CS @ NIT Trichy | 25k+ Views on YouTube | building AI products that scale in production | Sharing my journey & lessons (raw & unfiltered)linktr.ee/keyashqa BangaloreJoined September 2024
@ishaangodhaa Congrats Ishaan. Currently, I am building myself. Getting rid of all those social fears, bringing back my mental peace. Along with that, I am building production grade agents for scaling.
That coffee cup looks soo dumb for it's shop's aesthetics.Use claude design a better cup, with a good lid and straw. Make some good starbuck references, some good space to write customer name on it and build the complete design with the company's logo and colour palette. Sell the design to the coffee shop for $ 20k.
And, give me $10k for the idea(just kidding 😂)
I solved somewhere around 270-300. Then, I felt DSA as purposeless. So, dived completely into Agentic AI, just with my resume, got shortlisted for Interview. Interview was easy peasy, completely about projects. So, got in. Now, working on building prod grade agents end to end inc. deployment. So, yeah...DSA is to check how well you fit into the employee mindset. That's my pov, not to harm anyone who is preparing it.
@googledevs A2A is of not much use. It is just a basic Agent card to identify an agent.
The extensions in A2A like UCP, AP2 and other customizations make A2A much much powerful and that's why, it is being loved by devlopers.
A2A without extensions wouldn't have lasted long fr.
By analysing the trajectory of LLM thought process, and keeping the evaluation for each tool call and its order instead of just evaluating the final output.
The main reason for hallucinations is either too much or not sufficient context.
By this way, you can reduce and control hallucinations.
Exactly, people build their product, then search for users. But, it is always the vice versa. And, I am preparing to do podcasts with multiple industry leaders to know about their problems, which helps builders to find the right pain point to solve for.
Can I connect with you to talk on this.?
You can save one week if you are building production grade agents.
Here you go:
Just shipped a production AI agent to Google Cloud in under an hour. No Terraform. No Dockerfile. No FastAPI boilerplate.
One tool did all of it: agents-cli
scaffold → playground → deploy. Vertex AI Agent Runtime, IAM, telemetry, evals — all generated for you.
Command:
uv tool install google-agents-cli
If you're building agents on GCP without this, you're doing it the hard way.
Testing code in a sandboxed environment is very simple than I thought:
1/
Run git init and configure local git credentials inside the project folder without the --global flag.
This forces the agent to use a fake profile ("Kaggle Student") so your real GitHub identity/email never leaks.
2/
Force the agent to create and work strictly inside a brand-new folder (~/secure-agent-lab).
This sets a hard operational boundary, keeping the agent's file system scope isolated from your personal documents.
3/
Use uv to spin up a blazing-fast Python virtual environment.
Any dependencies or broken packages the agent installs during runtime are trapped here, keeping your global system immaculate.
Simple, logical isolation before you let an agent touch your code.
I hope this helps any beginner to code securely.
@dev_maims They can't even if they want to.
If they did, US would impose anti-trust against Google. That might lead to splitting of the company, similarly to how Standard Oil got splitted into 34 smaller ones.
This has done to rationalize the monopoly and to give chances for others.
If anyone in any industry doing any work that feels even slightly repetitive, Please read this out :
I build Agentic Workflows to aid the boring part of any professional's work.
If you could kindly help me by a small walkthrough with your work, I would love to make it automated for you without much human intervention.
I am actively into building production grade systems. And, I won't be charging a single penny for this. I just want to work closely with Industry Professionals to help them by understanding the problem by leveraging AI wherever possible.
If you know someone who could be benefited by this, kindly let me know.
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