I use it with Delphi. Claude Code with Opus 4.7 works fine. It can use FPC in Delphi mode so that it can test itself. I'm doing greenfield and not an old project though.
SEEKING WORK - 26+ year Software Architect - Remote - US
Full stack developer, growth hacker, and serial entrepreneur for a variety of projects involving tens of millions of visitors. Jack of all trades software developer and strategist for AI, the web, mobile, and desktop. Core competency lies in faster time to market by modifying existing technology to get the job done now instead of later.
Recently working with Stable Diffusion 1.5, SDXL, Flux, Dreambooth, LORAs, Diffusers, Replicate, Suno AI, Controlnet, GANs, A1111, Python, PHP, Runpod custom GPU clouds (H100 NVLs, A40s, 4090s, A5000s, A6000 ADAs), HTMX, Open AI APIs, AI video, and more. 70+ million AI photos delivered. Hundreds of thousands of fine-tunes trained. 1000+ AI songs generated.
SEEKING WORK - 26+ year Software Architect - Remote - US
Full stack developer, growth hacker, and serial entrepreneur for a variety of projects involving tens of millions of visitors. Jack of all trades software developer and strategist for AI, the web, mobile, and desktop. Core competency lies in faster time to market by modifying existing technology to get the job done now instead of later.
Recently working with Stable Diffusion 1.5, SDXL, Flux, Dreambooth, LORAs, Diffusers, Replicate, Suno AI, Controlnet, GANs, A1111, Python, PHP, Runpod custom GPU clouds (H100 NVLs, A40s, 4090s, A5000s, A6000 ADAs), HTMX, Open AI APIs, AI video, and more. 70+ million AI photos delivered. Hundreds of thousands of fine-tunes trained. 1000+ AI songs generated.
SEEKING WORK - AI Solutions Architect - Remote - US
Full stack developer (26+ years), growth hacker, and serial entrepreneur for a variety of projects involving tens of millions of visitors. Jack of all trades software developer and strategist for AI, the web, mobile, and desktop. Core competency lies in faster time to market by modifying existing technology to get the job done now instead of later.
Recently working with Stable Diffusion 1.5, SDXL, Flux, Dreambooth, LORAs, Diffusers, Replicate, Controlnet, GANs, A1111, Python, PHP, custom GPU clouds (H100 NVLs, A40s, 4090s, A5000s, A6000 ADAs), HTMX, Open AI APIs, Runway ML video, and more. 70+ million AI photos delivered.
- Stock and real estate data summarization and analysis
- Psuedo scaling algorithms
- Marketing copy
- Code conversion between languages (like C# to Delphi)
- Cost comparisons between signing a Cloudflare enterprise contract and not over 12 months
- Naming a novel brainstorming
and many many other things. A huge productivity multiplier. It's like having 1000 domain experts and junior devs on tap 24/7 that you don't have to hire off Upwork. Also have to be able to recognize when it produces trash.
The pricing or lack there of is a huge turn off. We use Replicate and Runpod. On Replicate everyone just shares the GPU cloud. On Runpod I had to bundle 8 together into my own cloud but I can't see that this service solves my problems (queueing image generation and restarting jacked stable diffusion nodes).
I'm a full stack contractor. Been following generative AI since late last year. Picked up an AI startup gig in early January. Launched a couple weeks ago. Building out the client, API, server, and orchestrating the AI image generation pipeline plus Dreambooth. Choosing an AI GPU provider (or 3), solving prompt issues, figuring out model settings, making sure it can scale. A lot of the models are all comoditized on providers like Replicate which makes it like any other API based project. AI knowledge is still very useful to know what settings to use with the models though.
Building an MVP right now. Digital Ocean but may switch to Linode. LAMP. Wordpress for web and the API. Delphi for iOS, Android, Windows, macOS, and Linux clients. Stable Diffusion.
Interested in content marketing strategy and generative AI right now but 25+ years as a software developer and entrepreneur. Delivered content and technology to 250 million people in the last 12 years.
It isn't difficult. Just use Delphi. 26+ years of unbroken excellence building using Win32. And now Microsoft is saying that going forward they are back to promoting Win32 as the best way.
Delphi still exists and you can still do it in Delphi. Responsive. Cross-platform on Android, iOS, macOS, Windows, and Linux. Single codebase single UI.
Yes, it could be as simple as having Dev-C++ run a build every time a file is saved. Currently it does not do this. Remember, Dev-C++ didn't have -j support at all until I added it. TwineCompile does do this (background compile). Therefore the IDE is providing this functionality and has nothing really do to with make or the compiler.
TwineCompile is not a plugin wrapping the -j flag. It is a separate thing entirely unique to C++Builder. It does offer integration with MSBuild though.
The second part of that was the fall off. With the 1 million size files it only ever used half of the cores and each successive round of core compiles it would use even less cores. TwineCompile didn't seem to have that problem but this post was not about TwineCompile vs. MAKE -j so I did not investigate this farther.
I was expecting MAKE/GCC to blow me away and use all 64 cores full bore until complete and it did not do this.