# Our Agents Ran Our Launch-Week Analytics > Source: > Published: 2026-08-19 00:00:00+00:00 # Our Agents Ran Our Launch-Week Analytics Ten Reddit threads, 501 comments, a Product Hunt page, GitHub traffic and PostHog funnels — read, cross-referenced, and reported by a hive of agents. The workflow, and how to point it at your own launch. After launch week we had ten Reddit threads, 516 comments, a Product Hunt page, and analytics dashboards — far more than any human was going to read honestly. So we didn't. **A hive of agents read all of it**: one agent per channel, structured briefs in, markdown + JSON reports out, one synthesis at the end. Every launch decision we've made since traces to those reports. Here's the workflow. There’s a specific kind of lying founders do after a launch: they remember the five most emotional comments and call it “what the community said.” We had 516 comments across ten subreddits. Nobody’s memory survives that honestly. But we make a tool whose whole job is [coordinating agents on real work](/blog/run-an-office-of-ai-agents/). Launch analytics turned out to be the best dogfood we’ve ever had. ## The floor plan [#](#the-floor-plan) Four agents, one channel each, spawned with a written brief: **Reddit agent**— the big one. Ten launch threads saved as raw JSON, 501 comments including every nested reply. Brief: account for*every*comment — bucket objections, praise, feature asks, and pricing signals, with quotes and usernames preserved.**Product Hunt agent**— the launch page: all 27 comments, the review, and the page’s own embedded data, read straight from the source rather than eyeballing rendered numbers.**GitHub agent**— stars, traffic, referrers, clones: which channel actually moved the repo.** Analytics agent**— PostHog funnels: installs, first runs, and where new users stalled. Each agent wrote two artifacts into a shared research folder: a **markdown brief** a human actually wants to read, and a **JSON file** with the counted, bucketed data so later questions don’t require re-reading anything. Then the orchestrator synthesized the four into one picture. ## Why the fan-out matters [#](#why-the-fan-out-matters) The naive version of this is pasting comments into one chat session until it fills up. The problem isn’t just context size — it’s that a model skimming its 400th comment gets exactly as lazy as a human does. One agent per channel keeps each report grounded in a full, careful read, and the [orchestrator](/blog/how-the-god-orchestrator-works/) works from four distilled reports instead of raw sludge. Fan out, then synthesize. It’s the same [pattern](/blog/multi-agent-orchestration-patterns/) that works for code. The other thing a hive gets you is **iteration without re-reading**. Days later we came back with sharper questions — “split willingness-to-pay by supporter motive versus buyer motive,” “which commenters were blocked from even running it?” — and dispatched them to the same agent, which still had [its memory](/blog/how-agents-remember-semantic-memory/) of the corpus. Each pass appended to the same reports. The research got *thicker* instead of starting over. ## What fell out of it [#](#what-fell-out-of-it) Findings we would have missed by skimming, all of which changed real decisions: **46% of all engagement came from one subreddit.** r/ClaudeCode delivered 1,017 of 2,233 combined upvotes. Two other communities flatlined. That’s next launch’s channel budget, decided.**Product Hunt sent 195 upvotes and ~25 visitors.** Credibility channel, not traffic channel. We’d have guessed wrong.**The two most serious evaluators asked for the same missing feature**— a visible “this decision needs your eyes” flag — in different words on different platforms. Only cross-channel synthesis caught that they were the same request.**Every blocked-user story on two channels traced to the same bug class**(the non-Claude-Code path on Windows), which moved it to the top of[0.4.4](/blog/launching-munder-difflin-v0-4-4/). The Reddit and Product Hunt halves of this analysis became [their](/blog/what-reddit-told-us-about-munder-difflin/) [own](/blog/number-five-on-product-hunt/) posts — both written *from the agents’ reports*, which is why they have real numbers in them instead of vibes. ## Run it on your launch [#](#run-it-on-your-launch) The recipe, portable to any hive setup: **Capture raw sources locally first.** Reddit threads have JSON endpoints; save them to disk so agents parse structure instead of scraping rendered pages.**One agent per channel, written briefs.** The brief that worked:*account for every comment; bucket, count, and quote; write both a human brief and a JSON dataset; flag what you couldn’t verify.*That last clause matters — our Reddit agent correctly flagged that view counts are null in public JSON rather than inventing them.**A shared research folder** all agents write into, so reports reference each other.**One synthesis pass** at the end — and keep the agents around, because your best questions arrive three days later. An evening of agent work, and launch week stops being a feeling and becomes a dataset. The [overnight version](/blog/claude-code-automation-while-you-sleep/) works too — we know, because half of this ran while we slept off the launch. ## FAQ What did the agents actually analyze? Four channels in parallel: ten Reddit launch threads (501 comments including every nested reply), the full Product Hunt page (27 comments plus the page's own data), GitHub traffic, and PostHog funnels. Each agent produced a structured report — a readable markdown brief plus a JSON file — and the orchestrator synthesized them into one picture. Why use multiple agents instead of one long session? Each channel is a full context window of raw material on its own. One agent per channel means each report is written by something that actually read every comment, not a skim. The orchestrator then works from the four distilled reports — which is exactly the fan-out-then-synthesize pattern hives are good at. Can I run this on my own launch? Yes — the recipe is at the end of the post. You need the raw threads saved locally (Reddit's JSON endpoints work), one agent per channel with a clear brief, a shared folder for reports, and one synthesis pass at the end. A weekend launch produces an evening of agent work.