There’s a version of this post that’s polished and abstract — “here’s how AI agents can transform your go-to-market strategy.” That’s not this post.
This post is about what actually happens when we open Spacebear on a Monday morning. The specific agents that ran overnight. The keyword Quinn flagged at 2am. The Reddit thread Scott surfaced that we never would have found. The article Harper recommended based on a dip in our Search Console data that we hadn’t noticed yet.
We use Spacebear to market Spacebear. This is what that looks like.
The brief that keeps everything coherent
Before any channel agent does anything, the Chief reads the brief. The brief is a living document — product description, ICP, tone, competitors, goals — that the Chief maintains and injects into every agent’s context. It’s the shared brain.
When we first set Spacebear up for ourselves, the Chief asked us about our product and audience through a conversation, not a form. We described Spacebear as a GTM engine for B2B SaaS founders who are too early for a marketing team but too busy to do marketing properly. The Chief took that, researched our site and competitors, and wrote a brief that all the other agents now reference.
The practical effect: when Quinn drafts a keyword strategy and when Scott drafts a Reddit reply and when Avery suggests a LinkedIn angle, they’re all working from the same description of who we are and who we’re talking to. There’s no drift. No one-off messaging that contradicts the homepage.
The Chief also posts a daily report — a short summary of what’s happening across all channels, what’s performing, and what recommendations are pending. It takes about two minutes to read. It’s the only marketing dashboard we need.
Quinn: the Google Ads space
We have two campaigns: branded search (people looking for “Spacebear”) and non-branded (people searching for things like “AI marketing agent” or “autonomous GTM tool”). Quinn monitors both.
Quinn runs keyword analysis every hour. When she spots a search term that’s converting or a keyword that’s bleeding spend, she creates a recommendation. We see it in the dashboard, review the data she’s pulled, and either approve or dismiss. The actual change — pausing a keyword, adding a negative, adjusting a bid — only happens after we click confirm.
A few things Quinn has caught that we would have missed:
Keywords burning money with no conversions. Some broad match terms were accumulating spend with zero signups — high CPC, wrong intent. Quinn flagged them with recommendations to pause and shift budget toward terms with clearer buying intent. We confirmed. Done in under a minute.
Search terms we hadn’t thought to target. Quinn pulled the search terms report and found phrases we were already showing up for that were converting — phrases we hadn’t deliberately targeted. She recommended adding them as exact match keywords. We added them.
A campaign that needed a bid cap. One of our ad groups was auto-adjusting bids too aggressively and running up costs. Quinn recommended a hard CPC cap. We set it. Spend normalized.
None of this required us to open Google Ads. Quinn does the daily work. We make the final calls.
Scott: the Reddit space
Reddit is where our audience lives, complains, and asks for recommendations. It’s also a full-time job to monitor properly — which is exactly why we have Scott.
Scott tracks a handful of subreddits where our audience hangs out — communities for SaaS founders, startup operators, and marketers. Every day, he crawls those subreddits, reads threads, scores them for relevance to Spacebear, and surfaces the ones worth responding to.
The discovery flow works like this: Scott identifies a thread, drafts a response, and creates a recommendation. We see the thread and the draft. We can post it as-is, edit it, or dismiss. We never post anything from a Reddit account we own without reviewing it first.
A few threads Scott has surfaced:
Someone asking whether AI can actually replace parts of a marketing workflow — a genuine question, not a troll thread. Scott’s draft led with an honest account of what Spacebear does for us specifically — not a pitch, a case study. We approved it lightly edited. That thread still shows up in Google for long-tail queries.
A “how do you handle marketing as a solo founder?” thread. Scott drafted a response that described our situation — too early for a team, too much to do manually — and mentioned Spacebear as what we use. Honest and specific.
A thread that went live at midnight and we genuinely would have never seen. Scott caught it during his overnight sweep. By the time we woke up and approved the draft, it was hours old — but still on the front page of the subreddit. We posted. Got upvotes. Got traffic.
The overnight problem is real. Reddit threads have a half-life of hours. Scott runs continuously. We don’t.
Harper: the content space
Harper is our content strategist. She reads our Search Console data, researches what’s trending, identifies gaps, and recommends articles. When we approve one, she drafts it.
