Digital Customer Success @Alteryx | AI • Cloud • Data • APIs | Building tools, learning in public, and helping customer-facing teams become more technical.
India
Joined March 2012
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I built this as a personal project for anyone preparing for the ☀️Claude Certified Architect – Foundations exam. 🎓
Free to use:
✓ Practice questions
✓ Progress tracking
✓ Topic review
✓ Resume anytime
Try it → prep.aniesh.com/
Aniesh Kumar retweeted
If there is one tool that almost everyone at Razorpay uses, it has to be this one. And today, we are open-sourcing it :)
Almost every document we create is AI-generated (vetted by humans, ofc), and we have effectively replaced Google Docs with this tool. Why?
Because the documents look soooo beautiful, are interactive, and this just makes the whole experience of reading so much more enjoyable.
We have been using it internally for quite a while now, and today we are finally sharing it with the world.
Give it a spin :)
AI agents are changing how we work and collaborate, but documents are still stuck in the pre-AI era.
Agents can now create beautiful, interactive decks, dashboards, and reports in HTML. But the moment you want to collaborate on them, everything breaks down.
Google Docs wasn’t built for rich, interactive HTML or AI agents. Feedback gets scattered across Slack and email. Every edit means going back to the agent, generating a new file, and sharing another link. No real-time collaboration. No single source of truth.
We built SlashDocs to fix this.
Think Google Docs, but built for AI agents and the documents they create. Host HTML and Markdown in one central hub. Share documents, manage permissions, and comment directly on the content, just like Google Docs.
Agents can read feedback and update the same document in real time. No duplicate files, no endless back-and-forth, and everyone stays in sync.
What started as a small internal experiment in one team has now scaled across @Razorpay. 28,000+ documents created. Over 50% of all documents generated at Razorpay now live on
SlashDocs.
And today, we’re opening it up to everyone. Self-hosted. Agent-agnostic. Fully open source.
AI agents have changed how we create documents. It’s time we changed how we collaborate on them.
Try it: razorpay.com/slash-docs/
Aniesh Kumar retweeted
Alexandr Wang on Why Muse Had to Break Through the AI Noise
"It's a pretty torrential stream of updates... here's another model, and here's another product, and here's another feature."
"We need to break through. Meta, we have lots of distribution, but that's not enough to make it break through in an interesting cultural or fascinating way for the world to pay attention to." — @alexandr_wang
Aniesh Kumar retweeted
Congrats to Meta for training a frontier-grade model! Watermelon compares favorably to Fable 5.1 on WANDR evals.
Aniesh Kumar retweeted
Great to be with 700+ @googlecloud customers at the historic NASA Hangar One for Gemini at Work!
Today, we introduced the new Gemini agent, a single, universal agent for work that has all of your business context and answers your questions, handles your knowledge work, creates your images and media, and writes and runs code - all from a single prompt box. It is connected to your personal workflows, your systems of record, and your enterprise controls.
It’s built around a few core architectural principles:
Unified Agent: Gemini can answer questions, do knowledge work and generate code from a single prompt box.
Access: Gemini is web-based and can be accessed from any device and integrated into third-party applications. It can also operate without a dedicated user interface.
Persistent Execution: It runs in the cloud, which means it maintains a single set of memories, context and one personalization graph no matter where you access it.
Multi-Agent Orchestration: Gemini can create sub-agents to tackle multi-step tasks and can also act as a coworker agent with a defined role and its own dedicated identity
Context: Gemini knows your tools, data, and work history and learns how you work the more you use it.
Model Choice Flexibility: It orchestrates across multiple models to deliver optimal quality and lower your costs.
Read more in our blog: cloud.google.com/blog/produc…
Aniesh Kumar retweeted
Here's the mind-blowing impact of solving this problem: gatesnot.es/4AWayG0
Aniesh Kumar retweeted
Your calendar decisions are your priorities.
How to set an operational cadence that empowers your executives, keeps you informed, and aligns your impact.
andymacmillan.io/posts/estab…
Aniesh Kumar retweeted
End user compute is becoming a big counter balance to frontier models. Lots of advantages of having a really good, open weight model, locally on your device. Privacy, relevance, and context for a much lower cost (essentially free) when you don’t need frontier models capabilities.
Aniesh Kumar retweeted
Perplexity Decider v1.1 is now on OpenRouter
@perplexity_ai's open-weights multimodal decision model takes text, JSON, or images and returns typed answers with probabilities
$0.02/M input. Output is free
openrouter.ai/perplexity/ppl…
pplx-decider-v1.1-27b, our updated open weights multimodal decision model, is now available.
It scores the highest on the new @huggingface Decision Index 0.3 benchmark. pplx-decider-v1.1-27b costs half as much as v1, at $0.02 per million input tokens.
huggingface.co/spaces/multim…
Aniesh Kumar retweeted
I got almost 2 hours a week back! Here is how…
Every board cares about three things, really: cutting cost, growing revenue, buying back time. Doesn't matter if the board is nine people or just me at my kitchen table.
I run Cloud Girl by myself. Advisory calls, my own content calendar, brand partnerships and somehow they're all due the same week.
For call prep I'd use Claude to go back to my client history and notes, but it was time consuming because I had to make sure I am providing all the context across my notes, emails, client meeting transcripts etc.
I recently hired Viktor, put him in Slack and pointed at my calendar and client notes.
A few days later I had an advisory call coming up, and Viktor had already pulled research on the client and dropped it in Slack before I'd even opened my calendar to look. I hadn't asked. He saw the meeting and got started!
