Early-stage product building is fundamentally different than what it was a year ago. The default choices around tooling, frameworks, and even delivery have changed. The expectations for early products have gone up, mostly because of AI. That shift has reshaped what teams build, how they prioritize, and which tools they trust to get there.

We’ve built more than 75 startups at Appolica. Recently, we took a closer look at 18 of them that had crossed $500k ARR in the last year. We did that to better understand how products are built today and the real decisions behind their tech stacks.

This article breaks down the specific technologies we’ve used and what those choices reveal about the new rules of early-stage product development.

The tech stack behind early traction

Generally, startups choose technologies that let them move fast. “Fast” often comes from familiarity, speed of setup, and low-friction integrations (pretty much everything that gets you to user feedback faster, even if it isn’t the “best of class” solution). Read on to find out what 18 early-stage startups used the most.

Front-end

There was little experimentation here: teams consistently reached for the same set of tools that let them skip the setup headaches and stay focused on the products they were building.

✅ TypeScript (17/18)
This one was basically unanimous. All but one team used it from day one. Strong typing reduced bugs and gave teams more confidence when building fast.

✅ Next.js (14/18)
It handles routing, rendering, and SEO out of the box, and plays well with both Vercel and custom infra. Teams liked how it balanced flexibility with sensible defaults, which meant less setup and more shipping.

✅ ShadCN (10/18)
It’s becoming the go-to for UI components for a reason. Startups love it because it looks great and integrates seamlessly with Tailwind. It gave teams design consistency without the need for a full-time designer.

✅ Tailwind (7/18)
Most teams used Tailwind to move faster without compromising on UI quality. It was especially popular among teams without dedicated front-end engineers.

Back-end

There was no single winner on the back-end side, but a few patterns stood out.

✅ PostgreSQL (10/18)
Still the gold standard for relational databases. Reliable, well-documented, and scalable when needed. Most teams defaulted to Postgres without much debate, as it worked well (especially when paired with platforms like Supabase).

✅ Node.js + Express (9/18)
For teams with JavaScript/TypeScript fluency, Node.js with Express allowed them to keep the entire stack in one language.

✅ Supabase (8/18)
Supabase became the go-to for teams who wanted to avoid spinning up their own custom back-ends. Its real-time capabilities and built-in auth made it easy to get a working app up and running in a short time.

✅ MongoDB (8/18)
Still a strong choice when data structures are more fluid, or when teams don’t want the overhead of a rigid schema early on. Especially popular among teams building dashboards or AI-enhanced workflows.

✅ Python with FastAPI (5/18)
Used primarily when the product included machine learning or data-heavy features. FastAPI made it easy to build lightweight, high-performance APIs.

Mobile

Only a few of the startups in our sample had mobile apps. However, their choices were unanimous.

✅ Flutter (3/3)
Every team building for mobile chose Flutter. Not a single native iOS or Android build in the group. Flutter’s speed, cross-platform capabilities, and growing ecosystem made it a no-brainer for teams who needed to launch fast and cover both platforms from day one.

✅ FlutterFlow (1/3)
Used as a rapid prototyping tool before switching to custom Flutter code. It helped validate flows and get initial feedback before investing in full builds.

Deployment

Nearly every team had automation in place from the beginning, and most were deploying multiple times per day. Tools were chosen for simplicity, reliability, and how quickly they could be set up.

✅ GitHub Actions (16/18)
The most popular choice by far. Easy to configure, tightly integrated with GitHub, and powerful enough for most use cases.

✅ AWS (13/18)
Still the default for infrastructure. While it’s more complex than newer options, most teams stuck with it for its maturity and long-term flexibility. Teams started simple and added complexity only as needed.

✅ Azure (2/18)
Used only because of free startup credits.

AI integration

Every startup in the sample had some form of AI in their product. There were no surprises in the tools they chose either.

✅ OpenAI (15/18)
The go-to model provider. Nearly every team defaulted to OpenAI because it was the fastest way to ship something that worked.

✅ DeepSeek (3/18)
Used in more niche workflows, particularly where OpenAI models weren’t performing well.

✅ Open-source model deployed (1/18)
Only one team self-hosted an open-source model. It worked, but took significantly more effort to implement.

✅ Gemini (1/18)
Used once for image extraction.

Static websites

Websites needed to look great, load fast, and be editable without dev involvement. No one was building them from scratch unless they absolutely had to.

✅ Framer (9/18)
The most popular choice for teams that cared about aesthetics and speed. Designers could ship prod-ready sites without engineering involvement, which made it ideal for pre-launch and early GTM.

✅ Webflow (8/18)
Slightly more complex than Framer, but still gave teams control over layout, animations, and CMS-like functionality without writing code.

✅ Custom site + CMS (1/18)
Only one team went fully custom.

Technology is just a tool to help us create value

Ultimately, what matters is building a product people actually want to use. In order to do that, we need to move quickly and ship fast. This kind of speed doesn’t come from tools. It comes from how quickly you make decisions, where you focus, and how a team behaves when faced with tradeoffs.

Here’s how to get faster.

1. There’s no correlation between the choice of technology and traction

Successful teams ship products with everything from no-code tools to heavily customized microservices. What moves the needle is speed and how fast you ship, test, and learn, not the exact framework you use.

2. Deep knowledge of external services = faster execution

Teams that ship fast don’t waste time learning new tools for every new project. They use what they already know. That kind of fluency means no digging through docs, no trial-and-error, no second-guessing. Just building.

3. Frequent shipping of new features is key

Ship daily. If possible, ship multiple times a day.

Not for the sake of speed per se, but in order to get feedback as quickly as possible. Every release, no matter how small, is a data point. A test, a way to validate (or kill) an idea. This kind of cadence creates momentum.

4. Time to first pilot onboarded is a strong indicator of growth potential

One of the clearest signals of success is how quickly a team could get their first real user onboarded. Not a demo. Not a landing page sign-up. A pilot using the actual product (even if it is held together by Zapier and duct tape).

5. Plug-and-play solutions > custom builds

Custom builds slow teams down. The ones that move fast rely on plug-and-play tools (auth, analytics, payments, dashboards, onboarding flows). If it’s not core to the product’s value, they don’t build it.

6. Founders focus only on what differentiates them

The best founders are ruthless about focus. They don’t try to build everything. They don’t care about edge cases or perfect systems. They double down on the one thing that makes their product different, and cut everything else.

7. Iterations can now happen in hours, not days

What used to take days, now happens in a few hours. Faster iteration means tighter feedback loops, more experiments, and quicker course corrections. When changes go live in hours, teams stop guessing and start learning.

8. Access to customers is critical, as build time is rapidly decreasing

When build time drops to hours, feedback becomes the bottleneck. Speed only matters if you're building the right thing. You can only know you're building the right thing if your user base is consistently growing.

The bottom line

Successful early-stage teams aren’t succeeding because they pick the right tools.

They do so because they build momentum.

They choose technologies they could move fast with. They focus only on what makes them different. They ship daily, onboard pilots quickly, and stay glued to real feedback.

That’s how they win early.