ramshanker

Yes. Waiting for the Windows Version myseflf. RTX Spark Desktop.

I hope it brings the RAM prices down!

Same here. Late to agentic party. 1st month was Codex, 2nd Claude, already thinking 3rd will be Codex again! Since Fable will be gone soon.

For me the Best Pros is "That one random-internet-comment is a good usability improvement, ask LLM to do the small change and commit immediately."

Smaller ideas need not be approved, or held back by schedule pressure from bean counters. Just Do It. :). It's the small corrections which end up polishing the product as good as "professional usability studies".

If they release a model comparable to OpenAI / Antropic, will there be any reason left for 1T valuation of other companies? At that point, it will simply become Revenue proportional to Gigawatts available. Whoever got the energy wins.

I can count 2:

Dec 2025: We use a commercial 3D modeling software to build refinery. There was no license dashboard in this ancient piece of junk. Fortunately license server provided verbose live status report through a command line. I ask ChatGPT to ingest the logs into a Django web application and generate weekly/monthly/yearly usage dashboard, and It one shorted the whole Backend + Frontend in 4 to 5 shot. There were around 10 regexes just in the log parsing batch script. I was totally speechless. Encouraged by the success of, I went ahead and made the dashboard for 3 more software in the same Django app. Released to peers by evening, feedback incorporated in 2 days to integrate Name, Employee Number, IP Address sync etc in 2 days. And it’s been live for 5 months, actively being used by all coadmins, even management has it bookmarked, to help with department redistribution. Making this thing without AI would have taken well over a month of “learning new stuff”, or paying external consultants too much. Even head of IT replied back, it was awesome. ;)

2nd , June 2026: I asked codex to something fairly complex before going to morning bath!, which would have taken me more than a week of learning DirectX12 API nuances and such things, 20 min latter, I return to task exactly completed with code changes in 5 different files. Build complete without any error. OMG. Free Quota over for whole month! I subscribed by the evening.

Once someone taught me "you can do xyz reading a book, but you cant do surgery by reading a book". Now replace the book with LLM. This is what "domain expertise" look like for some domain.

Agree on this one. As a Civil engineer, I can smell which software ( or some part of) was developed by computer engineers without much understating of the "domain". The worst offenders are software needing multi-domain expertise in the first place. Crude Ex. Payroll (Finance) and Leaves (HR) are 2 seperate domain, and they need to account for each other.

Guess we can run this even on CPU!

With the new agentic capabilities, I am quickly running out of Architecture decisions I have already made myself! For my work-in-progress engineering application. There is also some kind of don't know every little if/else with my own Code now.

However the good part, what I had planned for 5 years, now looks like doable in 6 months. Looking forward to real use by the end of this year.

Ref: https://github.com/ramshankerji/Vishwakarma

Thank you for the insight. This makes me feel confident, the L40S we are about to acquire with 48GB VRAM for engineering application should be useful for agentic coding as well.

I wish it offered a windows binary as well, since the original project gitea from which it was forked, does so.

Sometime you need to go where many customers ahem enterprise are.

As a developer of an engineering application, windows is the way to go 1st hand. It would have been easier to adopt one more application on the daily driver enviornment. Till than, I am on GitHub only.

This is the best publically posted model size, ever since top AI labs started treating model size as a trade secret. This should also guide next generation of inference ASICs.

Building blast resistant is a common practices for Refinery control rooms. The same methodologies can be employed for data centers as well.

1 blast can be expensively guarded againt. However designing anything above ground for sustained barges is practically/commercially prohibitive. Underground is only option.

PS: Civil Engineer. Designed few of those Gas explosion resistant control rooms.

Anther perspective, AI is fast turning [0.1x to 0.5x] low cost X-world Sofwate Engineers into >1x engineers.

Contrary to pre AI era, one of my close relative he has become very good "understand / write the requirement" guy. HN may be dominated by >1x engineers, another revolution is happening at lower /bulk end of spectrum as well.

Same approach as mine. :)

One more thing I try is give same prompt once in a while to ChatGPT/Gemini/Grok. Than take the 2 out of 3 ideas forward.

All leading AI seems to have some blind spot. Like some kind of intricsic character. 1 will completely overlook some particular bug while finding other excellent bugs and edge cases.

Getting the code through all 3 before commiting has shown excellent results to me.

Currently working on C++ DirectX12 graphics engine of my Engineering / CAD software. Part of my Mission Vishwakarma 2035.

https://mv.ramshanker.in/

Github: https://github.com/ramshankerji/Vishwakarma

>>>Hey, I'm nearly 80 years old.

You are an inspiration. I will remember this when I grow older. Just wanted to say this, I am 1/2 your age, and I am sure there are 1/3 or even 1/4 people here. ;)

I can imagine, where this becomes a mainstream PCIe extension card. Like back in days we had separate graphics card, audio card etc. Now AI card. So to upgrade the PC to latest model, we could buy a new card, load up the drivers and boom, intelligence upgrade of the PC. This would be so cool.

I was all praise for Cerberus, and now this ! $30 M for PCIe card in hand, really makes it approachable for many startups.

As I said, all these are optimized for Mechanical engineering, to the best of my knowledge. In civil, there are lots of standardization in 3D part and a lot more focus on 2D side. Major part of building design is using standard steel section. Mechanical side, apart from nut bolts, everything seems to be custom. Software interfaces prioritize these use cases.

Think of I beams, all major countries have national standards of shapes and sizes. There are many "devil in detail" nuances.

So, giving it a go myself. If not for others, at least for my own itch. This is one aspect of open source.

3 days late clarification: It is for personal projects! Not for sumbitting pull requests to established projects.

I will try the newer version again. Last I tried 2 years or so back, it was crashing for me.

Personal Context: I am a civil enginer, and our requirement from CAD softwares are a lot simpler than Mechanical Engineering. Here on HN, whenever I see people discussing CAD, its the mechanical version of parts and 3d printing.

Shameless Plug: I have decided to try building my own! Over a long enough timeline, it is doable, including the UI/UX part.

https://mv.ramshanker.in/

At least for me personal open source project[1], it has been >5x boost. In speed, motivation. Operating knowledge level etc. At some places, I even put inline comment, "this generated function is not understood completely" ! Or may be a question on specific syntex (c++20).

[1] https://github.com/ramshankerji/Vishwakarma/

At least xAI now has a revenue generation backer. SpaceX.

Others must pull up their revenue number.

Do we get any model architecture details like parameter size etc.? Few months back, we used to talk more on this, now it's mostly about model capabilities.

Not just that, previously many orgs outsourced to consultancy, now when the consultancies also start outsourcing to AI, sooner all business may cut the middleman and have inhouse it teams outsourcing work to AI instead of consultancies !

Thank you for shaking me once more .....

This year: DirectX12 documentation. Lots of them. Harry Potter part 7 (again). Read Part 1 and 2 to kid.

Is there anything preventing incumbents from developing their own ASIC equivalent of a google TPU?

Or maybe the GPUs are not really that different from TPU.

To me, one of the secret sauce of AI chips is Memory amd Interconnect bandwidth. Memory everyone is using the same HBM series. No difgerentiation. Multi chasis Interconnect is already not bottlenecked vs compute. So GPUs aren,t any worse.

Ammuter Guesswork!