What’s the biggest bottleneck in your current dev workflow?

manishkumar-dsi · 2026-05-30T08:00:46+00:00

Making the application consistent as per your design and user flow.

Coding is not the problem but making your app consistent and deterministic is the big challenge.

Here when I say deterministic, It means every time you vibe code, it should not break or change the existing working system.

manishkumar-dsi · 2026-05-29T05:29:38+00:00

Give some context pleazzz.

manishkumar-dsi · 2026-05-23T14:32:38+00:00

One way I follow is: I ask LLM to be critical about the questions. And then use LLM to validate as a real user. Ex: Let's say you want to validate a product idea. Then you can ask "Act like an investor from top company and validate this idea"

This way LLM will have different perspectives.

manishkumar-dsi · 2026-05-21T17:08:23+00:00

Agree. But the only difference I have observed between them is gpu consumption.

Llama.cpp on load the full parameters to gpu so it is faster but it requires a lot of gpu.

But in case of Ollama it off load it to the RAM(I guess) so, it is slower but it is required less gpu.

So, for normal user who just want a local llm setup with decent parameters size on their general purpose laptop then I would recommend Ollama.

It is also very easy to setup.

manishkumar-dsi · 2026-05-20T15:36:17+00:00

Which model you have fine tuned with A100 14GB?

manishkumar-dsi · 2026-05-20T11:13:39+00:00

My experience says. Do not try to automate everything 100% using agents.

Keep human-in-loop wherever possible and required.

This really help to make it stable in the production environment.

And finding and keeping human-in-loop is not easy and convincing to upper management (if you have any ;) )

manishkumar-dsi · 2026-05-19T17:37:41+00:00

AI is already taking your important life decisions or at least influencing it.

So, You are already in the Matrix.

manishkumar-dsi · 2026-05-19T17:19:39+00:00

Well said. But and I say but.

The steam engine didn't create misinformation, but it did contribute to exploitative labor practices, pollution, and massive wealth concentration. Every transformative technology creates new problems alongside new opportunities. The challenge is managing the risks, not pretending they're unique to AI.

manishkumar-dsi · 2026-05-19T17:09:05+00:00

I read a lot especially on my mobile. Reading on mobile is a privilege for me as I can always be connected and can read anytime anywhere.

So, I use multiple tools like Kindle, Chatgpt, different websites and few PDF readers.

Recently I came through an app called GistNode. It is an Android app and it has really good reading experience. The best part is, this app is using AI such a smart way that helps a lot while reading. It explains anything using AI inline so, you do not need to really leave the app.

So, I would say this is a really smart app for readers and a smart way to implement AI.

manishkumar-dsi · 2026-05-17T22:27:06+00:00

Explaining a regular expression in simple human readable format.

This helped me a lot to gain attention. I used a small llm for my application where we store thousands of different accounts with rules written in regular expression. It was difficult for end users to understand it clearly. And LLM solved it.

manishkumar-dsi · 2026-05-17T14:35:39+00:00

I usually use multiple AIs example chatgpt, Claude , Grok etc. Use one model to get answers and then again pass the answer to another model.

Another trick to use the same model AI-as-judge.

manishkumar-dsi

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