It's 11:47 PM on a Sunday. Maya has six hours of laptop battery, a FastAPI app she finished an hour ago, and a friend who asked to see "the thing" before standup. Tabs open: Heroku pricing, Fly.io machine docs, a half-read Render tutorial. None of them are loaded.

She types curl -X POST https://api.instanode.dev/db/new and her laptop replies with a working Postgres URL in 945 milliseconds.

She read none of those tabs. The other people in this post had different problems but the same Sunday-night shape: a problem at the front of their head, low tolerance for ceremony, and the next twenty minutes to make the problem disappear.

Maya's full night

Maya is shipping a tool called Bookbase. People upload a CSV of book titles and get back tagged, summarized entries with embedding vectors attached so the next "find me books like this one" query is fast. The work was the modeling, the prompt design, the rate-limiting. The work was not supposed to be the deploy.

Maya does not run Kubernetes. Maya does not want to.

At 11:50 she has the Postgres URL. She runs curl -X POST .../cache/new for Redis — that's where she'll cache the tag dictionary so the LLM doesn't have to re-derive labels on every request. Two URLs in her clipboard.

# 1. Postgres for books + embeddings, Redis for tag cache
curl -X POST https://api.instanode.dev/db/new -H 'Content-Type: application/json' -d '{"name":"five-people-who-built-something-th-db"}'
curl -X POST https://api.instanode.dev/cache/new -H 'Content-Type: application/json' -d '{"name":"five-people-who-built-something-th-cache"}'

new \ -H "Authorization: Bearer $JWT" \ -F "name=bookstore-app" \ -F "[email protected]" \ -F 'env_vars={"DATABASE_URL":"...","REDIS_URL":"..."}' ```

env_vars is a JSON map; whatever's in there lands in the deployed pod's environment on the first build. Maya pastes the two connection URLs in. The multipart upload completes in three seconds.

90 seconds of build later — there's a kaniko Job (kaniko = a build tool that runs a Dockerfile inside a container without needing root) grinding away in the platform cluster, but Maya doesn't have to know that — and the response includes:

https://bookbase-7a3f.deployment.instanode.dev

A working HTTPS URL on the deployment subdomain, with a valid Let's Encrypt cert that cert-manager handled in the background.

Maya curls her own URL: {"ok":true,"books_indexed":0}. She uploads a sample CSV. She refreshes. Twelve rows of tagged, summarized books come back.

She sends the URL to her friend at 12:14 AM and goes to bed.

What that 90 seconds usually costs

Every alternative Maya didn't read assumes she's awake. Heroku still wants a Procfile, a runtime.txt, and a credit card before her first push — fifteen minutes of yak-shaving on a laptop at midnight. Fly's flyctl launch is fast, but its first run drops her in an interactive prompt about regions she didn't know she had to pick. Render and Railway want her to git push, which means a new repo, a new remote, and reading their auto-detected build settings before anything happens. None of these are bad products. All of them assume she'll wait until tomorrow.

The instanode endpoints fit in muscle memory: /db/new, /cache/new, /deploy/new. Maya read zero documentation this session. The platform shapes itself around what she was going to type anyway.

When she wakes up tomorrow her resources will be marked anonymous and expire at midnight Monday. If Bookbase has a user by then she'll click the claim link in the response and pay $9/mo. If it doesn't, the URL goes away and nothing was wasted.

Two others, same week

Maya is not unusual. The shape repeats. Here are two more from this week whose problems looked nothing like Maya's and whose sessions looked exactly like hers.

Cleo — a coding agent that finally remembered things

Cleo is not a person. Cleo is a long-running coding agent that lives inside someone's terminal for days at a time, handed tasks like "ship the auth refactor by Friday." Until last Tuesday her memory was a flat memory.md file: it broke on corrupted writes, fell out of sync across terminal tabs, and couldn't be queried for anything beyond grep.

The fix was one tool call. Cleo issued POST /db/new from inside her own agent loop — no human in the middle, no signup, no dashboard — and got back a Postgres URL she could write to immediately. Her new schema is a memories table with a vector(1536) embedding column. Pgvector (Postgres's vector-similarity extension) ships pre-installed on every instanode database, so similarity search is one line: SELECT ... ORDER BY embedding <-> $query LIMIT 10. No separate vector DB, no second auth flow, no second bill.

Two days later her user asked about a decision they'd made on Monday. Cleo answered correctly and quoted the original turn back. The memory wasn't a new feature she shipped. It was a thing that started working because the storage layer stopped being a project.

Priya — the Stripe webhook that was eating events

Priya is a senior engineer at a payments company. Their Stripe handler had been intermittently dropping events for a week and nobody could reproduce it locally. The usual tools failed her in the usual ways: stripe trigger fires synthetic payloads, not the malformed real ones she needed; ngrok wanted a paid plan for an account her size; the staging environment was booked by another team's load test.

She typed curl -X POST https://api.instanode.dev/webhook/new and pasted the returned receive_url into Stripe's test endpoint config. The next fourteen real payloads landed in the platform's request log, fully inspectable — headers, body, timestamp, raw bytes. The malformed field was in the second one: a customer with a unicode apostrophe in their billing name that her JSON deserializer was choking on.

She wrote the fix on the train. It shipped before standup. The whole debugging session — from "I need a public URL" to "I have a repro" — was under three minutes, and the URL is still sitting in her shell history in case the bug comes back.

What ties them together

A solo founder at midnight, an autonomous agent halfway through a multi-day task, and a senior engineer on a commuter train do not look like the same customer. They have nothing in common on a marketing slide.

What they share is the moment they show up: eyes glued to the problem they want to disappear. Anything between them and "the thing is alive on the internet" is friction. Anything that survives that gap is a story they tell their friends.

Three different starting points, three different problems, one shape of solution: curl, build, ship, optionally claim.

If you're somewhere in this list — or in a fourth shape we haven't documented yet — the curl works right now. No signup.