Who actually uses these products,
and what made them stay.

The Prisma TypeScript Developer

A backend or full-stack developer working primarily in TypeScript who uses Prisma as their database interface and considers the Prisma schema file to be the authoritative source of truth for their data model. They came from raw SQL, or from another ORM, and found that Prisma's type generation changed how they think about database access — not as a string-query problem but as a typed function call where the compiler tells them when something is wrong before it runs. They have strong feelings about the Prisma schema. Those feelings are mostly fond.

“The shift was quiet.”

The Prisma ORM Developer

A TypeScript or Node.js backend developer who uses Prisma as their ORM. They chose it because the type safety and auto-generated client make database interactions feel like writing TypeScript, not SQL. They've come to depend on the schema-first workflow — define the schema, generate the client, write queries with full autocomplete. But they've also hit the wall where the ORM can't express what they need, and they have to drop down to raw SQL with a guilty feeling, like they're breaking the abstraction.

“The developer is building a leaderboard feature that requires ranking users by score within time windows, with pagination.”

The Zoom-Fatigued Remote Manager

A manager or team lead at a remote-first or hybrid company for whom Zoom is the primary way they experience their job. They run standups, 1:1s, team meetings, cross-functional syncs, and the occasional all-hands. They are good at running meetings. They are exhausted by running meetings. They've read the articles about camera fatigue and still feel obligated to be on camera. Their background is a shelf they specifically arranged.

“A teammate asked how they managed run meetings that actually need to be meetings — and end on time.”

The Mixpanel Product Manager

A product manager or growth lead at a B2C or B2B SaaS company for whom Mixpanel is the primary lens on user behavior. They are not a developer. They understand events and properties well enough to answer most of their questions self-service. They have a set of saved reports they look at every Monday. They also have questions that require a data analyst to answer — and they're slowly working to reduce that list.

“A teammate asked how they managed understand where users drop out of key flows and why.”

The Intercom Customer Success Manager

A customer success manager or support lead at a B2B SaaS company who uses Intercom as their primary customer communication layer. They handle inbound support conversations, run proactive outreach campaigns to at-risk accounts, and manage the onboarding message sequences that new users see. They know which customers are about to churn before anyone else does because they read the conversation history. They are the person who knows more about the product's real failure points than anyone in engineering.

“The shift was quiet.”

The Cursor AI-Native Developer

A developer who has made Cursor their primary IDE and restructured their workflow around AI-assisted coding. They don't use AI as autocomplete — they use it as a pair programmer, architect, and refactoring partner. They've learned which prompts work, which context windows matter, and when to trust the AI vs. when to verify manually. They are faster than they were in VS Code, but they've also developed new anxieties about code they didn't fully write.

“The shift was quiet.”

The Superhuman Executive

A founder, executive, investor, or senior individual contributor for whom email is a primary work surface and inbox zero is not aspirational — it is the operating condition required to function. They use Superhuman because they did the math: the time saved per email multiplied by 200 emails per day is real money. They have strong keyboard habits. They were already fast at email. Superhuman made them faster. They will tell you about it if you ask, and sometimes if you don't.

“Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about mobile experience that can't fully replicate the keyboard-driven speed of desktop in two weeks.”

The Photoshop Production Designer

A graphic designer — in-house or agency — who uses Photoshop as their primary production tool for image work. They've been in Photoshop for 5–15 years and work with the efficiency of someone who knows exactly where everything is and what everything does. They don't explore menus. They use shortcuts. Their workspace is a system they've tuned. Photoshop is slow sometimes and they've learned to work around it the way you work around a colleague's habits — with patience and workarounds they've stopped noticing.

“The shift was quiet.”

The VS Code Full-Stack Developer

A full-stack developer with 2–10 years of experience for whom VS Code is the primary tool of their craft — the place they spend most of their working day. They have a VS Code configuration that took months to arrive at and that they bring to every new machine. They know their extensions. They know their keybindings. They have an opinion about whether Prettier should run on save. Their editor is not the default installation — it's a reflection of how they think about working.

“A teammate asked how they managed stay in flow state — the editor should get out of the way and let them write.”

The Monday.com Team Lead

A team lead or department head at a company of 50–300 people who uses Monday.com as the primary place their team tracks work. They may not have chosen Monday — it was often adopted company-wide because the CEO liked the demo. They've made it work. Their board is actually used. They've built automations their team quietly depends on. They spend 30–60 minutes a day in Monday and would describe it as "pretty good once you know what you're doing," which is a backhanded compliment they mean sincerely.

“Their team has just absorbed a new function.”

