lightly without making every piece of content about buying. if you're using a launch discount, this is also where you can open at the lowest price and make it clear that the price will increase as the launch moves forward. WEEK 2 go deeper into the same problem by explaining the consequences, common mistakes, and your point of view on solving it. keep the email cadence simple: one useful newsletter, one story with a CTA, and one short reminder before the next price increase. you want people hearing about the offer consistently without burning them out before launch week. WEEK 3 release a lead magnet that teaches the framework behind your product and helps people understand the path from their current problem to the outcome they want. use that lead magnet to identify people who are actually interested, then start conversations with them. this is also the week to reach back out to previous customers, old leads, and people who already showed buying intent. WEEK 4 make the launch hard to miss. post about the product every day, send short emails, answer objections, show proof, explain who the product is for, and keep reminding people exactly when the offer closes. on the final day, the sequence can be as simple as 24 hours left, 12 hours left, and 3 hours left. the content should also match how aware the buyer already is: PROBLEM UNAWARE → help them notice the pain. PROBLEM AWARE → explain what the problem is costing them. SOLUTION AWARE → teach useful ways to solve it. PRODUCT AWARE → explain your process and why your approach works. MOST AWARE → answer objections and give them a clear reason to act now. once the launch closes, use the next few weeks to deliver, collect feedback, improve the product, and build stronger proof for the next launch. then run the same cycle again with a better product and better evidence.1d ago3.1K20110391.94%
how i'd set up a 24/7 GTM research bot in 45 minutes: - give it 5 files to start: ICP, offer, competitors, positioning, and do-not-repeat.md - connect it read-only to your CRM, Gong/Fathom, support inbox, X, company changelogs + news - track buying signals: funding, hiring, exec changes, pricing changes, new products, new markets + anything else that creates a reason to buy - once a week, pull exact phrases from sales calls + support tickets. save the words customers actually use, not a cleaned-up summary - keep a competitor log. pricing, homepage copy, launches, hiring, complaints. only show what changed since the last check - watch 20-30 accounts + keywords on X. save outlier posts, repeated questions, new angles + anything your ICP keeps talking about - every item needs the source, date, company/person, and one sentence on why you saved it - use KEEP / HOLD / SKIP on the daily brief so it learns what you actually care about - cap the morning brief at 10 items. best accounts to contact, strongest customer language, competitor changes + content ideas - once a week, dump the best findings into one page so the research doesn't disappear after you read it - keep email sends, CRM edits + public posts behind approval if the morning brief takes more than 3 minutes to read, it's doing too much.frozen8d ago3.0K17211251.53%
Grok Bot just made founder-led content way easier. your founder already forwards customer emails, voice notes, screenshots, Slack threads + things they have opinions about all day. now each one can trigger its own content routine. the setup is 2 aliases, 3 folders + 1 Friday routine. FOLDERS /voice → save 10 posts the founder actually wrote themselves. pick the ones that best represent how they think, explain things + structure posts. /proof → save screenshots, reports, customer emails, dashboards + anything that supports a claim or number. /drafts → every X and LinkedIn draft waits here until someone approves it. 1. MAKE A CONTENT ALIAS create yourbot+content@ and have the founder forward anything worth talking about: customer emails, voice memos, internal debates, lost deals, product decisions, competitor launches + strong opinions from the week. paste this routine: "When an email arrives here, find the strongest opinion, story or lesson inside it. Preserve the founder's wording wherever possible and use /voice as the style reference. Create one X draft and one LinkedIn draft. If the email contains a number or factual claim, check /proof for supporting evidence. If you cannot find support, remove the claim and flag it in the notes. Before drafting, search X for this topic from the past 7 days. Check whether the founder already posted the same idea, which posts on the topic are outperforming, which angles have already been used heavily + whether there is a strong post worth quote-posting instead. Save the finished drafts to /drafts and send them to me for approval. Never publish anything." 