We Ran an AI Hackathon for Our Content material Crew. Right here’s What We Constructed with Agent A

Two of us independently constructed variations of the identical factor.

Mateusz’s Scrapbook helps you to paste any URL or block of textual content, and the AI reads it and saves a structured observe with abstract, key bullets, claims-with-sources, and three article concepts impressed by it.

Louise’s SavedIn is a Chrome extension that scrapes Louise’s LinkedIn “Saved” checklist and dumps full posts (writer, headline, physique, URL) right into a dashboard, plus a Media tab for YouTube transcripts and a URL inbox for “learn this later, but additionally let the LLM learn it”.

Completely different inputs, identical thought: cease dropping the good things you stumble throughout. The whole lot backs as much as GitHub. The entire staff can browse one another’s analysis library.

A pleasant aspect impact: with that a lot structured materials sitting in a single place, you possibly can ask attention-grabbing questions of it.

Louise added a “Scrap developments” tab that runs a weekly LLM report over her library and returns themes, ache factors SEOs are speaking about, and 5 to 10 ready-to-brief article concepts. The clipping device quietly become an editorial calendar.

We constructed three instruments that chip away on the “what ought to we write” drawback from completely different angles.

The most important is Mateusz’s Key phrase Analysis Hub, a four-tab workflow over Ahrefs knowledge:

• Discovery pulls seed-and-related key phrases with branded/NSFW filters.
• Content material Hole finds competitor key phrases we don’t rank for.
• Breakout finds weblog key phrases rating 31 to 100 that don’t have a devoted web page but.
• Grasp Checklist dedupes every part and labels it by cluster and tier.

The intelligent bit is the tier system: every candidate will get a cosine distance out of your matter clusters, then reduce by percentile into Tier 1 (core orbit) by Tier 4 (in all probability noise). You cease arguing about whether or not one thing is “on-topic” as a result of the mathematics simply tells you.

Louise’s Trending Key phrases is the day by day model: takes her seed subjects, queries Ahrefs on daily basis, and surfaces what’s new, what’s rising 3m/6m/12m, and whether or not we already rank. The “spot it earlier than everybody else does” device.

My Entity Hole Finder comes at it from a unique angle. It scrapes our whole weblog for entities and phrases we point out usually, checks if we’ve a devoted web page for every, and exhibits the place we rank.

I constructed it as a result of I stored noticing we’d reference an idea fifty instances throughout the weblog with out ever writing the submit that ought to rank for it. Plumbed into the pipeline, it ought to generate these posts mechanically.

Mateusz and Louise each constructed Reddit listeners. Independently. On the identical day. That in all probability tells you every part about how a lot we needed one.

Each variations scan r/Search engine optimization, r/bigseo, and r/SEO_LLM for AI-search discussions (GEO, AEO, AI Overviews, Perplexity, ChatGPT search), flag the “scorching” posts the algorithm is surfacing, and roll the week up right into a Monday report: themes, ache factors, rising developments, weblog concepts. Mateusz calls it “RSS on steroids”, which is the perfect description.

We additionally constructed two adjoining radars.

My Search Advertising Information Aggregator grabs the final seven days of search-and-marketing information (constructed for our e-newsletter, now utilized by anybody scanning what occurred this week).

And Mateusz’s Search engine optimization Experiment Tracker helps you to arrange an experiment with a URL and speculation (“including FAQ schema will enhance AI Overview citations”), snapshot baseline visitors and rankings from Ahrefs, take periodic snapshots, and on the finish hit Assess for an LLM verdict: Labored, Didn’t Work, Inconclusive, or Too Early.

Cease counting on “I feel this labored” and have the receipts.

The factor that quietly impressed me most isn’t a device.

It’s the sample Mateusz wired by Scrapbook, Notes, and Supply of Reality: each repo has an index.json that auto-updates every time a file is created, edited, or deleted.

From that index, a light-weight reference file will get regenerated, a plain-text abstract the agent reads initially of any dialog. The agent is aware of what exists with out fetching something, and solely pulls full content material when it truly wants it.

As Mateusz mentioned:

“This device expands what feels potential, and it’s addictive. You retain fascinated by what else you can construct, even past Search engine optimization.”

This was how Mateusz ended up with instruments like Scrapbook, his very personal inspirations clipping device. Paste any URL or uncooked textual content, and Agent A will learn it and generate a structured observe with a abstract, key bullet factors, particular claims, knowledge factors, and three article concepts impressed by the content material.

