HaveTML
a home for AI artifacts
Developer Tools·AI & Machine Learning·Productivity
About
HaveTML is a home for AI artifacts — infrastructure for hosting and sharing AI-generated HTML, Markdown, YAML, and JSON. Upload an artifact and get a permanent sandboxed share link with pinned comments, version history, projects, and access controls. It is closer to Google Drive for AI artifacts than a static host. Surfaces include the web app, REST API, Chrome extension, and MCP so agents can publish directly. Pricing is freemium: Free at $0 for 3 artifacts, Creator at $10/mo for 20 artifacts, and Pro at $25/mo for 100 artifacts. Built for AI builders, product teams, and agencies who need durable, reviewable artifact links instead of ephemeral chat outputs.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
the highest chance of feature adoption and customer retention comes from features that align with the job that the customer needs to do with the tool... features that did something outside that scope were often ignored and complained about like we considered integrating other systems that they may have used or building communication features between teachers but those things were underused or unused at all
Build only features aligned to the specific job-to-be-done your tool exists for
Audit every feature request against the single job your tool solves. FeedbackPanda existed to help teachers ship written student feedback faster. "Communicate with other teachers" sounded reasonable but had zero adoption — outside the job. "Share feedback templates across teachers" sat directly inside the job and exploded adoption + network effects. The pull to add adjacent features is always there; the discipline is to refuse anything that doesn't make the core job faster or easier.
the headline is that realized LTV less than a month in... is 60% lower on the people who saw monthly... of the people who saw the annual as a default around 800 of them went with annual but almost 400 selected monthly.
Pre-Selecting Annual Drove 10% More Conversions and 60% Higher Realized LTV Than Monthly Default
David ran his first-ever A/B test: annual pre-selected vs monthly pre-selected. Monthly default got 10% more total conversions (people clicked through more at $4 vs $40), but realized LTV at 30 days was 60% lower because most stayed monthly. Annual default lost that top-of-funnel edge but captured far more up-front revenue per subscriber. For most apps, defaulting to annual is the right call even knowing some users will switch to monthly.
There's a play for whatever you're stuck on.
Read all 2722 playbooks