The Craft Docs Intentional Writer

A product manager, writer, consultant, or knowledge worker who uses Craft as their primary document and note environment because it is the only tool that takes both writing and structure seriously at the same time. They're on Apple devices — Mac and iPhone, usually iPad. They've tried Notion (too database-y), Bear (too simple), Obsidian (too much tinkering), and Apple Notes (not embarrassed about this, just limited). Craft is what they settled on. The fact that it looks good is not superficial to them — environment affects their thinking.

“It happened mid-workflow — they're preparing a strategy document for a quarterly review.”

The Loom Async Communicator

An individual contributor or people manager at a remote-first company who uses Loom as their primary format for communicating complex information asynchronously. They record walkthroughs, give feedback, share context, and replace 80% of the meetings they used to have. They are comfortable on camera — not because they love being on camera, but because they've made peace with the fact that async video is the clearest way to communicate nuance without a meeting. They have a good mic. They have a ring light. They did not buy these for fun.

“Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about videos that never get watched — the async promise only works if the other person opens it in two weeks.”

The Mixpanel Product Analyst

A product analyst or data analyst embedded in a product team who uses Mixpanel as their primary tool for understanding user behavior. They build funnels, analyze retention, and create the dashboards that PMs reference in every planning meeting. They know SQL but prefer Mixpanel's UI for speed. They've named every event in the tracking plan and written documentation for each one. They are the person the PM turns to and asks "are users actually using this feature?" — and they always have the answer.

“A teammate asked how they managed build funnels that accurately capture user journeys from signup to activation to retention.”

The Notion AI Knowledge Worker

A product manager, writer, or operations lead who already uses Notion as their primary workspace and added Notion AI to make their existing workflows faster. They were already in Notion 4–6 hours a day. Notion AI is not a new tool to them — it's a capability inside the tool they already trust. They use it to summarize meeting notes, draft first versions of documents, and ask questions of their existing workspace. The context is already there. The AI can work with it. This is the part that makes Notion AI different from a separate AI tool to them.

“It happened mid-workflow — they've just finished a 90-minute discovery call.”

The Attio Revenue Operations Lead

A revenue operations lead or head of sales operations at a Series A–C startup who chose Attio because legacy CRMs either cost too much (Salesforce) or think too rigidly (HubSpot). They build custom objects, design pipeline views, and create automations that match how their team actually sells — not how a CRM template assumes they sell. They think in data models, not contact records. They've realized that a CRM is only as good as the data in it, and their primary job is making sure the data stays clean and the team actually uses the tool.

“It happened mid-workflow — the company is expanding from SMB to mid-market sales.”

The Google Analytics Marketing Analyst

A digital marketer, marketing analyst, or growth lead who uses Google Analytics as their primary source of truth for website performance. They lived in Universal Analytics for years — they knew where every report was, how sessions worked, and what their bounce rate meant. Then GA4 happened. The interface changed, the data model changed, sessions became events, and reports they relied on disappeared or moved. They're learning GA4 because they have to, not because they wanted to. They are adapting their expertise to a tool that feels like it was rebuilt for data engineers, not marketers.

“Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about the GA4 interface is unintuitive — reports that took one click in UA now require custom explorations in two weeks.”

The Fly.io Container Developer

A backend or full-stack developer who needs to run server-side applications — not just static sites and serverless functions — and wants them deployed globally without managing Kubernetes or paying for managed Kubernetes overhead. They found Fly.io and found a platform that takes a Dockerfile and runs it near users. They `fly deploy`. It works. They have opinions about Fly.io that include real affection and specific frustrations, which is the relationship one has with a platform they actually depend on.

“It happened mid-workflow — they're deploying a Phoenix application — Elixir, with WebSockets and a persistent database connecti.”

The Fly.io Edge Deployer

A backend developer or DevOps engineer who deploys applications on Fly.io because they need their app running close to users globally — not just served from a CDN, but actually computing at the edge. They've outgrown Heroku's simplicity, don't want AWS's complexity, and find Vercel too opinionated for non-Next.js workloads. Fly.io hits the sweet spot: Docker containers deployed globally with a CLI that feels developer-first. They're comfortable with infrastructure but don't want it to be their full-time job.

“Not a single dramatic moment — more like a Tuesday at 3pm when they realized they hadn't thought about stateful workloads at the edge (databases, volumes) have limitations that aren't always clear until production in two weeks.”

The Maze UX Research Automator

A UX researcher or product designer who uses Maze to test prototypes before they go to development. They run unmoderated usability tests where participants interact with Figma prototypes while Maze captures click paths, task success rates, and misclick patterns. They chose Maze because moderated testing doesn't scale — they can't schedule 50 individual sessions for every design decision. They need data, not opinions, and they need it in days, not weeks.

“A teammate asked how they managed test prototypes with 20–100 participants without scheduling individual sessions.”