2. MAKE A PROOF ALIAS create yourbot+proof@ and forward customer results, screenshots, reports, useful emails + interesting numbers whenever they show up. paste: "Save every attachment or forwarded email to /proof with the date, company/person, what the evidence shows, which claim it can support + the original source. Keep the original file or message attached." 3. BUILD A LIBRARY OF GREAT CONTENT pick around 100 strong X accounts across your niche, adjacent niches, founders, marketers, GTM people + writers with great packaging. save their outlier posts with the source, hook, topic, format, proof used, payoff + why you think it worked. now the bot has hundreds of examples of packaging that already performed instead of inventing every hook from scratch. 4. SEARCH THAT LIBRARY BEFORE EVERY DRAFT when the founder forwards something about pricing, onboarding, sales, hiring, AI, etc., search the library for related winners first. the bot should be able to see whether the topic worked better as a teardown, quote post, numbered playbook, story or short take, then use the founder's own material inside that structure. 5. CHECK THE FOUNDER'S OWN POSTS search the last 90 days before drafting. if they already made the same point, only reuse it when there is new evidence, a new story, a better example or a timely reason to bring it back. 6. LEARN FROM THEIR EDITS every Friday run: "Compare this week's approved posts with the original drafts. Find edits the founder made repeatedly, including shortened intros, deleted phrases, changed claims, replaced words, removed explanations + formatting changes. Only add a new writing rule when the same preference appears more than once. Update /voice with the rule and an example." 7. TRACK WHERE THE GOOD POSTS COME FROM tag each published post by source: CUSTOMER, PRODUCT, SALES, FOUNDER OPINION, COMPETITOR, INTERNAL DEBATE, MARKET NEWS or X RESEARCH. after a month, compare bookmarks, follows, replies, profile visits + inbound conversations by source. you'll know which parts of the company consistently produce content people care about. 8. KEEP APPROVAL ON Grok Bot can find the idea, research the angle, check the proof, search X, draft the posts + learn from edits. the founder forwards things worth talking about and approves what goes out.3d ago3.0K11100281.34%
David Politis says ONE great GTM engineer can have the impact of ~20 RevOps / marketing ops people. $100k–$120k salary. And in a week, they’re building things companies have been stuck on for months: • micro-segmentation • data pipelines • custom sales decks • enrichment • internal GTM tooling • workflows CRM can’t do out of the box He called it the highest-ROI role he’s seen in his career from a demand + growth perspective. Matt Amundson agreed: the pace is basically “light speed” compared to how GTM teams used to operate. this role is going to be everywhere.frozen16d ago2.9K612040.45%
this is a pretty insane marker for where AI is heading: Isomorphic Labs, the AI drug discovery company spun out of Google DeepMind, is reportedly already in talks to raise at a $40B+ valuation. some of the biggest AI companies may end up making their money outside software entirely.frozen12d ago2.9K825150.72%
if you're running a small marketing team, you should have systems doing the work for you. research, content, creative, distribution, lifecycle, paid, analytics, experiments. here's the marketing system i'd build: ⁠1. make one marketing database with 7 buckets: CUSTOMERS, CONTENT, CREATIVE, CAMPAIGNS, COMPETITORS, EXPERIMENTS, PERFORMANCE. every campaign, post, ad, landing page + email should eventually connect back to this. ⁠2. build a customer-language pipeline. pull sales calls, support tickets, reviews, churn interviews + customer emails into one place and tag pains, objections, desired outcomes, buying triggers + exact phrases worth reusing. ⁠3. turn that research into a weekly content queue. save repeated customer questions, competitor moves, product updates, strong opinions + outlier posts from your market, then rank them by relevance before anyone starts writing. ⁠4. keep a swipe file for creative. every ad, landing page, email or post worth studying gets saved with its hook, angle, format, offer + reason it caught your attention. when you need new creative, you already have references. ⁠5. give every campaign one ID and carry it through the ad, UTM, landing page, form, CRM + revenue data. six weeks later you should still be able to tell which campaign created the pipeline. ⁠6. build reusable templates for work that repeats: launch brief, ad brief, landing page, newsletter, case study, social post, experiment report + weekly recap. the team should spend time on