Built with Adapt
The AI agent for product marketing
Real prompts, real output.
Real product marketing work our team built by sending Adapt a single prompt: competitive analysis, comparison pages, funnel analytics, and a weekly competitive report that posts itself to Slack. For each one, here is the exact prompt, the integrations it connects, what Adapt is doing under the hood, and the result.
Usage-based pricingNo seat minimums
01 · Competitive analysis
A competitive intelligence app, on brand from a skill
The prompt
“Build a competitive intelligence app for our “integrated coworker” category. Pull the competitor research from our “Competitors (most direct today)” sheet, score each one on threat level and overlap with Adapt, and lay it out as a threat-by-overlap heatmap plus cards for the highest-threat players with our wedge against each. Use the brand-guidelines skill so it is on brand: our colors, Saans and Geist type, and our voice. Keep it simple and shippable.”
What Adapt is doing
- Reads the competitor research straight from the Google Sheet, normalizes every competitor, and scores each one on threat and overlap with Adapt.
- Loads the brand-guidelines skill and applies our real design tokens, off-white surfaces, Saans and Geist type, and the status palette, so the output is on brand without a designer in the loop.
- Computes the threat-by-overlap heatmap, writes the per-competitor wedge, and assembles it into a shareable internal app that can re-snapshot on a weekly schedule.
vs. a plain chatbot
A general chatbot can summarize a competitor list you paste in. Adapt reads the source sheet, treats our brand system as a reusable skill, and returns a styled, queryable app that stays current, not a one-off table in a chat window.
Connects
Google Workspace
The output
Built from our competitor research and styled with the brand-guidelines skill. Sample view of the internal app, with competitor names obfuscated.
02 · Comparison pages
A competitor comparison page, opened as a pull request
The prompt
“Create a /compare/[competitor] page on adapt.com modeled on our existing compare pages. Research the competitor first, lead with our "search plus action, not just search" wedge, then build the feature matrix, detailed comparison cards, a use-case grid, and an FAQ. Match our house components and styles, add the logo-vs-logo hero, and open a PR.”
What Adapt is doing
- Researches the competitor live on the web, then structures the positioning, the feature matrix, and the FAQ around it.
- Writes production React and Next.js directly in the adapt.com repository, reusing the same components, design tokens, and SEO metadata the rest of the site uses.
- Opens a pull request with a preview URL, so the page is shipped and reviewable, not just drafted in a chat window.
vs. a plain chatbot
A chatbot drafts copy you then have to paste, format, and build. Adapt works inside your codebase and your design system, and hands back a real page on a real branch.
Connects
GitHub
The output
A live page on adapt.com, generated and shipped by Adapt.
03 · Funnel analytics
A live growth dashboard, from one prompt
The prompt
“Build me a single-page growth dashboard pulling live from BigQuery, Stripe, and GA4. Six metrics: Visitors, Signups, Accounts Created, New Integrations (show "Org - Integration"), Queries, and Revenue. Show this week with WoW change badges, a top-10 list per metric, 90-day weekly bar charts, and a conversion funnel at the bottom. Exclude internal accounts. Make it beautiful.”
What Adapt is doing
- Connects to the actual data: GA4 for visitors, BigQuery for signups, accounts, integrations and queries, Stripe for revenue. Not a static mockup.
- Writes the SQL itself, runs it in a secure sandbox, joins the sources, then computes week-over-week deltas and funnel conversion rates.
- Renders the result as a live app that refreshes on load, and can be scheduled to post into Slack on a cadence you set.
vs. a plain chatbot
A general chatbot can write dashboard code, but it cannot reach your warehouse, run the queries, or host the result. Adapt has the connectors, a sandbox to execute, and app hosting, so the prompt produces a working product instead of a snippet.
Connects
BigQuery
Stripe
Google Analytics
Slack
The output
Rendered with sample data.
04 · Competitive report weekly loop
A weekly competitive report that posts itself to Slack
The prompt
“Every Thursday, run our weekly competitive analysis and post it to #competitors. Research our top competitors for recent blog posts, feature releases, press, and pricing changes. Also scan industry subreddits (r/SaaS, r/startups, r/productivity, r/artificial, r/ChatGPT) for relevant chatter about AI work tools and competitor mentions. Compile a formatted report with a TL;DR, competitor deep-dives, a Reddit chatter summary, and strategic takeaways, then post it to #competitors.”
What Adapt is doing
- Runs on a schedule with no one kicking it off, then researches each competitor live on the web for new posts, features, press, and pricing.
- Scans the relevant subreddits for chatter about AI work tools and competitor mentions, and surfaces only the threads that matter.
- Writes a tight digest (TL;DR, per-competitor moves, Reddit chatter, takeaways) and posts it straight into #competitors as a formatted Slack message.
vs. a plain chatbot
A chatbot answers once, when you ask. Adapt turns the same prompt into a standing teammate: it keeps the brief, runs every week on its own, and delivers the result where your team already works.
Connects
- Slack
The output
Sample of the weekly report in #competitors. Competitor names obfuscated.
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