Marketing and communications leader. 25 years at the moments that change a company: rebrands, M&A, a PE exit, an IPO. Founder, Ballintra. NYC.

New York, NY
Joined December 2008
Building Ballintra in public. It's a marketing firm run on a different model: senior leadership, AI agents for speed, global talent for craft. I'm building the brand and the playbook with AI by my side. I'll share what works and what doesn't. ballintra.com
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My full fireside conversation with @patrickc at the Science: A New Golden Age Summit. We discussed building new institutions for discovery, accelerating scientific progress, and how America can move faster on the hardest scientific challenges.
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Robert Burke retweeted
HABITS I STOLE FROM A McKINSEY PARTNER WHO MADE SENIOR DIRECTOR AT 34. Simple habits. Better decisions. Stronger execution. 1. The Sunday Scan. 👇
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if you learn marketing engineering, you will never be unemployed again. you need two things for all of it: claude code and a github account. marketers who know how to use them well and build their own agents will make real money for their companies. 11 steps:
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Robert Burke retweeted
Some data we recently assembled on entrepreneurship/compute in Europe: eudata.vercel.app. We hope that one of the useful roles that Stripe can play is in collecting and publishing empirical data pertaining to entrepreneurship and industry in Europe. There's growing appetite to get Europe on a better footing, and cross-sectional comparisons can often shine light on where opportunities lie. If you're interested in this kind of thing, we publish more at stripeeconomics.substack.com.
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I can’t stress enough how little an idea matters compared to the agency of the people executing the idea. I have had the privilege of knowing and sometimes even working with some of the most successful people (by various metrics). The difference between mediocre and excellent work and outcomes is predominantly one of agency. In practice this means: they dont wait for things to happen to them they go out and make things happen for them. They don’t wait for someone else to do something, for someone to teach them, for someone to give them the path, etc. They just go out and find a way to do it. I think the single biggest superpower these people have is the realization/belief that the world around them is completely mutable. Most everything that happens is because a person made it happen. I used to tell people to look around the room you’re sitting in. Look at everything. Every noun. It almost all exists because a person willed it into existence. Nothing is stopping you from doing the same. I see people online all the time dismissing someone else’s success because “I had that idea first” or whatever. I mean… yeah? If so then the difference is… you. So a bit of a self own whenever I hear that. Number one tip: act with agency.
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30 features of an AI native company: 1) Function-by-function process blueprint of your entire business. 2) Everyone in org using a daily driver harness like Grok Bot, Claude Cowork, ChatGPT at Work. 3) Centralized intelligence layer that aggregates structured and unstructured data, documents, and business logic into a single source of truth that is queryable & agentic work can be done on top of. 4) Model routing via OpenRouter, Ramp, etc that optimizes cost-per-successful-task across the business. 5) Treat context as code, ensuring architecture documents and conventions remain updated while allowing for diligent upfront planning. 6) Willing to throw away everything that you've built every three months and reimagine all your workflows. 7) A “skills distribution system” is used to manage agent behavior and optimize for token efficiency by ensuring developers trigger consistent skills throughout their workflow. 8) Separate technical implementation from high-level specifications, enabling non-technical staff to contribute in a format that agents can utilize to build technical implementation plans. 9) A key software metric is “cost per accepted PR”, with a focus on driving these costs down through better token efficiency. 10) An automated, agent-native development system where fleets of AI coding agents handle planning, writing, testing, reviewing, and shipping code while humans define the intent and acceptance criteria. 11) Heavy planning with higher-effort models and executing with cheaper, faster models. 12) Agent harness that uses CLI tools to parse metadata within markdown files to traverse dependency relationships, allowing agents to be granular in their input token usage. 13) Finance org that runs processes continuously in accounting (record-keeping) to re-define/reset forecasts on a much, much tighter cadence. 