Next gen app developer
Turn your idea into a working app, built with AI in weeks.
Freelance development with AI in the loop — and every build tested in practice against the scope agreed up front. You get shipped software, not a demo.
Diflowrin
Next gen app developer
What your app gets built in
The stack adapts to your problem.
I evaluate your requirements — performance, scalability, platform, integration needs — and pick the most efficient technology stack for them.
Every build is tested end-to-end to ensure reliability, so you get a solution optimized for your use case, not constrained by a single language or framework.
Below are the technologies I can build in, depending on what your app needs.
TypeScript
React, Next.js, Node
Python
FastAPI, Django, automation
JavaScript
Vue, Svelte, Express
SQL
Postgres, MySQL, Supabase
Swift
Native iOS apps
Kotlin
Native Android apps
Dart
Flutter, cross-platform
PHP
WordPress, Laravel
Go
APIs and microservices
Rust
Performance-critical code
C#
.NET services, Unity
Java
Spring, Android
How a project runs
From the first call to a deployed application, in three steps.
Scope the build
I map out what the app has to do, who uses it and where it runs. You get the scope, the timeline and the price before any code is written.
Build in short cycles
AI writes the code, I direct it and test every build in practice. You see working software every few days instead of a status report at the end of the month.
Ship and hand over
Deployment, documentation and the repository are yours at the end. Nothing is tied to me, so you can take the codebase to any other developer.
Tested before it ships
AI writes the code. What decides whether it is any good is whether the app does the job it was scoped for, so every build is put through practical testing before it goes near production.
AI across the whole cycle
AI is not autocomplete here, it is the whole build. It writes, fixes and rewrites, and I stay responsible for every call: what gets built, what gets dropped, and whether the result is good enough to put in front of your users.
Fixed scope and price
You agree what gets built and what it costs before the work starts, so the budget stays put while the project moves.
Product judgment included
Product and interface decisions sit with one person. You get an opinion on what is worth building, not just someone who takes the order and disappears.
What a next generation developer actually is
Nearly every developer uses AI now. Google’s DORA research put daily use at 90% in 2025, so reaching for the tool is no longer what separates one developer from another. The gap moved somewhere else: JetBrains surveyed 24,534 developers and found that while 85% use AI regularly, only 44% have it genuinely integrated into how they work.
I go further than most, and I would rather say it plainly than let you find out later: I do not write code by hand. AI writes it and I direct it. What I bring is deciding exactly what the app has to do, choosing the stack that fits, and testing every build in practice until it does the job. Specifying and testing is the part AI cannot do for you, and it is where a project is won or lost.
AI as a collaborator
AI writes the code and I direct it. The work is deciding exactly what the app has to do, then testing each build in practice until it does that.
AI concepts in the stack
Prompt design, chaining, retrieval-augmented generation and embedding-based search are the parts of AI I work with hands-on, used where they solve a real problem rather than because they sound impressive.
Roles that overlap
On a small build, product, design and testing are one job. The same person decides what the app should do, how it should feel to use, and whether it is ready to go live.
" AI made the typing fast. Deciding what is worth building is still the job. "
Most of the work is web and mobile applications for founders and small teams who need a product that runs, not a prototype deck. The stack follows the problem, every build is tested in practice before you see it, and you own the repository from the first commit.
What that looks like in practice
- Scope and price
- Both fixed in writing before the first line of code.
- Progress
- Working builds every few days, not status reports.
- The repository
- Yours from the first commit, whatever happens next.
- Generated code
- Written with AI, checked by running it. The repository is yours to audit.
Typical work
Where the software industry actually is
42%
of all committed code is now written by AI, and developers expect that share to reach 65% by 2027.
96%
do not fully trust that AI output is functionally correct, and only 48% always check it before committing. Trust has to come from testing, not from the tool.
67%
of engineering leaders say AI-generated code needs more testing than code written by hand. That testing is where the work goes.
+81%
more duplicated code than in 2023, measured across 623 million real commits. Refactoring fell to 3.8% of changes.
37%
of those using AI to build describe their governance as formal or better, while 94% report real productivity gains. Adoption is not practice.
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