We publish articles for two reasons: to rank for queries our audience is already searching, and to have something worth reading when someone clicks through from Reddit or LinkedIn. Harper is the one who connects those two things.
Every day, Harper generates 2–3 article recommendations. Each one comes with a rationale: why this topic, what keywords it targets, what angle she’d take. We review them and either queue them or dismiss.
Some examples of what Harper has recommended:
A piece on Google AI Overviews and CTR. Harper noticed from our Search Console data that several of our existing articles had strong impressions but declining CTR — a pattern consistent with AI overview displacement. She recommended an article explaining the phenomenon. We approved it. The resulting piece earns consistent search traffic and has picked up backlinks from other marketing blogs covering the same trend.
A comparison piece targeting competitor keywords. Harper’s web research surfaced topics where competitors had content and we didn’t. She recommended a piece drawing a sharp contrast between AI assistants (reactive, task-by-task) and AI agents (autonomous, proactive). We published it.
When we approve an article for drafting, Harper writes a full piece — typically 1,500–2,500 words, in our voice, with citations and structure. We edit for accuracy and tone, then publish. The writing itself takes us maybe 20 minutes of review, not 3 hours of original work.
Sierra: the SEO and GEO space
Sierra handles the technical layer that Harper doesn’t touch. She crawls our site programmatically — up to 50 pages per run — checks around 30 signals per page, and generates a health score. She’s been running since we launched and the score has improved meaningfully over that time.
Issues Sierra has caught that we fixed:
A canonical tag pointing to an HTTP URL on our pricing page. Low drama to fix, but genuinely harmful for crawlers indexing the wrong version.
Missing meta descriptions on several blog posts. Harper’s older articles were missing them. Sierra flagged them; we added them.
Image alt text gaps across the marketing site. Not a major issue but a consistent pattern Sierra surfaced and we batch-fixed.
Beyond technical SEO, Sierra also checks for AI search presence. This has become more valuable than we expected. She searches for our product category in web search and tracks whether Spacebear appears in AI-generated answers (Google AI Overviews, Perplexity, ChatGPT). We now appear in Perplexity results for several queries in our category — something Sierra spotted before we ever thought to check manually.
Avery and Nix: LinkedIn and Hacker News
LinkedIn is a channel where consistent presence compounds. Avery monitors relevant conversations — product people discussing AI, founders talking about GTM, marketers debating automation — and surfaces the ones worth engaging with.
Avery doesn’t auto-post. She drafts comments and posts for our review, which we then post manually from our own accounts. The value is in the monitoring and the drafting: we’d occasionally check LinkedIn for interesting threads; now we’re consistently in the right conversations. Avery also tracks how competitor posts are performing and flags when something is getting unusual engagement — which is often a signal about what our audience cares about right now.
Nix monitors Hacker News. HN is a niche channel for us, but a high-signal one — the people who discuss AI tools on HN are often early adopters and vocal advocates. Nix tracks Show HN posts in adjacent spaces, Ask HN threads about marketing tools, and any mention of autonomous agents.
The most useful thing Nix has done: surfaced an Ask HN thread about what tools people are actually using for B2B marketing before it got too old. We added a comment about our own experience with Spacebear. It’s a thread that still receives occasional traffic from Google.
What dogfooding actually teaches you
Running Spacebear on ourselves has been the most direct source of product feedback we have.
We see exactly what the agents surface and how often we approve versus dismiss. Scott’s Reddit recommendation acceptance rate tells us something real about how well his relevance scoring is working. When Harper recommends a topic we’d never write about, it’s a signal that her understanding of our audience needs refinement — and we can fix that by updating the brief.
We’ve also learned what the product is actually good at: consistent presence. We’d always intended to be active on Reddit, write regularly, keep our ads optimized. The intention was there. The execution was not — because there’s always something more urgent. Spacebear doesn’t get distracted. The agents run whether we’re in the zone or in the weeds.
The daily Chief report reflects this. Three months in, we have a clearer picture of what’s actually working across channels — and what’s not — than we did when we were trying to manage it manually. That visibility alone is worth it.
Spacebear gives every founder a full GTM team. Each channel gets its own Spacebear — monitoring, researching, drafting, and surfacing the work that matters, while you stay in control of every decision that counts.