14) Financial models embedded in the underlying OS across the org to help drive reasoning. 15) Citizen Developer SDLC where non-technical employees can take a solution from idea to production with governance, access, versioning, and software conventions built in. 16) Closed loop, self-improving non-engineering workflows that learn from previous runs based on external performance metrics or internal evals. 17) AI ROI framework that includes experimental phase, scaling phase, and optimizing phase with bets sitting in 3 buckets: infrastructure, innovation, and efficiency. 18) Paid marketing motion that uses agent swarms to deploy thousands of pieces of creative for testing, before increasing spend on human-generated ads. 19) AEO/SEO engine that audits, rewrites, and (ideally) generates SEO/AEO-optimized blogs on a weekly basis, and then measures if any of it worked. 20) Agentic cyber security solution that fights AI with AI. 21) Combo of RL gym and first-party data to fine-tune open source models on high-volume processes that need SOTA performance at reasonable cost. 22) Human touch and judgement gets reserved for the first and final mile of most processes. 23) Evals are core infrastructure of your business. Anytime new models come out you have an apparatus for testing cost & performance against core processes. 24) Everyone is a builder. Especially C-level execs. 25) Everything gets recorded because what you don’t capture can’t be turned into ai-enabled work. 26) Legal, HR, and IT work in lockstep with owners of AI agenda so that business’ ass is sufficiently covered without slowing down transformation. 27) Bias to disrupting yourself before being disrupted by others. 28) Guardrails before features. Agents inherit the permissions of whoever is asking, enforced in the data layer. 29) Earned autonomy. Feedback feeds the evals that gate each new version, and agents move up a ladder as they clear it: observe, suggest, act with approval, act alone. The endpoint is agents running whole workflows inside a defined boundary, with humans setting the standard instead of checking every answer. 30) Traceability as the training signal. Trace every output to its prompt, model, data, and approver, so human feedback attaches to something specific rather than a vague sense that something is off. What's missing?
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True
Facebook VP of Growth Alex Schultz: “Retention is the single-most important thing for growth” Alex walks through how to calculate a retention curve for your startup (graph the percentage of monthly active users on the y-axis versus the number of days from acquisition on the x-axis). As he explains: “If you end up with a retention curve that asymptotes to a line parallel to the x-axis, you have a viable business, and you have product/market fit for some subset of market.” If you do not have a retention curve that flattens out, you do not have product/market fit and none of the growth hacking or virality tactics that people love to talk about will work. “Focus on getting to product market/fit… If you don’t have a great product, there’s not point executing well on growing it, because it won’t grow. The #1 problem I’ve seen inside Facebook for new products and the #1 problem I’ve seen for the startups I’ve advised has been that they don’t actually have product/market fit when they think they do.” Source: @ycombinator (Oct 2014)
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Robert Burke retweeted
Social media and SEO just had a baby. Google can now show you which Instagram, TikTok, and YouTube posts appear in search, what people searched to find them, and how much traffic they drive. That means your social posts are becoming search results. And almost every search falls into one of four buckets. Informational: “How do I get more protein?” That’s a tutorial video. Navigational: “Netflix login” or “Chipotle locations.” They already know where they want to go, they’re using Google to get there. Commercial: “Best CRM for small businesses.” That person wants comparisons, rankings, and honest reviews. Transactional: “Price,” “discount,” “book,” or “near me.” They’re ready to take action, so give them one clear next step. Most content creators only make informational content because they don’t realize the other three categories exist. Here’s what I tell my clients: type your topic into AnswerThePublic. It shows you the questions and phrases people are already searching for. Then create videos across all four types of search intent, adapt them for Instagram, TikTok, and YouTube, and publish them across every relevant platform. Finally, use Google Search Console to track which topics rank, which searches drive traffic, and which videos deserve follow-ups. You’re not just posting more content. You’re covering the entire customer journey and using real data to decide what to create next. The feed rewards whoever posted last. Search rewards whoever answered best.