It’s indirectly Search engine optimization-related however it’s a base for him to draft his subsequent thought management piece.

That’s what “use AI extra” can’t seize. Utilizing ChatGPT looks like asking a sensible good friend for a favour. Constructing a device looks like hiring one. When you’ve employed one and watched it work, you begin wanting round your week for the subsequent factor at hand off.

Not one of the standout tasks requested anybody to invent a brand new workflow from scratch.

• We had been already saving LinkedIn posts; SavedIn made the saves usable.
• We had been already amassing URLs; Scrapbook gave them construction.
• We had been already lurking on Reddit; the listener turned the lurking right into a weekly report.
• We had been already refreshing knowledge posts each quarter; Knowledge Refresh simply made the refresh take an hour as an alternative of a day.

Don’t construct a device that requires a brand new behavior. Construct the one which makes an current behavior sooner.

The massive unlock wasn’t “AI can write.” Everybody is aware of that.

It was that the agent may pull up the precise info, like previous drafts, saved analysis, our inner fashion information, what we already rank for, with out us pasting them in each time.

Instruments like Supply of Reality, Scrapbook, SavedIn, Notes, the GitHub-backed indexes, Louise’s writing-sample library, the editorial-style talent, none of those generate content material. They seize, organise, and retrieve context.

The drafts that come out of pipelines hooked into them are markedly higher than drafts from pipelines that aren’t. If you happen to’re choosing one factor to repeat from this hackathon, copy the reminiscence layer first. The writing instruments enhance themselves as soon as the reminiscence exists.

Louise had already prototyped items of her workflow on Lovable, and was bracing for a painful rebuild. She bought the alternative:

“It’s very simple to maneuver a mission from one other platform like Lovable and rebuild it in Agent A. Simply export the code and Agent A immediately rebuilds it.”

So if you happen to’ve already began constructing someplace else, you don’t lose the work. You simply plug it in subsequent to Ahrefs knowledge.

Our hackathon was solely 4 folks. All on the content material staff. We didn’t invite anybody else from gross sales or product advertising to hitch in.

You’d need to withstand the urge to make it cross-functional on spherical one. Twenty folks throughout three departments turns the hackathon right into a collection of Zoom calls and conferences. That defeats the aim of a hackathon, which is to construct.

Decide the staff with essentially the most repeatable, painful workflows. Content material, Search engine optimization, ops, assist, lifecycle advertising — anyplace folks do roughly the identical factor each week. Roll it out wider after you might have demos to level at.

That is the one which quietly kills most “innovation weeks.” Don’t ask folks to construct “alongside” their regular work. They’ll default to the conventional work.

Ryan cleared our week the Friday earlier than: no posts, no edits, no conferences outdoors the hackathon, OOO replies on Slack. If you happen to genuinely can’t spare 5 days, do three. Don’t do one.

I’ll be trustworthy: We didn’t do that for our hackathon. However I did this for myself personally and located it useful.

As a result of the checklist of what you can construct is infinite. Between that and “use AI extra”, you may be caught in a panic and find yourself doing nothing. So, having an inventory of frustrations made tackling the hackathon simpler.

So, you’d need to checklist down the issues in your job that you just maintain doing manually that you just want you didn’t must. That’s how I got here up with my Knowledge Refresh device. It was as a result of one thing that seemed so easy on paper took me surprisingly lengthy to do.

Two guidelines:

• Be particular. Not “analysis”, however “I spend two hours each Monday going by my LinkedIn saves and pasting the great ones right into a doc.”
• Be trustworthy. Boring chores depend. Probably the most-used instruments we constructed got here from chores, not from anybody’s intelligent AI thought.

These lists are the briefs. The extra particular the frustration, the higher the device.

Why does this interview step matter? Right here’s what Louise mentioned:

“It’s simple to get caught in immediate loops bettering the UI of your app, and making fixed incremental enhancements, relatively than ensuring the app achieves its overarching aim. This results in numerous token waste. As a substitute it helps to plan what you need beforehand and spend time speaking/being interviewed by the Agent earlier than you begin constructing.”

Once more, full honesty: I didn’t do that myself. Nevertheless it’s such an ideal thought. The following time we run a hackathon, and even simply me constructing one thing for myself, I’m going to do this.

It’s best to too.

Everybody exhibits what they constructed, why, and the way it works.

The demos are the place the cross-pollination occurs, the place somebody realises their device can be 10x higher with the info one other teammate’s device produces, and the place the subsequent week’s work plans itself.