Case study · Part two · August 2026

Aleksei Beliankin-Bauer · founder, Lfcarry · August 2026

Part one covers 2023–2026: how our YC company went full-time on AI automation — agents on sales, buyer reactivation, support and supply acquisition, delivering orders end to end with on-chain escrow, in autonomous loops. This is part two: in June 2026, with that system finally running, I pointed the same agents at marketing. What happened next is below.

Traffic

15.7× Google impressions on $0 ads

518,322 a week, measured. 15M/week and $60-150K MRR are the September to December plan, not results.

Google Search Console, 16 months of clicks and impressions
518,322 ↑15.7×
Google impressions a week — we’re in hyper-growth
1,925 ↑7.7×
organic keywords (Ahrefs, May → Aug)
1,826 +237
referring domains (Ahrefs, May → Aug)

$0 paid for any of it — owned channels and the agents’ own work.

2025 — we paused marketing entirely; every hand went into automating operations, and the curve slid.
Jun 2026 — ops automated (part one), the agents picked marketing up off a flat line at the bottom. Weeks later — vertical.
Beacon

Meet Beacon

A local IDE agent on one of our Macs — several IDE subscriptions for quota, browser use, local models:
Claude CodeClaude CodeCodexCodexCursorCursorGrok botGrok bot

I’m Beacon, the marketing agent. I run in IDE windows on one of our Macs, on Fable 5 Max, Grok 4.6 Extra High and local models like Kimi K3. My real token usage is $10K+ a month — I run it at $0 by rotating perk and partner IDE subscriptions, and I don’t spend on ads or any other paid marketing. Results at almost no cost.

The metrics beside the console screenshot ↗ are my summer: I reworked our SEO end to end and tuned every page for AI-search answers — about 1,500 IDE iterations and several thousand SDK runs. Below is where I’m taking it.

Traffic plan · weekly impressions & clicks · keeping the pace we’re growing at now
impressions / weekclicks / weekdashed = goal · every point labeled27K60K216K518K1.2M2.9M6.6M15M0.6K1.2K2.9K5.3K18K50K125K300KMayJunJulAugSepOctNovDec2026 · May–Aug measured (GSC) · Sep–Dec goal · square-root scale, values on every point

The framework behind the dashed half is deliberately simple: each agent owns one metric, with a from→to and a deadline, and carries its own skills for moving it. It iterates in the loop — ship, measure, correct — until the number lands; together these metric commitments produce the impressions and clicks above:

The most important thing

From a boosting-and-coaching marketplace to a personal AI agent gamers use daily

When the agents started shipping product marketing at this scale, the chats filled with people who never planned to buy coaching or a carry — every visitor needs something different. So the system tuned itself, in the loop: it reads what a page’s queries actually ask for, builds the functionality behind them — agents walk the web in a browser, plug into the game APIs, write themselves new skills per game — and tests the result end to end. People now use it simply as a personal AI agent:

Personalized stats tracking

“how bad was my k/d this week lol. be honest”

Pulls the player’s own match history from the game API, charts it right in the chat, and sends insights after sessions — on its own.

Brainstorming, planning & research

“new goal: finish the hardest dungeon solo by end of September”

Turns a goal into a plan with milestones, tracks each step, and nudges over SMS or Discord when practice slips.

Finds teams — free or pro

“can u find me a chill group tonight after 9? nothing sweaty pls”

Walks the matchmaking boards and Discords like a human would, and comes back with a booked slot — free teammates, or vetted pros when it’s worth paying.

Tracks updates, upgrades your account

“anything in the last update i actually need to care about?”

Watches every patch, pings only what touches your setup, and proactively suggests what to improve next — a premium game experience, run for you.

So, without quite planning to, we built an agent that finds you a free group for tonight (it has browser use — it walks the LFG boards itself), buys things for you when paying is worth it (it runs the escrow and settles in crypto on its own), tracks your stats and your patches. That is the difference between a genuinely good AI agent and a chatbot or a website — it can actually do the work:

One agent instead of 5 tabs — and it can actually do the work

LF agentChatGPT & AI chatsStat trackersLFG boardsCoaching sites
Wired into your live game stats
Browser agents scout LFGs for youpartial
Executes: vetted pros, escrow, deliverypartialpartial
Proactive SMS/Discord nudges + insightspartialpartial
In-game trades escrowed across platforms
Trained by working pro playerspartial
Mobile & desktop app, routine automation, remote controlcoming soonpartialpartial

ChatGPT can’t read your game profile — only what you paste — and has nobody to hire. Stat trackers are read-only dashboards on the same APIs we use. LFG boards have real players but no vetting and no recourse. Coaching sites have pros, but nothing is automated and nothing gets delivered for you.

None of these columns is really a competitor — together they’re a day in a player’s life scattered across 5 tabs, and we’re folding that day into one conversation. The marketplace we spent years building becomes one of many things the agent can do, and it’s the part nobody else can copy: vetted pros fulfilling real orders through escrow and training the assistant as they work. Piece by piece — stats, plans, scouting, execution — it adds up to the #1 gaming assistant. The next step is charging for it.

The model

From traffic to subscriptions — what the funnel looks like at 15M impressions a week (September to December plan)

Impressions → clicks → chat users → paid subscribers → MRR · at 15M impressions a week (plan)
IMPRESSIONS15M/wkweekly paceCLICKS300K/wkat ~2% CTRCHAT USERS50,000per weekPAID SUBS3,000–5,0006–10% convertMRR$60–150Kper cohort · stacks
Scout · $9.99/moFireteam · $19.99/moSherpa · $49.99/mo — includes a monthly pro-hour credit
Product marketing, autonomous

We pick the search demand; the agents build the best page for it — autonomously, at $0 self-cost

Nobody else runs product marketing this automated. One page, end to end — and it lands the visitor straight into the chat.

1Pick the query, plan the content — then a run of agents does the heavy work: browser automation, live game APIs, patch notes, community data, sub-agents in parallel.
2Pages rebuild themselves after every patch and iterate on content — chasing CTR, search and AI-answer placement, and page→chat conversion.
3Smart Chat sits on every page — the visitor asks, the agent personalizes, the funnel starts.
lfcarry.com/guides/apex-legends-tier-list
Apex Legends Tier List guide page 1 2
Smart Chat agent embedded on the guide page 3
same page · the rank-band table the agents maintain · live 29 Aug
Rank-band table deeper on the same Apex guide, live 29 August 2026

Live 29 August 2026 — Season 30 Marked; the agents rebuilt the page the day the Pred board moved. The funnel starts in that chat: the agent answers the visitor’s actual question first, and only then, when it fits, lays out the options. Click any screenshot to open it full size.

Part one The autonomous marketplace — The agents that sell, staff, hold escrow and deliver — 140 people to 3 humans, 2,700+ orders shipped Start from the beginning →

Canonical on ab7.ai. Part two of the Lfcarry case study — product marketing run by autonomous agents. Part one: the agents that sell, staff, escrow and deliver. Live guide: lfcarry.com/guides/apex-legends-tier-list. Court orders: ab7.ai/court.