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Robert Burke retweeted
If a B2B founder hired me tomorrow to build their LinkedIn presence from zero, here's exactly what I'd do. They've never posted, have maybe 300 connections from accepting random requests over the years, and their entire marketing budget is going to conferences and content syndication. First thing I'm doing is blocking 90 minutes on their calendar. Not to write posts. To extract stories. Every founder has 15 to 20 stories they tell in sales calls, board meetings, or over drinks that would make incredible LinkedIn content. They just never think to write them down. My job in that first session is to pull those out and turn them into a content bank. I'm recording the conversation with their permission, transcribing it, and tagging every story by theme. Product decisions they agonized over, customer wins that surprised them, hiring mistakes they learned from, industry opinions they're afraid to say publicly. That transcript becomes the raw material for the next 60 days of content. Then I'm setting up a dead simple cadence. Three posts a week. Monday is a tactical post about the problem their product solves, written from the founder's perspective. Wednesday is a story. Something specific that happened, a decision they made, a bet that paid off or didn't. Friday is an opinion. Something they actually believe that their competitors would disagree with. Three posts. Three formats. I'm not adding carousels, newsletters, LinkedIn Lives, or anything else until this rhythm is locked in for at least six weeks. The posting itself takes the founder maybe 20 minutes a week. I write the drafts. They review them in a shared doc, make edits in their voice, and approve. Most founders who say they don't have time for LinkedIn actually mean they don't want to stare at a blank screen. When someone hands them a draft that sounds like them, the approval takes three minutes. Now here's where most founder LinkedIn programs fall apart. The team posts consistently, gets some likes, the CEO feels good about it, and nothing connects to pipeline. The piece most teams skip is the engagement strategy. The founder needs to spend 15 minutes a day commenting on posts from people in their ICP. Actual responses that reference something in the post and add a perspective. If the founder's product sells to VPs of Finance, I'm building a list of 30 to 40 VPs of Finance who are active on LinkedIn and the founder is commenting on their posts before they ever see a single piece of content from us. This does two things. It gets the founder's name in front of the exact people they want as customers. And it trains the LinkedIn algorithm to show the founder's posts to those people's networks. I'm also connecting the LinkedIn activity to the CRM from day one. Every new connection request that comes from a post gets tagged. Every DM conversation gets logged. Every demo that books where the prospect mentions LinkedIn gets flagged in the opportunity record. If you're not tracking this, you will never prove ROI and the program dies in quarter two when someone asks what all the posting actually did. The metrics I care about in the first 90 days are profile views per week, connection request volume from ICP titles, DM conversations started, and demos booked where the prospect engaged with content before booking. Follower count is vanity at this stage. A founder with 800 followers and 20 DM conversations with target buyers is outperforming a founder with 10,000 followers and zero pipeline. Every founder-led LinkedIn program I've seen die has died because the CEO posted for two weeks, didn't see results, and decided it wasn't working. My job is to set expectations upfront. Pipeline impact shows up around month two or three. The early signals are profile views and inbound connection requests from the right people. If those are climbing, the program is working even if no deals have closed yet. One more thing. I'm not letting the founder post from the company page. Ever. People follow people. The company page can reshare the founder's posts, but the original content lives on the personal profile. Company pages on LinkedIn get a fraction of the reach that personal profiles do and every B2B company I've worked with that tried to build a brand through their company page alone ended up with 200 followers and a content calendar nobody looked at. This whole setup costs almost nothing compared to what most B2B companies spend on paid acquisition. A founder posting three times a week with a 15 minute daily engagement habit and someone managing the drafts and tracking the pipeline impact. That's the program. Just a founder willing to show up consistently and someone making sure the effort connects to revenue.
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Robert Burke retweeted
Claude Code is INSANE for B2B outbound. I put all 40 skills our team uses into one plugin. This is the exact stack behind campaign angles benchmarked against 244,000 real outbound campaigns. Inside: - ICP definition down to real buying signals, not demographics - List building from ICP filters, no manual research - Cold email copy hitting 8.5%+ reply rates - LinkedIn outreach and cold calls running from the same brief - Reply handling and pipeline analysis, done before you finish your coffee Want it? Like + Comment "OUTREACH" and I'll send it over ASAP (Must be following)
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Robert Burke retweeted
GTM Engineering will be THE most important GTM role in 2027. There are 12 skills that define it: 1. Tech stack evaluations: spotting new GTM tools before competitors do 2. Workflow design: mapping every flow before you build it 3. TAM mapping: turning a whole market into a precise account list 4. Signal tracking: layering first-party and third-party signals to rank accounts 5. Data enrichment: finding the data points traditional databases miss 6. Automated outbound: run Instantly(.)ai for email and HeyReach for LinkedIn 7. Inbound orchestration: routing every form fill for enrichment and CRM sync 8. Claude Code: your company OS running from the terminal with MCPs 9. Ads audience building: feeding marketing clean lists to build ad audiences 10. CRM workflows: cleanup and enrichment so reps always have context 11. Awareness scoring: ranking accounts by their buying stage 12. Content engineering: turning call transcripts into content for marketing Master all 12 and you will be irreplaceable. PS We put together a full masterclass document on GTM engineering. Want it? Comment ENGINEER + follow me and I’ll DM it to you.
