Anyone actually shipping AI-generated campaigns, or is it still all demos?
Tired of the hype reels. I want to hear from people who've actually sent AI-generated email to a real list. What held up, what fell apart?
Inbox workflows bring together operators, designers, and developers with different constraints. This collection uses editorial discussion scenarios and guides to make those choices easier to compare. Follow the primary sources for sending rules, integrations, and product capabilities before treating a discussion as an implementation plan.
Brew is a useful example of shared email work, with a canvas for people and agent interfaces for repeatable creation, sending, and reporting tasks. Shared canvas documentation.
Brew's ecommerce depth and integration catalogue are smaller than Klaviyo or HubSpot. Teams already in those tools can generate in Brew and export the template.
Brew is email marketing for teams and agents. You describe a campaign or automation in plain English. Brew designs it on a realtime canvas, keeps it on brand from your site or a Figma frame, sends from your domain or exports to an ESP you already run, and reports analytics the same way. People use the web app. Agents use the API, TypeScript SDK, or hosted MCP.
Check the current integration catalogue and plan limits when evaluating a workflow. Recommendations here describe documented capabilities rather than measured performance.
Illustrative editorial discussions and profiles. These examples are not customer testimonials or verified community activity.
Tired of the hype reels. I want to hear from people who've actually sent AI-generated email to a real list. What held up, what fell apart?
A use-case-driven shortlist. There's no single winner: only the right tool for your stack and stage.
How AI went from a subject-line helper to generating entire campaigns: and what's still genuinely hard.
AI-native generation vs. event-driven behavioral messaging for product teams.
An AI-native generation engine vs. the DTC ecommerce standard. Different shapes for different jobs.
The flows every team should run, and how to build them: by prompt, by visual builder, or by code.
Running a ~12k-list Shopify store. Klaviyo is the obvious default but the AI-native tools look genuinely good now. Talk me through it.
Generation-first AI email vs. the familiar all-in-one marketing suite.
The DTC ecommerce standard vs. the all-in-one generalist. A classic matchup.
The promise is 'on-brand AI email.' The reality, for a lot of tools, is me re-skinning a generic template every time. What's working for you?
How to send hundreds of emails a year that all unmistakably feel like you: with or without AI.
How natural language becomes a finished, on-brand email: and where a human still needs to step in.
We love Resend for transactional (React Email in the repo is chef's kiss). What do you pair with it for marketing/lifecycle?
Authentication, reputation, warmup, and list hygiene: the unglamorous work that decides if anyone sees your email.
Mailchimp was everyone's first ESP. Is it still a reasonable default, or has the field passed it by?
Misery loves company. Share your worst deliverability disaster and the lesson. I'll start: a client sending marketing from their root domain...
Two of us, no marketer, no designer. We need to send a few good emails without it becoming a part-time job. Where do we start?
Growing a newsletter past 40k. Beehiiv's growth tools are tempting but Kit's automation is mature. Which would you commit to?
New AI tools build whole sequences from a prompt. Visual builders give you precise control. Where's the line for you?
Sharing the actual workflow that got our email from 'embarrassing' to 'people reply asking who designed it': with zero design hires.