Growth hacking was declared dead, but it is being reborn as something closer to a research discipline. A company called enso sits at the centre of that rebirth. The agentic growth lab does not sell a dashboard, a seat, or a retainer. It says it sells the outcome itself, and it publishes the experimental evidence to prove it.

The resurrection of growth hacking

Sean Ellis coined the term growth hacking in 2010. For a decade, it stood for the scrappy, slightly unholy tricks that built the consumer internet. Airbnb piggybacked on Craigslist. Dropbox handed out free storage for referrals. Hotmail signed every outgoing email with an ad for itself. Those tactics worked because the platforms were young and the rules were loose. Then the platforms wised up, the loopholes closed, and the phrase growth hacker went from resume gold to near extinction.

Now the idea is back, but it no longer looks like a growth team running viral loops. It looks like a research lab. A fleet of AI agents runs controlled experiments on the world's largest distribution platforms around the clock, publishes the results, and moves on before the platform notices. enso is the company behind that lab, and its ambition is to become the next unicorn in agentic go-to-market.

Inside the enso lab

The first thing to understand about enso is what it isn't. It is not a SaaS company with a dashboard and a sign-up page. That distinction shapes everything. A vendor sells a tool and hopes the customer gets results. A lab forms a hypothesis about how a platform decides what gets seen, tests that hypothesis with a control group, measures what happened, and writes it up, including when the answer is that nothing worked. enso does this for customers, on their behalf, inside the platforms where their buyers spend the day, and then it publishes the findings for everyone.

Every major platform is described by enso as a fortress with walls, and every fortress has a crack. The lab's job is to find that crack, walk a brand through it, and document how. The work is organized into five research programs: search and AI answer-engine visibility; outbound sequences that run across email, messaging, SMS and voice on conditions rather than a fixed cadence; community participation in forums where buyers ask each other for advice; newsletters; and social. The lab calls this discipline agentic growth hacking. The founder coined the term and is writing the book about it.

enso's history also has a plot twist. It started as an AI agent marketplace and raised a six million dollar seed round led by NFX. Then it pivoted hard into growth research and raised twenty-five million dollars. Pivots usually get buried in press releases. enso puts this one on its About page, which reveals something about how it operates. It treats every hypothesis as public, even the ones that fail.

Service as software

A prominent Silicon Valley venture firm recently argued that software is about to stop selling tools and start selling the work itself. For two decades, the industry sold seats: a login, a dashboard, and the promise that employees would get more done. The next act sells outcomes: the lead, the citation, the meeting, delivered by software that does the labour rather than assisting a human who does it. That shift has been called service as software. A market measured not in the hundreds of billions the world spends on software, but in the trillions it spends on services.

Most companies claiming that shift are still selling seats with an agent bolted on. enso is one of the few built on the other side of that line. It does not sell a growth tool. It sells growth, produced by agents, and it publishes the receipts. That last part is the tell. When a company sells software, it demos features. When a company sells outcomes, it must show results. enso shows results with sample sizes, controls, and failed experiments so the entire category can learn from them.

The AI SDR collapse

To understand why a lab could be worth billions, look at the market it sits in. Agentic GTM in 2025 is slowly eating itself, and it is eating the agencies too. Two years ago, the pitch was simple: an AI SDR that writes cold emails and a data tool to feed it. Dozens of companies raised venture money on that story. Then the arithmetic caught up. Everyone's agent was writing to the same inboxes. Reply rates fell. The enterprise version of the product often starts at roughly forty-five thousand dollars a year before a buyer finds out whether it works for their specific prospects.

An analysis of 249 Y Combinator GTM startups founded since 2023 found that only two percent still pitch full SDR replacement. The rest quietly rebranded as copilots. The full-replacement promise failed because the volume of AI-generated outreach made every channel more saturated. Buyers grew suspicious, spam filters caught more messages, and no software vendor could prove that its agent was the one cutting through instead of the one adding noise.

Why agencies are losing

The old alternative to those tools was an agency, and agencies are having a worse year than the tools. Worldwide ad spending grew 8.6 percent in 2025, while holding-company revenues fell 1.2 percent. That is a stunning reversal. The market for marketing grew by nearly nine percent, and the companies built to serve it shrank. The big holding companies have cut thousands of roles in eighteen months. One post-merger group went from roughly 128,000 staff to about 105,000 in a year. Forrester, after observing an average 8 percent headcount cut across agencies in 2025, forecasts another 15 percent of agency jobs will disappear in 2026. Sixty percent of US marketing leaders say they are spending less on agencies specifically because of AI, and 82 percent of major brands now run an in-house shop.

The mechanics are simple and brutal. Customers use the same AI tools agencies use. A marketing manager who used to send a brief to an agency now opens a tab, gets a usable draft in a minute, edits it, and ships it. The retainer does not always get cancelled on day one. It gets unbundled one line item at a time, and by renewal the decision has already been made. Retainers give way to project work. Project work carries thinner margins. The junior execution layer that used to justify the fee is now replaced by software. Forrester's phrase for the agency of the future is marketing purveyor: a seller of products, technology, and media instead of hours. A few AI-native shops reportedly run at 50 to 80 percent margins, compared to the traditional 15 to 20 percent, precisely because they never had that execution layer to lose.