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Someone asked me today what's the most motivating thing I've ever read. It's this quote: "The definition of hell--on your last day on earth, the person you became met the person you could have become." The most profound regret is not about things you did but about the things you didn’t do—the missed opportunities, the untapped talents, the unlived dreams. It serves as a powerful reminder to live fully and intentionally and to be the version you could have been if you had not been held back by fear, doubt, shame or complacency.
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If you're in sales, this kind of stuff is the bare minimum now.
Agent-pilled sales teams are building custom landing pages + demo videos for every buyer in their outbound campaigns Response rates are in a different league This agent runs 24/7 in a loop: >finds prospects with real buying signals in @useapolloio >builds a custom page for each of them >embeds a custom demo video rendered with @HyperFrames_ Get this agent, Signal, on Hyperagent Marketplace: hyperagent.com/marketplace/a…
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I've overseen the GTM motions of 250+ B2B companies. These are my top 9 strategies for 2026, each rated by difficulty and time horizon: 1. AUTOMATED OUTBOUND • Difficulty: 3 stars. • Time horizon: Short. • Runs automatically by a GTM engineer • Without scaling SDR headcount. 2. PRODUCT-LED GROWTH • Difficulty: 5 stars. • Time horizon: Long. • Build user bases through free plans. • Then systematically upsell. 3. MANUAL OUTBOUND + COLD CALLING • Difficulty: 2 stars. • Time horizon: Mid. • Old-school sales that will always work. • But it requires headcount to scale. 4. ABM • Difficulty: 4 stars. • Time horizon: Long. • Full GTM resource deployment to a list of target accounts. 5. COMMUNITY + PARTNER LED • Difficulty: 4 stars. • Time horizon: Long. • Enabling external companies to sell for you through a community flywheel. 6. PAID MEDIA • Difficulty: 3 stars. • Time horizon: Short. • Guaranteed eyeballs through social media ad funnels. 7. SEO + AEO • Difficulty: 3 stars. • Time horizon: Long. • Capturing high-intent clicks through Google and LLM search queries. 8. SOCIAL CONTENT • Difficulty: 3 stars. • Time horizon: Long. • Building a personal brand through consistent content publishing. 9. EVENTS • Difficulty: 3 stars. • Time horizon: Mid. • Face-to-face sales and brand-building at live events. PS Want the full high-res PDF of the 9 GTM motions? Comment "motions" and I'll send it to you.
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whoa this blew up we're working hard to keep our system up and running with no issue - thanks y'all!
