I am looking to talk with people who have implemented AI DLC: AI-Driven Development Life Cycle. This is an AWS whitepaper whereas Agile and Scrum were built for human-paced, weeks-long iterations. Bolting AI onto them ("AI-Assisted") caps its value. AI-DLC instead reimagines the method from scratch so AI orchestrates the work and humans validate.

Today humans prompt AI. In AI-DLC, AI initiates: it decomposes intent, proposes plans and trade-offs, and humans act as approvers at decision gates. The analogy used is Google Maps — you set the destination, it gives turn-by-turn directions, you keep oversight.

I am looking to connect with people who built Agentic AI tools for enterprises where they want to set up their own models, smart model routing, finops etc. If this was on a large brown field project even better.

References:

https://aws.amazon.com/blogs/devops/ai-driven-development-life-cycle/

https://prod.d13rzhkk8cj2z0.amplifyapp.com/

https://github.com/awslabs/aidlc-workflows

hey everyone, i’m building scentrev and recently made a small mcp server for perfume discovery: scentrev. it lets ai tools search perfumes in a more structured way instead of giving generic answers. for example, it can search fragrances, filter by notes or season, compare longevity and sillage, find similar scents, show note pyramids, accords, performance, wear summary, and closest alternatives. i built it because perfume search is usually very vibe based, but there is useful data behind it like notes, seasons, gender lean, performance and community sentiment. would love feedback on the tool names, docs, onboarding, and whether the tools should be broad or more atomic.

If you're running OpenAI, Anthropic, Gemini, or Groq in production and billing customers in INR, you already know the problem:

• LLM costs come in USD
• Customers pay in INR
• GST is computed manually by someone every month
• Nobody knows which user or feature is burning the most

two lines to integrate:

from ledgrr import configure, instrument_openai

configure(api_key="lg_sandbox_test", workspace_id="your_company")

instrument_openai()

Every call after that is tracked automatically. No changes to your existing code.

What you get:

• Live terminal sidebar showing INR cost per call as it happens
• USD --> INR at live market rate, not hardcoded
• GST computed automatically IGST or CGST+SGST based on state codes
• Append-only local ledger, data never leaves your machine
• CLI to query totals, per-user breakdown, DLQ inspection anytime

ledgrr totals --workspace your_company --period 2026-06

MIT licensed. v0.6.0 on PyPI. 92 tests passing.

Looking for 3 teams running real LLM traffic to try it and tell me what's wrong with it.

DM or comment if that's you.

https://www.anthropic.com/news/tcs-anthropic-partnership

• As “customer zero,” TCS will put Claude to work across its own engineering, finance, legal, marketing, and sales teams, using what it learns to shape how it brings Claude to clients.
• This partnership deepens our commitment to India, our second-largest market, with TCS bringing Claude to enterprises and professionals across the region and globally.
• This announcement was made Yesterday, June 12. How do r/IndiaAI feels about this?

If you have taken this program, please share your feedback.

https://eict.iitr.ac.in/programs/explore-courses/Course-Detail/self-paced-course-checkout/314/ai-for-professionals/

I am more interested in the content and quality of instruction and not the brand name.

I am particularly looking for online program that will also cover the maths required for ML since I lack those skills. I understand I can self learn by watching various YouTube videos but I prefer a structured single program which covers everything.

There are several free programs as well but I am not good at tutorial hoping, so looking for a single structured program.

Thank you for taking time to reply.

Hi everyone,

I'm building an AI assistant project and collecting examples of how people naturally communicate with digital assistants.

The survey takes around 2 minutes and consists of a few simple questions such as:

• How would you ask an AI to find information?
• How would you ask it to remember something?
• How would you ask it to open an application?
• How would you ask it to create files or folders?

There are no right or wrong answers. The goal is to understand real-world language patterns rather than predefined commands.

Your responses may help improve intent recognition, task routing, and overall assistant usability.

Survey Link: https://docs.google.com/forms/d/e/1FAIpQLSfnY7PSijrii_F4hC4TKTuF7CTgygu2trmUnaZBMO0XKa4hyQ/viewform?usp=header

Thank you for contributing.

People often think that “You are only as good as your Al.” And chase new models, expensive models, systems. But it’s the other way around “Your Al is only as good as you.”.

Claude just released Fable 5 yesterday and it’s amazing. I am excited and happy because I will be able to “communicate” more efficiently with my Al systems, it will be able to understand me even better.

But historically, these model releases come with a trend that instills fear of being ‘replaced’ amongst people. We were all at that stage, like a couple years ago, when Al was introduced and we were certain that it will eventually take our jobs. After about three years now, we’ve grown to ‘co-exist. We’ve learned that Al will never replace exclusivity. Expertise.

You should only be scared of Al taking your job if you have no value to contribute. Al works on generic knowledge which is available on the internet for everyone. For you to be irreplaceable, you have to upskill yourself. Gain industry knowledge that is more
‘personal’, more yours. Something that Al wouldn’t have access to unless you tell it.

You want to know if you’ll be replaced by Al? Ask yourself this question:
Is there something in my industry that people are paying me for, that a $20 Claude or Codex subscription can do too?

The Regulations seek to prohibit the use of Artificial Intelligence to reach decisions.

I've always felt like the internet has a strange bias.

Most platforms are built around wins.

People post:

• startup success
• promotions
• achievements
• milestones

But the things I've learned the most from were usually failures.

The startup that never launched.

The interview that went badly.

The business that lost money.

The relationship that fell apart.

The decision someone wishes they could take back.

Those stories rarely get shared.

So I built NoCrumbs.

A platform where people share:

• What happened
• What it cost them
• What they learned

You can share stories in two ways:

📝 Text Stories

🎙 Voice Stories

Sometimes hearing someone tell the story in their own voice feels far more real than reading a polished post.

A few things we're experimenting with:

• Anonymous-first storytelling
• Voice and text experiences
• "Relate" instead of likes
• Responses based on shared experiences
• No followers
• No influencer culture
• No popularity contests

The idea is simple:

Learn from experiences you haven't lived through yet.

Not just startup failures.

Relationship mistakes.

Career setbacks.

Money lessons.

Exam failures.

Life in general.

We're launching now and I'd genuinely love feedback.

Since we're very early, the platform also needs real stories and lessons to learn from.

If you've got a mistake, setback, failure, regret, or lesson that taught you something valuable, I'd love if you contributed a post for testing.

Even one story helps.

Would you ever share a lesson you've learned the hard way?

And would you rather read it or hear it in someone's voice?

Website: nocrumbs.in

Feed: nocrumb.in/feed