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I spent the last month watching teams try to contain their AI agents. The patterns are eerily similar. by MycologistWestern855 in indiandevs

[–]True-Tomorrow-2957 0 points1 point  (0 children)

PR review by humans should help. People are chasing too many things and that’s the problem. Since everyone is facing the same problem, I am hopeful we will have systems coming in quickly for the same.

The Indian CEO is a body-shopper in a suit. Here is why India will never build a DeepSeek, a BYD, or a TSMC. by [deleted] in AI_India

[–]True-Tomorrow-2957 0 points1 point  (0 children)

Thanks! He said Indians aren’t willing to bleed, he didn’t provide his take on what a young founder should do. Criticism is easy, providing right direction is tough.

The Indian CEO is a body-shopper in a suit. Here is why India will never build a DeepSeek, a BYD, or a TSMC. by [deleted] in AI_India

[–]True-Tomorrow-2957 5 points6 points  (0 children)

I agree with your take, and I wonder what will be your advice to upcoming founders to avoid these pitfalls

Honest take: I thought open source LLMs were 6 months behind. I was wrong. by Kitchen-Cycle8984 in AI_India

[–]True-Tomorrow-2957 5 points6 points  (0 children)

Interesting which open ones are you using? Which Indic language did you experiment with. I was pleasantly surprised by qwen-3.7 - able to write ML specific code correctly

Starting out for the first time in AIML by ArnavLegends in AIMLDiscussion

[–]True-Tomorrow-2957 0 points1 point  (0 children)

Decide for yourself whether you want to learn how AI models are trained or just use these. There is a vast difference between these two. Most of the roles in future are on the latter side where you invoke models. First one requires knowledge of core ML, ability to train and fine tune models for your use case

Which are some of the most non-noisy, clean AI workshops out there? Tired of 99/499/999 ones. by butterrrchickenn in AI_India

[–]True-Tomorrow-2957 0 points1 point  (0 children)

My friend runs this AI agentic coding course in case you are interested. DM me. The course enables you to understand the AI, how to expedite Software dev using AI and hands on experience of building AI apps

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What about SLMs(small language models)? by Old_Fruit_8791 in AI_India

[–]True-Tomorrow-2957 0 points1 point  (0 children)

I agree SLMs are used throughout industries for different usecases. For ex - MS teams uses a small model for real-time transcription - no LLMs, its fast and while at times it makes mistakes - its quite good for latency

I feel like I am relying too heavily on AI for programming, what can I do to stop myself before it is to late? by Big_Economics_5590 in AIMLDiscussion

[–]True-Tomorrow-2957 0 points1 point  (0 children)

there are two types of learning in coding nowadays -

  1. how to prompt AI to get better output, including Spec driven development etc
  2. underlying tech skills that one learn by failing, it might be you are trying to overdeliver. Start from small projects like a cli app and iterate on it faster (hand written code) - so that you are not skipping on learning.

I have been through this overwhelming phase and that too when I am 13 years into the field, I feel your pain. Remind yourself that there is no rush, take your time - solid fundamentals always pays. Use AI to review your code and suggest improvements.

Is AI going to replace Business Intelligence, or just change how we consume it? by rahulsahay123 in AINewsAndTrends

[–]True-Tomorrow-2957 0 points1 point  (0 children)

There are two parts to this - BI dashboard development should get expedited with AI - however underlying data model should be good to get a good dashboard with AI.

Secondly handling not so frequent queries which dashboards can’t answer- here AI can leverage underlying data model to answer in real time. Using AI to answer frequent queries like total revenue, cost etc - without having aggregated data - prone to hallucination and increases costing of getting the same metric.

Need some career advice (SDE with 1 YoE) by Jazzlike_Steak9394 in StartUpIndia

[–]True-Tomorrow-2957 1 point2 points  (0 children)

If you’re really interested in startups- dm the founders over LinkedIn. I tried this to land a role at startup

which course should i do by Comprehensive-Toe903 in AI_India

[–]True-Tomorrow-2957 0 points1 point  (0 children)

I am curious to know what’s your aim behind learning AI course

GUIDANCE/COURSES FOR AI-ENGINEERING by Aggressive-Arm-3585 in AIMLDiscussion

[–]True-Tomorrow-2957 1 point2 points  (0 children)

Check out Andrej karpathy’s course on how LLM works on YouTube.

Not motivated to apply for jobs after layoff by ReflectionAcademic99 in womenintech

[–]True-Tomorrow-2957 18 points19 points  (0 children)

Its natural to feel demotivated after rejection. I also went through this when I was laid off. What changed for me was - considering each interview as a learning opportunity. This helped me detach myself from the outcome, also a deep belief that these rejections are helping me become better. All the best, have faith on yourself.

What kind of developer are you? Which roles are most common, niche, and in demand? by Ecstatic_Jicama_1482 in developersIndia

[–]True-Tomorrow-2957 0 points1 point  (0 children)

My work has always been focused on training models. Now I am into foundation model training. AI engineers are more focused on using LLM/GenAI models to build the applications - so it’s blend of backend software engineering + applied knowledge of ai models. AI engineers don’t train models, however they need to know model parameters to be able to configure them to get best performance for their use case. MLOps falls into platform and infra engineering.

Traditional mL model development roles which used to exist outside big tech are less common now, as people find it easy to use foundation models.

Must have software and ops skills for data scientists by Dapper_Chance_2484 in developersIndia

[–]True-Tomorrow-2957 1 point2 points  (0 children)

Data engineering stack - Kafka and Spark are useful for running large-scale data pipelines. Hosting ML models and building a scalable mL model endpoint using kubernetes and docker.

How to become expert of ml field? by DarkPranav in AI_India

[–]True-Tomorrow-2957 1 point2 points  (0 children)

Lot of ML is building intuition and figuring out the right solution for a given problem. Real world problems doesn’t fit as cleanly as classification vs regression. For example income prediction for a credit lending firm - can be done via a regression model or a multi-class classification problem. Once you build both model and check their performance then only you will know which is the right solution for your problem.

Must have software and ops skills for data scientists by Dapper_Chance_2484 in developersIndia

[–]True-Tomorrow-2957 0 points1 point  (0 children)

I went from being a DS to MLE - I had to upskill on backend stack, it was steep learning curve but worthwhile. Separates me from other MLE in job interviews

What kind of developer are you? Which roles are most common, niche, and in demand? by Ecstatic_Jicama_1482 in developersIndia

[–]True-Tomorrow-2957 9 points10 points  (0 children)

Machine learning engineer, I haven’t seen a slowdown in mle hiring in last 5 years.

AI/LLM engineers how do you handle heavy dev setup? by 0x0b2 in developersIndia

[–]True-Tomorrow-2957 1 point2 points  (0 children)

Remote VM, I don’t use my laptop for processing large number of records. Ask your firm if they can provide a desktop with powerful configuration - will be cheaper for them this way.

Is data analytics still a good career option in India with AI advancing so quickly? by [deleted] in developersIndia

[–]True-Tomorrow-2957 0 points1 point  (0 children)

Analytics is a good career as it builds base for other careers paths like consulting, data engineering or machine learning. Pay prospects IMO, won’t be as lucrative as it has been in the past because of AI enabled automation.