introducing Helena, the world's first self-improving AI marketer. $10M in sales driven for 20,000 businesses already. everyone's shipping an AI that just makes more slop: so we went further. Helena grades her own work, and rebuilds the ones that miss - including the ones she built. what she does: ➤ runs loops to optimize Meta/Google ads & social ➤ drafts SEO content that ranks, straight to WordPress/Webflow/Framer ➤ optimizes emails in Klaviyo/Mailchimp/Brevo ➤ sends you a daily brief: what worked, what she's changing real numbers: ➤ grew organic traffic 35%+ for hundreds of brands ➤ 2x-ed a DTC brand's sales in 5 weeks ➤ scaled a dead ad account from $0 to $10k/mo ➤ drove $40k email revenue in 6 weeks 100+ skills. 3,000+ integrations. purpose-built by marketers who actually scaled hundreds of businesses. just your url. all done in less than 3 minutes. try it now 👇 hirehelena.com
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Robert Burke retweeted
Someone asked me recently why I’ve become interested in aesthetics after having spent most of my life more interested in STEM-adjacent topics. I hadn’t really considered the question consciously before, but I’m certainly thinking about aesthetics more than I used to. I think it’s a confluence of things: • Many things today are ugly and far uglier than they used to be or need to be. Once you see this, it’s kinda hard to stop perceiving it. (Early twentieth century phone boxes versus modern phone boxes; old water fountains versus new water fountains; etc.) As someone with a naively meliorist assumption that most things should be getting better rather than worse, it’s all a bit perplexing: why did we stop doing things nicely? Is it a choice? Was there a malevolent spell cast upon us? This vein led me to think more about modernism and why much of art became more intentionally "challenging", grotesque, opposed to prettiness, rebarbative, dissonant, etc. Can or should anything be done about this? Is this just how things ought to be? • Relatedly, much of modernism involved a kind of explicit repudiation of cultural continuity and represented a schism with prior practices. This is maybe most evident in American architecture, where the International Style exhibition in 1932 initiated the displacement of a rich tapestry of prior styles. This cultural break seems important and interesting to me, and I suspect that the rejection had important consequences outside of the aesthetic domain. Samuel Hughes has been exploring this question in his recent writing at @WorksInProgMag; @RuxandraTeslo is also pulling on this thread. Elaine Scarry wrote about how beauty inspires creation. If so, the inverse may also be true: ugliness inhibits it. • It’s clearly the case that changes in the aesthetic domain can at least inspire progress in other places. Petrarch helped set some of the preconditions for the Renaissance which in turn fostered the scientific revolution and Enlightenment. Things like World Fairs (the 1851 Fair at the Crystal Palace recorded 6 million admissions when the population was 21 million) reflect the popular interdependency that used to exist between aesthetics and material development. • @tedgioia and others have written about stuck culture and how so many domains seem to have ceased to straightforwardly advance in the way that they did up until the nineties or thereabouts. This is obviously peculiar and interesting. What changed, and what does it mean? Is it about the internet and fragmentation? Is it about a loss of supply? Is it just about having reached the zenith of various mediums? • I’m generally interested in markets and the dynamics of creation. In aesthetics broadly, I find the reflexivity between supply- and demand-side factors to be very thought-provoking. There’s a natural desire to view satisfaction of individual preferences as the yardstick to measure market success, but things get interesting and even a bit unsettling when we start to think about how the supply might start to shape the demand. I often think about this in the context of food. Why is food so much worse in Germany than many of its neighbors? Germany certainly doesn’t have less material ability to produce good food; indeed, Germany is richer than the countries around it. There’s probably something about German food supply chains that is impoverished relative to France and Italy, but the Germans themselves don’t seem too upset about it. It just seems that the Germans are stuck in an objectively worse market equilibrium than their neighbors: the food is bad and they’ve gotten used to it. The obvious question then is where else these kinds of reflexive patterns apply, and where else we’re stuck in some objectively inferior equilibrium, even if preferences are in some superficial sense being sated. • While this is an extremely banal and obvious point, I hadn’t until recently thought much about or internalized how much one can study reasonably objective things ("the status of women in society", say) through artwork. (Thanks to @_alice_evans for opening my eyes here.) In this vein, I’m pretty excited about the possibilities over the coming years in computational art analysis. I want something that’s conceptually similar to Google Ngram timelines but for the visual arts. • We've always tried to do things well at Stripe. I've come to see that attempting to do them beautifully is often a helpful way to break out of standard practices and to do something with greater novelty and in a way that might have other benefits besides. (Also, excellent people want to do great work because it is intrinsically satisfying. Explicitly allowing aesthetic considerations to carry weight avoids having to justify every assessment with some kind of torturous empiricism.) • In his Nobel Lecture, Solzhenitsyn said that, among the Platonic virtues of goodness, truth, and beauty, that beauty is special, for it possesses a unique kind of irrefutability. He notes that arguments, writing, and philosophical systems can all be predicated on misapprehensions, but that “a true work of art carries its verification within itself.” He proceeds to observe that when goodness and truth are threatened, the “ever surprising shoots of beauty will still force their way through.” There is a lot of specious and motivated reasoning in the world today and plenty of questionable value systems. I don’t think that beauty directly reflects any definitive trait, but I’m intrigued by the idea that it can be a marker of deeper metaphysical coherence.
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We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all. I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand. Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.
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