Freelance Flutter Developers in England
Freelance Flutter Developers in England
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Daniel Meen
Thetford, UK
Full Stack Engineer - Mobile | IoT | AI
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Full Stack Engineer - Mobile | IoT | AI
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Flutter & ChatGPT Integration: Real-time Chat Streaming + Local…
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20
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Uber Style - Taxi Booking Mobile Application - YouTube
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7
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Advanced POS Mobile App Development: Seamless Integration of Mu…
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8
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SCR3310 Smart Card Reader Android App - YouTube
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21
Flutter Developer
(2)
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ossa codes
London, UK
Bringing Your Web & Mobile Ideas to Life 🚀
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Bringing Your Web & Mobile Ideas to Life 🚀
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Flutter web app for public chat application based on location.
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16
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A map based dating hybrid app with flutter
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11
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A chat Mobile App(Android and Ios) using Flutter
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9
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Flutter Developer
(3)
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IDOWU ELIJAH
London, UK
AI Product Engineer | Building Production Ready AI Apps
23
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AI Product Engineer | Building Production Ready AI Apps
1
I’m not just building a poker UI. I’m building a system that can understand the table. This project started with a simple idea: Can software look at a poker table and turn what it sees into structured game logic? The deeper I get into it, the more interesting the engineering becomes. The system has to deal with things like: → Card recognition — identifying cards from the screen → Board detection — understanding the current board state → Player positioning — determining where players are located → Action recognition — interpreting Fold, Call, and Raise → OCR — extracting information from visual elements → Coordinate mapping — knowing where important elements exist on different layouts → Game-state logic — turning all that visual information into something the application can actually understand And this is where AI-assisted development becomes powerful. I can use an AI coding agent to help investigate the codebase, implement changes, run tests, and work through bugs. But the outcome still depends on how I design the logic, test the edge cases, and verify what the system is actually seeing. The goal isn't: “Make AI write a poker application.” The goal is: “Build a system that can reliably understand what is happening on the table.” That's a completely different engineering problem. Right now I'm focused on making the recognition and game-state pipeline more reliable because one incorrect card, coordinate, or player action can affect everything that comes after it. Computer vision + AI + software engineering = some seriously interesting problems. 🧠🔥 What would you build with this kind of technology if you had reliable real-time visual recognition?
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Everyone is talking about AI. Very few are actually building with it. The opportunity isn't in using AI once. It's in creating tools that solve real business problems every single day. The builders who start today will have the biggest advantage tomorrow. What are you building?
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AI can write the code. Engineering is knowing what to test. I’m currently working on a poker-vision system where the application needs to understand what is happening on the table — recognize cards, identify ranks, process board states, and translate visual information into usable application logic. And this project is teaching me something important about AI-assisted development. The difficult part isn't getting AI to change the code. The difficult part is proving that the change actually works. My current workflow looks more like: Read the codebase → Understand the existing logic → Make the change → Run the test suite → Inspect the real output → Find inconsistencies → Fix → Test again. For example, I’m currently testing multiple buyer frames against the recognition logic instead of assuming that one successful test means the system is correct. That's a big difference. A function can compile. A test can pass. The UI can render. And the system can still be wrong. That's why I don't want my AI workflow to be: “Generate the code and move on.” I want it to be: “Make the change, challenge the result, and verify the behavior.” This is becoming increasingly important as coding agents take on more implementation work. Modern agent workflows are already moving toward repository-wide investigation, automated tests, linting, code review, and validation rather than simply generating files. The GitHub Blog (https://github.blog/changelog/2026-03-18-configure-copilot-coding-agents-validation-tools/?utm_source=chatgpt.com) For me, AI isn't replacing the development process. It's changing where I spend my attention. Less time typing every line. More time understanding: What should happen? What actually happened? Why are they different? And how do I prove the fix is correct? That's where the interesting engineering work begins. 🔥 For developers building with AI agents: what do you trust more a passing test, the actual application behavior, or both?
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The hardest part of AI-assisted development isn't generating code. It’s knowing when the code is wrong. I’m currently working on a poker-vision project where the system has to interpret what’s happening on the table — including card recognition, board ranks, hero cards, and positional coordinates. And this is exactly where AI-assisted development gets interesting. The agent can make a change. It can tell you the change looks correct. It can even run the code. But then you look at the actual result and realize: “Something is still wrong.” In this case, I was working through an OCR/ranking issue where the system was reading card information and producing an incorrect interpretation. So the workflow became: Inspect → Understand → Change → Run → Compare → Debug → Verify. Not: Prompt → Generate → Ship. That difference matters. AI coding agents are increasingly capable of working across repositories, editing multiple files, running tools and debugging issues. But current engineering discussions increasingly focus on the verification layer making sure generated changes actually produce the intended behavior. CodeRabbit (https://www.coderabbit.ai/guides/coding-agent-workflow?utm_source=chatgpt.com) For me, this is changing how I think about development. The value isn't just how quickly I can generate code. It’s how well I can understand the system, identify the real problem, direct the agent, and verify the final result. That's where engineering judgment still matters. And honestly, some of the best lessons come from the bugs that refuse to disappear after the first fix. 🔥 Developers using AI: what's one bug that looked “fixed” until you tested the actual behavior?
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25
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(2)
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Aijaz Ali Gopang
Romford, UK
Expert in AI/ML & Full-Stack Solutions
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Expert in AI/ML & Full-Stack Solutions
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dosh app 17+
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9
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Envision: AI Avatar Generator 17+
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6
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MakeupAlley 9+
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7
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(1)
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Marwan Awad
Southampton, UK
Fullstack Dev: React, .NET Core, Flutter Expert
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Fullstack Dev: React, .NET Core, Flutter Expert
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School Payment Platform on Mobile
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20
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HR Job Searching Website
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8
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School Payment Platform
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8
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Flutter Developer
(1)
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Huraira Muzafar
London, UK
Expert Web & App Developer
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Expert Web & App Developer
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Flutter Developer
1
9
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Web Devlopment
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5
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Desktop Application
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6
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Flutter Developer
(1)
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Samson Alejolowo
Manchester, UK
Experienced Full-Stack & Mobile Engineer
$1k+
Earned
1x
Hired
1
Followers
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Experienced Full-Stack & Mobile Engineer
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Brand Box – App Development, Web Design, Digital Branding
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12
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Streamline Mobile
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12
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Glidewell Mobile app
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10
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Flutter Developer
(1)
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Petar Santor
London, UK
Transforming Ideas into Mobile Apps
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Transforming Ideas into Mobile Apps
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XYZ App
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17
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Gelato app
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66
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Wio app
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42
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Findout app
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19
Flutter Developer
(1)
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