Unnecessary information that's safe to ignore
Hi. So I've been away for a couple of weeks. I was up in the remote highlands of Cambodia's Mondulkiri province, where it's cold, quiet, and surrounded by mountains, jungles, and elephants.
It was so relaxing that coming back to the city has made me unnecessarily toxic and grumpy. Imagine spending a few days surrounded byone of mother nature's greatest creations, only to return to traffic, emails, deadlines, and the unfortunate realization that I'm an adult with a job and people to manage.
I also trekked through remote jungle, mountains, waterfalls, streams, and rocks for 17km in a pair of Crocs with the indigenous people, by the way. I survived and I don't recommend it. I did it because I forgot to bring proper trekking shoes. That's it, No deeper meaning.
Anyway, while I haven't been completely off the internet, I've been reading a lot of content about people building and shipping things aggressively with AI, then immediately labeling them "production-grade" and "battle-tested."
And maybe it's because I just spent 17km learning what the word "survived" actually feels like, but...
What???
Slow down, big man.
A Demo Is Not a Battlefield
AI tools have made it faster than ever to go from an idea to a working app, and honestly, that's a great thing. Having more people building things is a good thing.
And if you know me, you know I'm not here to do the whole "real engineers write everything by hand" bit. Sure, that mindset is still somewhat embedded in my identity as a developer, but I try to keep an open mind. Tools change, the way we build changes, and I'm perfectly fine with that.
But there's a word being attached to a lot of these projects that implies a level of reliability you simply can't get from "I shipped it and a few people liked it."
Production-grade. Or its cousin, battle-tested.
These aren't just your Uncle Joe's enthusiastic adjectives that you throw around because something looks cool, not a vibe. They're empirical claims about what a system has survived — and surviving a demo is not the same as surviving Tuesday.
Two different claims, constantly conflated
"Complete, functional, and resilient" means:
- The features work as specified
- It handles the errors you thought to handle (this clause is doing a lot of work)
- It doesn't crash under normal use
- It has decent test coverage
- It looks done in a demo
This is a real, valuable milestone and with modern tools, they get you here faster than ever. Celebrate it. Put it on the README. Just maybe don't reach for the war metaphors yet.
"Production-grade" and "battle-tested" are a different axis entirely. Not "more polished" or "fewer bugs." They're about exposure to conditions you can't fully anticipate or simulate.
A few dimensions people underestimate:
1. Failure modes nobody designed for
Resilient code handles the errors you anticipated. Battle-tested code has lived through the ones nobody put on it, a dependency that silently returns malformed data instead of erroring, clock skew between servers, a queue backing up 10,000x during a spike, a connection pool exhausted by one slow query three services upstream.
Nobody designs for "the third-party API started returning 200 with garbage in it." You find that out the hard way, usually at an hour that makes the logs feel personal.
2. Observability under duress
When something breaks at 3 am, can an on-call engineer figure out what's happening from logs, metrics, and traces or does someone have to SSH in and guess? Which is a spiritual experience, btw. not an architecture.
Logging that satisfies a code review and logging that lets you debug a live incident are not the same thing. You usually can't tell which one you have until the incident happens. The incident is happy to tell you.
3. Graceful degradation, not collapse
When a downstream service dies, does your app fall over completely, or degrade — cached data, reduced functionality, queued retries? Designing for partial failure is invisible work. Almost nobody does it until they've been burned by not doing it. pretty expensive curriculum if you ask me.
4. Concurrency and scale edge cases
Imagine a payment endpoint that checks whether a transaction has already been processed before crediting an account. Looks safe enough.
Then the provider retries the same webhook twice, milliseconds apart. Both requests check the database, both see "not processed," and both credit the account.
Your tests passed. Staging was fine. Production was fine for months. Then one unlucky retry turns a race condition into a real financial bug.
That's the kind of failure that doesn't show up until the system is under conditions you didn't anticipate.
5. Exposure to abuse, not just correctness
Functional code handles legitimate input. Battle-tested code has been prodded, rate limits tested, auth edges probed, injection vectors thrown at it, resources hammered. This isn't something you test for once. It's sanded down over actual incidents.
Friendly users do not do this. Friendly users say "nice UI" and close the tab.
6. Operational maturity
Zero-downtime deploys. Safe rollbacks. Migrations that don't lock the table for 40 minutes while the app quietly suffocates. These are organizational capabilities as much as code capabilities, and they take time and infrastructure history to build up, they don't show up in a codebase on day one no matter how clean the architecture diagram looks.
7. A record of having been wrong
This is the literal meaning of "battle-tested": it has failed in production before, someone fixed it, and there's a postmortem, a monitor, or a regression test that exists because of that specific scar.
A brand-new system — however well-written — hasn't accumulated this yet. There is no "generate scars" button.
They're not a ladder
Easy to read all of this as a sequence: first you make it resilient, then time makes it battle-tested. That's tidy. It's also wrong.
You can have code that is battle-tested and not resilient. Years in production. Real users, real load, real incidents. It works perfectly, until an unexpected external API goes down, and the whole system falls over because nobody ever designed for that. The scars are real. The fault tolerance is not. Survival is not the same as a plan.
You can also have code that is resilient and not battle-tested. Fresh deploy. Timeouts, retries, circuit breakers, cached fallbacks, the whole poster. Excellent fault-tolerant architecture. It has not yet faced real-world traffic. The design is a hypothesis. A very well-written hypothesis. Still a hypothesis.
One is a history while the other is a design. You want both and you don't get to borrow the word for one because you have the other.
Why the distinction is worth defending
Building was always the easy part of the job — the visible 20% you can show in a demo. The other 80% is judgment: knowing which design choices will quietly rot in eight months, knowing when not to build something, reading a system that's been touched or contaminated by many hands and understanding why it looks the way it does, estimating honestly, responding well when production is on fire. None of that shows up in a working prototype. It only shows up after time, real users, real failures, and a few scars.
And none of this means you should undersell a functional, well-tested app. Call it well-engineered. Call it ready for early users. Those are good things. nothing wrong with that.
"Battle-tested" is a different sentence. It requires the battle. Somewhere there's a team that's actually run something through years of incidents and hard-won fixes, and their "production-grade" deserves to mean something different from a weekend project's. The words still have to mean something, or they stop meaning anything.