the idea and execution instead of rebuilding the process. ⁠7. create a distribution checklist for every strong piece of content. decide what becomes an X post, LinkedIn post, email, short video, sales asset, founder post + website update before publishing the original. ⁠8. keep one running list of creative angles that are working. pain, status, comparison, speed, cost, proof, objection, use case, before/after. tag every asset by angle so you can see which reasons to buy keep producing results. ⁠9. connect marketing directly to sales. every week, pull the objections sales heard, questions prospects kept asking, deals that moved quickly + reasons deals died. those should influence the next ads, pages, emails + content. ⁠10. run experiments from one backlog. each test needs the hypothesis, audience, change, primary metric, start date + result. keep the losing tests too so the same idea doesn't get repeated three months later. ⁠11. automate the reporting nobody should spend hours assembling. one dashboard should show traffic, leads, conversion, pipeline, revenue, CAC, content performance + active experiments, with the ability to trace a result back to the campaign that created it. ⁠12. send one weekly marketing brief with a hard cap: what grew, what fell, which creative won, which campaign created pipeline, what customers kept saying + the 3 things worth testing next. ⁠13. keep a permanent library of winning assets. ads, hooks, landing pages, emails, offers, case studies + campaigns should stay searchable with their audience, angle, performance + date. six months of good marketing should make month seven easier. ⁠14. tie the whole system to the company's current goal. need pipeline? pull the strongest buying triggers, winning offers + highest-converting channels. launching a product? pull customer language, competitor positioning, proven creative + the questions sales is already hearing.17h ago2.8K7210150.90%
so you're telling me Jobright's AI Recruiter can now... - pull candidates from 3M+ people already looking - screen out the fake ones before they hit your calendar - drop the yeses straight into your Slack all you do is interview recruiting is changing insanely quickfrozen9d ago2.7K512070.55%
Nooks CEO Dan Lee’s take on the future of sales deserves WAY more attention than it’s getting. His argument: the best sales teams won’t be armies of junior SDRs. they’ll be a few great salespeople with agents doing almost everything around them. the agents handle: • account research • prioritization • finding the right people • emails + calls • follow-up • account execution the human is still needed to: • understand the account • choose the strategy • knowwho to influence • decide the next move • think 2-3 moves ahead his analogy is perfect: AI can push the pawn. the key is knowing whether moving that pawn actually helps you win. if you work in sales, watch this.frozen14d ago2.7K411050.40%
so you're telling me I can now automate my LinkedIn?? - finds prospects that match my ideal customer in 5 minutes - researches each candidate and explains why they fit, which used to take 3+ hours in a day - drafts personalized outreach for every one of them, right inside LinkedIn all of that without copying profiles into a spreadsheet one tab at a time took me 5-7 minutes to set up, and I can take over whenever I want pretty cool to seefrozen3d ago2.5K14110131.14%
Grok Bot can read your X bookmarks now. if you have hundreds of saved posts you'll probably never open again, i'd set this up: turn your bookmarks into a Notion brain. 1. MAKE 5 DATABASES IN NOTION BOOKMARKS every post you save. fields: • post • author • date saved • category • why it matters • status • source link PEOPLE people worth remembering. fields: • name • X profile • company • what they talk about • why you follow them COMPANIES companies that keep showing up. fields: • company • category • people • products • notes TOPICS the stuff you're repeatedly learning about. examples: • Claude Code • GTM engineering • AI SEO • agents • content distribution • model releases PROJECTS things you're actively working on. 2. CONNECT X + NOTION TO GROK BOT X should be read-only. let it: • read bookmarks • open posts • read threads • check profiles • search X then give it access to the Notion brain. you don't need it posting, liking, following or DMing anyone. 