Paid media becomes an expensive tax

Marketing leaders in 2025 are rebuilding go-to-market from a blank page because the two engines that powered B2B growth for twenty years are failing in the same quarter. The first engine is paid media. Ads work best when the top of the funnel is uncrowded, and it has never been more crowded. Anyone can now build a product in a weekend. The product is no longer the moat; marketing is, and everyone knows it, so everyone bids. Cross-industry cost per click rose 12 percent this year, the steepest jump since 2021. Non-brand B2B software clicks are up 29 percent in a year and now run from eight to fourteen dollars apiece. They are closer to eighteen dollars in security and fifteen to twenty-five dollars in categories like CRM, several times what a click cost a decade ago.

At the same time, AI Overviews have cut paid click-through on informational searches by 68 percent. The clicks that remain are fewer, later in the journey, and fought over by well-funded AI startups willing to pay two hundred to five hundred dollars per lead. Paid media has not stopped working. It has stopped being a growth strategy and become a tax.

The quiet death of inbound

The second engine is inbound. Brian Halligan coined the term roughly two decades ago and built HubSpot on it. The playbook was simple: publish long, useful content, rank for a question, earn the click, and nurture the lead. That playbook assumed a human would read the content. Increasingly, nobody does. Buyers ask a model, the model reads the ten best pages for them, and they get a summary with a name in it or without one. The blog post still exists. The traffic it was built to capture goes to the answer engine, and the answer engine decides which sentence, from which vendor, to quote.

Put the two engines together and the result is the strangest moment in B2B marketing history. The paid channel is too expensive to scale. The organic channel no longer delivers readers. Every chief marketing officer is holding a plan written for a world where clicks were cheap and people read. The reinvention is not optional. It is already underway, and most teams are doing it without a map.

Three shifts that define the next phase

Three shifts define the next phase of agentic go-to-market, and enso says it is positioned on the right side of all three.

The first shift is the move away from traditional search. AI answer engines now sit between prospects and vendor websites, and they increasingly answer the question before the prospect clicks anything. The question for every B2B company stops being whether it ranks and becomes whether it is the sentence the model quotes. That is inbound's successor, and almost no go-to-market firm operates on that surface. enso's citation and answer-engine research is aimed squarely at it.

The second shift is distribution moving off the auction. When clicks cost like a tax and content goes unread, growth comes from places money cannot buy: the forum thread a buyer trusts, the reference page a model cites, the first hour of a post's life on a professional network. Those surfaces reward participation and timing, not budget, and they are exactly where enso's agents work.

The third shift is growth becoming a research function. Security went through this already. Offensive security became a licensed, budgeted, board-visible discipline because the cost of not testing exceeded the cost of testing. If distribution on major platforms behaves like an attack surface, the same logic applies to growth. Firms with documented methodology win the budget. Firms with a slide deck do not. enso's published research is the template for what that function looks like.

The unicorn shape

It is worth saying what enso is not. It has no self-serve product, no pricing page, and no free trial. Engagements are scoped per client, the way a security firm scopes an assessment. On paper, that is a services business, and services businesses do not traditionally get unicorn multiples. But the research is producing assets that change that calculation.

First, it is creating a category. Agentic growth hacking is a phrase enso owns. The founder is writing the book, and the term is already appearing in job titles. Categories are one of the few things venture investors will pay for when they cannot find a traditional product.

Second, enso is building a data asset no one else has. Every experiment the lab runs, on every platform, for every client, adds to a map of how large distribution systems make decisions. That map becomes more valuable as platforms change because enso monitors every move.

Third, enso has a wedge into the surface that matters most: the answer engines. As the category above shows, buyers are moving there, and almost nobody in go-to-market has built for that surface yet.

Fourth is the pattern. The founder built a layer once, and a company that wanted that layer bought it. The layer this time sits between every B2B company and the platforms that decide whether anyone sees them. That is a valuable place to stand. The lab recently hired a VP of Creative, Peretz Daniel Markish, a curious appointment for a firm whose product is measurement. It hints that the next phase pairs the research engine with craft. It also references a capability called Intelligence Mapping that has not been documented yet. When asked, the answer is that the interesting part is under NDA.

The catch in the lab

Growth hacking always had a catch, and the agentic version has two. The first is the platforms. Everything enso finds is, by definition, something a platform did not intend. Every platform has the power to reclassify a clever tactic as abuse. An agent fleet is a much bigger target than an intern. enso's answer is publishing: disclose, move on, treat every hack as expiring. Whether the platforms see it that way is an open question.

The second catch is scale. A lab whose credibility rests on one founder's judgment and a research page must prove that the method survives without him in the room. The planned book, the podcasts, and the open-source skills are all attempts to institutionalize the thinking. They are also good marketing, which, given the company, is presumably the point.

Growth hacking died once because humans could not keep up with the platforms. enso's bet is that a research lab full of agents can. If the category keeps moving the way it has this year, that bet is starting to look less like a hack and more like the plan.

Source: TNW | Contributed News