I didn't expect that. Usually the morning before a call is gone, just digging through old notes trying to remember where things left off. This time the background was already sitting there and I could spend that time actually forming an opinion instead of hunting for context.
Viktor delivered on the board math: cost down for 1 hire not needed, revenue up by 1 more client retained, time back almost 2 hours a week.
Tell me I'm wrong, but for a solo operator this is a big deal!
Hire @viktor_com for your team.
$100 in credits included, no card. Full link in first comment. ref.viktor.com/pvergadia-x-1
Paid Partnership
Aniesh Kumar retweeted
India needs @Starlink 🇮🇳
• 11,256 of India’s listed villages still lacked 4G coverage as of May 2026.
• India had 1.093 billion internet subscriptions in March 2026, but only 440.87 million were rural. Rural subscription density was 48.31 per 100 people, compared with 126.80 in urban India.
• BharatNet had laid over 850,000 route-km of fibre and made about 221,000 Gram Panchayats service-ready. However, its Points of Presence were reported operational at only 80,472 Gram Panchayats in June 2026.
• Only 4.26% of India’s internet subscriptions were wired connections in March 2026. Starlink could give underserved communities another route to high-speed broadband.
• Starlink has already built 20 gateway sites in India, according to SpaceX Vice President of Starlink Business Operations Lauren Dreyer, speaking at India Mobile Congress today.
• Starlink says it has developed India-specific security controls designed to keep Indian user data within India.
• Its satellite network could bring high-speed internet to remote villages, mountains and islands where extending fibre or mobile networks is difficult.
• Better connectivity could help rural schools access online learning, clinics offer remote consultations and small businesses reach more customers. Starlink already supports education and healthcare in remote communities internationally.
• Portable Starlink terminals have supported disaster response around the world. They could give Indian emergency teams backup connectivity when floods, earthquakes or storms damage ground networks.
• Direct to Cell could also help ordinary 4G phones connect beyond tower coverage, subject to Indian approvals and mobile operator partnerships.
• The government itself identifies difficult terrain, low commercial viability and infrastructure constraints as reasons for remaining coverage gaps. This is exactly where Starlink could help India reach more people.
• India should complete the remaining clearances and spectrum allocation so Starlink can begin commercial service.
• SpaceX’s Vice President of Starlink Business Operations, Lauren Dreyer, said that Starlink is ready to help achieve Prime Minister Modi’s vision of 100% connectivity across India. She highlighted its potential to connect remote classrooms, support telemedicine and restore connectivity after disasters, adding, “With Starlink, people can get connected within minutes, not years.”
India’s hardest-to-reach communities deserve reliable internet too.
Aniesh Kumar retweeted
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
Aniesh Kumar retweeted
We are entering a new era of discovery now:
openai.com/index/sharing-ai-…
Aniesh Kumar retweeted
Today we're releasing our AI SDLC transformation playbook, where we share best practices to deploy AI at enterprise scale
Engineering leaders frequently ask how Atlassian thinks about our AI-native SDLC. This playbook is our answer, informed by our own transformation and learnings from top engineering organizations we work with
Come find us at the AI SDLC booth at Team '26 EU this week for a physical copy (and merch) atlassian.com/blog/ai-at-wor…
Aniesh Kumar retweeted
The guys who worked on this are the most productive and insanely talented people I've ever seen.
Maintained this entire algo, also kept the entire C++ stack at Meta up to date with the latest language standards.
Had almost 10x diffs/month over the median.
We're open-sourcing Rebalancer, the assignment-problem solver Meta has used for resource allocation across our infrastructure for over nine years.
Given a set of objects and a set of bins, Rebalancer assigns one to the other to optimize your objectives under your constraints, including hardware placement, service and task placement, traffic routing, and more. It separates how a problem is specified from how it's stored, solved, and debugged, with both an optimal MIP solver and a parallelized local search solver.
At Meta it solves ~40 million assignment problems a day across 30+ problem formulations. P99 solve time is 12 seconds on a problem with 265k objects and 3.2k bins.
🔗 Read more on our engineering blog: engineering.fb.com/2026/09/2…
Aniesh Kumar retweeted
Google just released the best 1-hour course on Graph Engineering: from one agent to a full 24/7 system
00:00 - what graphs are
09:16 - build an agent
21:15 - graph engineering explained
41:03 - graph engineering in practice
52:21 - self-improving graphs
free, and the best thing on graph engineering I have seen
Prompts → Agents → Loops → Graphs
most people will watch the first nine minutes and go back to typing into a chat box
he spends the last twenty on the part that is still true next year
same model, same tokens, completely different week
watch it today
the full guide on agents and graphs is below, save it while it is still early ↓
Aniesh Kumar retweeted
Someone literally put an entire AI engineering degree on GitHub and made it 100% free 🔥
523 lessons across 20 phases, with ~342 hours of material.
The whole curriculum is built around learning AI from first principles.
You start with the math, then implement the concepts yourself: backpropagation, tokenizers, attention, agent loops and more. Production frameworks come later, once you've already built the core mechanics by hand.
Every lesson runs these 5 steps:
Read the problem → derive the math → write the code → run the test → keep the artifact.
By the end of each lesson you have reusable: prompts, SKILLmd files, agent definitions, MCP servers you built yourself. The code runs in Python, TypeScript, Rust or Julia, depending on what fits the concept best.
The curriculum goes from linear algebra all the way to autonomous agent swarms, multi-agent coordination, production infrastructure, and AI safety.
It’s 100% free, open source, MIT licensed and available to clone and run locally. 65k+ stars on GitHub.
aiengineeringfromscratch.com
