Something genuinely new is happening in software development, and 2026 is when it stopped being theoretical.
A founder with a validated problem can ship a production application in six weeks (or less). A two-person team can carry the operational footprint of a company five times its size (check all the YC stories). The skills that used to be the chokepoint — senior backend engineer, DevOps lead, database architect — have collapsed into work that one person and a set of AI tools (AI Employees!!) can actually do well, in a reasonable amount of time.
That's not hype. We've watched it happen. We've shipped 19+ products this way ourselves.
But there's a problem.
For every founder building successfully in this new model, there are five building badly. Vibe-coded prototypes that collapse the moment a real user lands. Architecture choices made by an LLM that has no opinion on the cloud bill. Security holes invisible until the breach. AI agents wired up with production write access because nobody asked the right question.
The promise of 2026 software development is real. The execution gap is wider than ever.
That's why we are here
AntigravityApps is the public lab where we figure out — out loud — what AI-native software engineering actually looks like in practice. Not the conference-talk version. The version where the AWS invoice arrives in month three and you have to live with the choices you made in week one.
We're a small team. We use Claude, Google Antigravity, Codex, and Cursor in different combinations across the spec-to-build process, not all at once. We ship on AWS Serverless because the substrate scales without rewriting. We've open-sourced a chunk of our work at github.com/AppGambitStudio so anyone can audit how we actually build.
What we'll write about here
Our day job is shipping. This blog is where we share what we learn along the way — short posts, a couple a week, on the things that actually matter to people building in this new model:
- New SDE patterns — what's working at AI-native scale, what's worth discarding from the old playbook.
- AI tools in practice — different combinations across different builds, when to reach for which, and when not.
- Architecture choices that quietly compound — or quietly destroy — margins six months later.
- Honest mistakes — post-mortems on what we shipped, what broke, and what we'd do differently.
- Keeping sanity — how to stay curious instead of anxious when the profession is changing every week.
The goal isn't to convince you AI is the future of software. That argument is settled. The goal is to share the second-order knowledge — what works, what fails, what costs $5 a month vs $500 — that you only learn by actually shipping.
There's a lot to say. We'll start small.
If any of this sounds useful: browse the portfolio, see how we build, or look at our 6-week MVP offer if you'd rather we build it with you.