3. BACKFILL YOUR OLD BOOKMARKS ONCE don't dump 2,000 summaries into Notion. have Grok Bot go through the backlog and decide: SAVE SKIP DUPLICATE SAVE only if the bookmark contains: • a useful idea • a workflow • a company worth tracking • a person worth remembering • a tool • a number/stat • something related to a current project everything else can stay on X. 4. DON'T SAVE SUMMARIES for every saved bookmark, have it write: WHAT I SAVED: the actual idea worth remembering WHY: why someone would care about it USE FOR: content / research / build / GTM / company / person / project RELATED: other Notion pages this connects to SOURCE: original X post a 12-paragraph summary is just another thing you'll never read. 5. RELATE EVERYTHING this is where Notion makes it much better. a bookmark about Claude Code agents could link to: Topic → Claude Code Person → Boris Cherny Company → Anthropic Project → Claude Code setup post a Virlo bookmark could link to: Topic → short-form intelligence Company → Virlo Person → Nic Mauro Project → paid partnership now one bookmark can show up in several places without being copied 4 times. 6. RUN BOOKMARK INTAKE EVERY NIGHT have Grok Bot check everything you bookmarked that day. for each new post: 1. check if it's already in Notion 2. decide SAVE / SKIP 3. add the useful part 4. tag it 5. connect it to existing people, companies, topics + projects 6. create a new page only when one doesn't already exist keep a processed bookmark ID so it never does the same post twice. 7. KEEP CLAIMS ATTACHED TO THEIR SOURCE if someone posts: “we grew 300% after doing X” don't save: Company grew 300% after X. save: CLAIM: author says the company grew 300% after X SOURCE: link VERIFIED: no your Notion brain should remember where something came from, not slowly turn X posts into facts. 8. BUILD TOPIC PAGES AUTOMATICALLY if you save 15 things about AI SEO, the AI SEO page should start becoming useful by itself. something like: AI SEO BEST IDEAS • ... • ... WORKFLOWS • ... • ... TOOLS • ... PEOPLE • ... COMPANIES • ... OPEN QUESTIONS • ... RECENT BOOKMARKS • ... now you're not just searching through your bookmarks. 9. CONNECT BOOKMARKS TO CURRENT PROJECTS if you're writing a post about Grok Bot, ask: “search my Notion brain for everything I've saved about Grok Bot, personal agents, memory and Notion workflows.” if you're researching a company: “show me every bookmark, person and note related to Virlo.” if you're building something: “what have I saved in the last 6 months that could help with this?” 10. MAKE A WEEKLY DIGEST every Sunday: • best 5 things I saved • topics I bookmarked repeatedly • new people worth following • companies that kept appearing • ideas connected to current projects • things worth testing • old bookmarks that became relevant again link every item back to Notion + the original post. 11. RESURFACE OLD STUFF once a week, have it find 5 old bookmarks that match what you're working on NOW. not random “on this day” resurfacing. if you're suddenly building a sales agent, an 8-month-old post about account research should come back. if you're writing about AI SEO, old SEO bookmarks should come back. that's the stuff X bookmarks are terrible at. 12. GIVE GROK BOT THIS RULE “X is the inbox. Notion is the memory. never treat the bookmark list itself as the knowledge base. extract what is worth keeping, attach it to the right people / companies / topics / projects, preserve the source, and bring it back when it's relevant.” at that point bookmarking something actually does something. you save a post once. Grok Bot files it, connects it, and can find it again months later.frozen7d ago2.5K5140120.87%
operator: "911, what's your emergency?" me: I'd like to report the murder of ChatGPT Dots operator: "wait... Dots was alive?"1d ago2.5K801050.57%
post stuff you'd be proud to post for $0 good content first payout second pretty nice when you do both and make a bit of money https://t.co/PlzWVaVdWefrozen13d ago2.4K810030.50%
paying $20 a month for AI is cooked only way forward is free AI that lives on your own devicefrozen6d ago2.4K811050.63%
Meta just released Muse Wonder TODAY. 3 things stand out from the release: 1. ACTIVE MEMORY it can carry the people, decisions, preferences, failed attempts + context that matter across conversations. 2. ACTIVE FOCUS it can stay on the same goal, try another approach when something fails, and adapt when new information changes the plan. 3. LONG-RUNNING AGENT WORK Wonder was built for agents that need to keep working across time and maintain state between sessions. those 3 things make these workflows WAY more useful:frozen10d ago2.4K410060.46%
