I started taking daily classes learning the Thai language in person. While I do learn Thai with AI sometimes, I do feel like an AI tutor can't possible give me the same "edge". Because with AI can just sit down, get distracted, turn it off; walk away and procrastinate. With a tutor however, that never happens; there is also personal connection, and the tutor constantly adjusting what you're learning. I am definitely optimistic about AI-learning and tutoring, but really have a hard time seeing it as replacement.
Whenever I see the new releases around video generation (and image) generation models, I get goosebumps, because it just feels so fun to work with them. But then I remember that I spend upwards of $10k on inference generating well over 50k images for storyboards, training models; and probably creating almost an hour of video (I assume). Yeah, I get that things can be economic if you don't use the latest models (ran some case studies on this), but the latest models are the most fun to work with. It doesn't scale as well as "vibe coding" stuff together on the weekend. And when things work really well its almost as if you're seeing an zoopraxiscope come to life for the first time; and you just want to keep going.
I got a few offers to work with some startups in this space, but it also seems that many startups work on stuff that just doesn't seem to be very worthwhile (like creating masses of spam for YT or TikTok shorts), or even straight out morally/ethically wrong (cloning/deepfakes, etc). But seeing advances in this space; and coming from a filmmakers background, I might just end up being naturally drawn to this space on an engineering level and figuring something out along the way. As you can see I worked on a lot of stuff just for the fun of it, and documenting the process: https://edwin.genego.io/blog (but I stopped at the beginning of the year .... might.. just pick it up again.
I went to Art Center for film. Loved it. But ended up writing software instead of shooting movies (while still also handling a lot of visual art direction, graphics work, UI, 3D animation, etc). Now I feel like we're starting to be roughly in the same boat as far as using prompts.
What bothers me is that every piece of content generated this way helps flood an already saturated market for content, while slowly degrading the expectations of what people see, to the point that no one will bother with shooting or animating anything anymore. Even if it's 50% worse, it's 90% cheaper, so the economics argur against producing any new physically made content. Simultaneously, it's cannibalizing all existing content. This points toward a feedback loop, like a snake eating its own tail. And even though Hollywood blockbusters have followed that pattern for a couple decades, it's demoralizing to me to see it enshrined as the future of film (or to hear from someone who makes films that it would be a preferred mode of creation).
> Even if it's 50% worse, it's 90% cheaper, so the economics argue against producing any new physically made content.
That is an unfortunate pattern I fear is become applicable to a lot of domains (film, software, food, clothing, built environment, electronics, physical goods et al). AI is just accelerating that in a few.
I feel these tools are destined to be mostly used as content generators - I'm happy to be proven otherwise but they've been around a while now and aside from a few pop videos I've not seen stuff that seems to be infused with the outer edge of quality art direction - perhaps because the model data limits it or perhaps it's the way they're used.
MiniMax H3 is going to release weights. You can locally run it with definitely less than $10k (and possibly faster than Seedance's queue), and it's fun to train it for whatever you need.
Perhaps refined ComfyUI workflows will squeeze more quality out of it, but it's definitely not in the realm of Seedance, and Lightricks is training LTX 2.5/"LTX-Next".
Note: Those results are a little misleading the good LTX results were generated with a good workflow in ComfyUI, and a prompt expanding local model.
Whilst the H3 result was generated with the raw api using his raw prompt.
If you ask ChatGPT or other AI model to "improve" your prompt (with cinematic, good lighting) generally, you will get also very good result from H3 also.
My own H3 test show that H3 (API edition) is undoubtedly better than LTX in prompt adherence ! The real comparison will be with the edition of H3 we get to run locally.
Awesome! Have been a bit in the dark of the latest models, will have a look. I am due an upgrade for my local machine and GPU, so that excites me as well.
I've been dabbling in this space on the application layer and have spent a few hundred myself experimenting with video models.
It can be really entertaining/addicting to build with them because you're essentially pulling the slot machine and having TikTok/Marvel/YouTube come out of it. I think that was the bet with Sora but the problem is mostly that the novelty wears off quick, and most people want to just consume content without typing in what content they want to see, or sifting through mass-generated spam "content" with nothing behind it to make it worthwhile (a lot of people engage with content parasocially)
Once the tools for creators to steer and integrate models in this space get better, it will explode. We've been working on what I think will be one of the first use case for integrating these models, because I think we're approaching a middle ground where they can be integrated in experiences to provide entertainment/engagement/fun experiences without feeling like slop.
Btw, I'm impressed with some of the AI content on your site but I think you might want to pare down the non-demo pages because it has a different impression me (can I trust that this text is true? / I'm reading a lot of words but not really learning about this person) than you might have intended). I'm a bit of a hypocrite here but also speaking from experience.
Thanks for the input! And no I agree with your assessment of the website, I have some plans of a much simpler redesign soon, and I definitely value that critique. I think my "digital garden" has been through at least a few dozen of iterations, and sometimes I just get too carried away with it. The good part being, the next iteration always starts out better than the previous one (or at least I hope so :)).
It is (mine)! And there is a purpose to it looking AI generated. However, the sample projects where actually fully worked on; mostly as hobby projects. I will have it go through another iteration of improvements soon. This may be the 10th version of the website, since maybe 2012-2014, I did have different domains since then. But the concept of using it both as a creative and professional outlet stays alive.