Grok Bot can now watch X, work across your apps, build decks, run routines, and hand work between specialist bots. GTM is the obvious use case. here are 10 workflows I’d build with it: 1. X INTENT RADAR every morning: • scan X for ICP accounts talking about your problem • watch target accounts for launches, hiring, funding + complaints • check who engaged with your posts • cross-check CRM + Gmail so current deals never show up as "new" • rank everything KEEP / HOLD / SKIP • draft the warmest first touches you wake up with today's best accounts already picked. 2. OUTBOUND BOT for every approved account: • research the company • find the right 2-3 people • pull recent signals • write the first touch around WHY NOW • draft LinkedIn + email together • stage the follow-ups • stop if they reply or enter pipeline you approve the batch. the bot keeps the machinery moving. 3. PRE-CALL BOT 15-30 minutes before every sales call: • read the CRM • read past emails • read previous call notes • check recent company news • map the stakeholders • pull relevant proof/case studies then give me: • what changed • what they care about • what I need to learn • 3 questions worth asking • the ONE outcome I should leave the call with 4. POST-CALL BOT meeting ends. within minutes: • summarize what actually mattered • pull objections • identify commitments • draft the follow-up • propose the next CRM stage • create the tasks • flag anything we promised nothing sends without approval. 5. CAMPAIGN LAUNCH TEAM give it a new product + target customer. specialist bots handle: • demand research • competitor research • positioning • search structure • ad variants • landing page outline • campaign shells • conversion tracking • reporting setup then hand the decisions back to the marketer. SpaceXAI is already using Grok Bot this way for its own paid media. 6. PAID MEDIA WATCHDOG every morning: check every ad channel. ONLY message me if: • spend is way off pace • a channel stops spending • conversions suddenly disappear • lead quality falls • tracking breaks then show me what changed + where to look. I do not need another dashboard I have to remember to open. 7. SOCIAL → PIPELINE this one is insanely useful. have one bot watch: • X replies • mentions • target accounts • relevant conversations • people engaging with your content when someone shows real buying intent: Social Bot → Outreach Bot → Sales Bot the context follows them through the entire handoff. 8. CUSTOMER FEEDBACK LOOP every week: combine: • sales calls • support • customer emails • feature requests • churn reasons • product usage cluster the repeated problems. then rank each theme by: • frequency • accounts affected • pipeline affected • revenue affected once something crosses your threshold, turn it into a product brief. when the feature ships, automatically find everyone who asked for it and draft the follow-up. 9. PROPOSAL + DECK BOT this got better literally this week. after a serious sales call, give the bot: • transcript • stakeholder map • pain points • relevant case studies • pricing • next-step goal have it build the actual personalized deck. PowerPoint or Google Slides. then you edit the 20% that actually requires taste. 10. GTM CHIEF OF STAFF make your primary Bot the front door. every morning it combines: • pipeline • meetings • inbox • X signals • campaign problems • customer issues • work from every specialist bot and gives you ONE action list. then it proactively spots work it can take off your plate instead of waiting for another prompt. the setup rule I'd steal: one bot = one job. one primary bot = one front door. anything customer-facing = approval first. bookmark this and build them one at a time.frozen13d ago2.3K610030.44%
the fastest way to make a cold DM feel automated is trying too hard to make it feel warm. people have been taught that every cold message needs some personalized opener. so now agents dig through your profile, find one tiny detail, and force it into the first sentence so the message LOOKS handwritten. which almost makes it worse. you can feel when someone knows your work. and you can feel when software went hunting for a detail to manufacture familiarity. a cold DM does not need to pretend there’s already a relationship. it needs: • a real reason you picked that person • something relevant enough to deserve their attention • a clear point • an easy reply if you genuinely noticed something they said, mention it. if you didn’t, don’t fake it. being direct feels more human than fake warmth ever will. master cold DMs and it'll change your life.frozen8d ago2.1K601050.58%
i seriously don't think i've seen a bad article from this accountfrozen8d ago2.0K411040.51%
if you write content for a living, this is a must read “once you know what the feed is doing to your brain, it changes how you think about every post you write.” read it, bookmark, and go write your next post5h ago1.8K13110242.12%
if you're trying to use ai better as a software developer, i'm begging you to use pstack read this article, bookmark it, give it to your agent, and read it again until you fully understand it. https://t.co/vs6G7SNM5g25d ago839110010.36%
this article + this free course = becoming rich just saying https://t.co/UFMq3QH3N727d ago605100010.33%