Ask someone for feedback on your website. To you it might look ok, but to me and I think many others, it is unintelligible. I have no idea what I'm looking at and it is impossible to parse.
That is the primary issue, and secondarily it is a cookie-cutter AI slopfest that will make any technical person not submerged in Kool-Aid click away.
Please just get your AI to follow some basic UI best practices or pick up a UI library.
Thanks for the feedback, appreciated! Yes its due an overhaul, but a large part of the purpose of this website is going through experiments as a digital garden and having a creative outlet, I am fully aware how it looks, but there is a part of me that needs it to go through the process of looking as sloppy as possible. It's likely going to end up going through its nth iteration very soon, and then another one after that. I do run and maintain (for clients/myself) many websites that look nothing like this.
SEEKING WORK | Senior Django/Python Web-developer & AI Engineer - Platform, Architecture, Ops, Applied AI
Location: Thailand (UTC+7)
Remote: Yes, and available for hybrid arrangements in Thailand.
Technologies: Django, Python, PostgreSQL, Redis, Celery, HTMX, Tailwind, Docker, APIs, RAG/MCP
Resume/CV: https://edwin.genego.io/about
Email: edwin@genego.io
Senior full-stack Django/Python engineer for founders and lean teams that need platform, product, architecture, and ops ownership. Django has been my daily driver since 2018. I build production web platforms, MCPs, APIs, integrations, internal tools, document/data automation, and AI-enabled workflows. Recent R&D: generative image/video pipelines, Lora training, multi-model orchestration, prompt architecture, and repeatable creative AI tooling—but the broader pattern is platform engineering.
Open to fractional or project-based work, especially 2-6 week focused cycles with startup founders, cofounders, agencies, or product teams. Next to client work, for the past 2 years I have been busy building and experimenting with agent harness systems (before it was cool) and Gen AI video automation, orchestration and model training. You can read about that here: https://edwin.genego.io/blog - https://edwin.genego.io/projects
Why does Railway deserve any blame here at all? It was an MCP with elevated infra access, that the user willingly connected through Cursor, which allowed an LLM Agent to manage infra on Railway. The user would first have gone through oAuth confirming the access level scope (I would have rejected the moment it indicates to me that it can delete critical infra and backups...). So obviously it has access to all commands the user would also have access to. From my perspective the blame is entirely on the user, and partly on Cursor for not enforcing HITL correctly across their agents.
Putting AI aside, people make mistakes. One of the most common mistakes people make is deleting the wrong thing. After they realize the mistake, people want to restore the thing they deleted from backups. Thus deleting the thing and deleting the backups of the thing should always be separate operations.
Senior full-stack Django/Python engineer for founders and lean teams that need platform, product, architecture, and ops ownership. Django has been my daily driver since 2018 — I've only worked with Django-native startups. I know the framework deeply: ORM, migrations, admin, middleware, signals, async, deployment. I build production web platforms, APIs, integrations, internal tools, document/data automation, and AI-enabled workflows. Recent R&D: generative image/video pipelines, Lora training, multi-model orchestration, prompt architecture, and repeatable creative AI tooling—but the broader pattern is platform engineering.
Open to fractional or project-based work, especially 2-6 week focused cycles with startup founders, cofounders, agencies, or product teams.
I keep having this conversation with clients. If you want to allow an LLM to delete, create or update data; you need to do this with a human in the loop, and explicit hitl gating against execution; where the agent can't even call the tool without triggering an update on the UI that has to be confirmed (then the confirmation issues the actual tool call).
I am a well-seasoned software engineer; who grew up with a hackers mindset. I am currently exploring create AI tooling around image & video generation pipelines, multi-model orchestration, prompt engineering systems and cost-optimized workflows. I am currently looking for a startup or agency interested in working with me; as I have availability coming up in the next few months. I have 10-Years of experience (full-stack) mostly with Django, Python & Tailwind. I have most of my work outlined on my website.
Sr. Software Engineer building production Django apps with practical AI integration. I specialize in creative AI tooling , image generation pipelines, multi-model orchestration (Flux, SDXL), prompt engineering systems, and cost-optimized workflows. Current work: 20+ custom management commands for AI image generation, character IP systems, scene replication with layered prompt architecture. I help teams ship AI-powered creative tools without risky rewrites, handling multi-model workflows, resume-capable operations, and obsessive cost tracking. Looking for fractional or project work (2-6 week cycles) involving generative AI, creative tooling, or content pipelines.
Whenever I saw people complain about LLMs writing code, I never really understood why they were so adamant that it just didn’t work at all for them.
The moment I did try to use LLMs outside of Django, it became clear that some frameworks are just much easier to work with LLMs than others. I immediately understood their frustrations.
LLM is the fad of the day, and these sort of articles provoke the natural get-rich-quick-greed inherent in all of us, especially the young tech-types. As such they are clickbait, and also a barometer of the silliness that is widespread.
I am curious why re-reading incerto sharpens your bullshit sense. I have read a few in that series, but didnt see it as sharpening my bullshit sensor.
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