Vaishnavi Tikke

Vaishnavi Tikke

Forward Deployed Engineer | Turning Business Problems into AI Solutions 8x-m7d343

LinkedIn & X creator · India · 8.5K followers

Vaishnavi is a creator on Naano, where companies pay creators to write posts about their product.

Below: Vaishnavi's audience and recent posts.

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About Vaishnavi Tikke

I take customer problems from conversation to production. Engineer with hands-on experience across AWS, GCP, Kubernetes, Terraform, Docker, and CI/CD. I enjoy working close to the problem understanding requirements, building solutions, and getting them into production. ▫️ Turn requirements into working solutions ▫️ Build, deploy, debug, and iterate ▫️ Automate workflows and improve reliability ▫️ Work across DevOps, AI, MLOps, and AI infrastructure I’ve grown a 21K+ developer audience on X by sharing practical engineering insights and learning in public. Currently focused on Forward Deployed Engineering and AI-native systems. I build, ship and explain.

SoftwareAIProductivity

My audience

LinkedIn

Followers
8,505
Est. median reach
350
Reactions per post
4
Median of recent posts

My most engaged audience

87% Engineering / Data

From 32 people who reacted to or commented on my posts

Public LinkedIn data · Oct 31, 2026

X

X followers
22,072
Average public views
690.3
Engagement / measured views
1.2%

Public X data · Captured Oct 31, 2026

  • Bangalore devs, do you agree....? 😂

    11 reactions · 0 commentsView
  • Andrej Karpathy said we should stop thinking of LLMs as chatbots Think of them as the kernel of a new operating system. That idea is becoming much more practical in 2026 Local LLM engineering is no longer just about running a model. It’s about building an always-on AI system on your own machine. Think: ▫️ Model → cognitive core ▫️ Context → RAM ▫️ Files → storage ▫️ Tools/MCP → peripherals ▫️ Agents → processes Local models can already handle: → Coding → Private document Q&A → Ticket triage → Data extraction → Coding agents → Overnight automation But model size isn't everything. Memory determines what you can load Bandwidth determines how fast it runs Context determines how much it can see Quantization determines the memory cost Utilization determines whether the hardware is worth it And you don't need one giant model for everything Small local model → routine tasks Larger local model → serious private work Frontier API → genuinely difficult reasoning The goal isn't to replace cloud AI. It's to give the right task to the right model The interesting question isn't: “Can I run an LLM locally?” It's: “What should my machine be doing while I sleep..?” 👀

    7 reactions · 2 commentsView
  • Vibe coders build software using AI Reverse engineers figure out how existing software works & rebuild it If both can create software, where is the software engineering industry heading..? 👀

    4 reactions · 1 commentsView

Work with Vaishnavi Tikke

LinkedIn

Choose a format for your next LinkedIn collaboration.

Sponsored LinkedIn post

A dedicated post to introduce your brand to my audience.

€500

Not taking bookings on LinkedIn right now.

X

Choose a format for your next X collaboration.

Sponsored X post

A dedicated post to introduce your brand to my audience.

€500

Not taking bookings on X right now.

Your collaboration, managed on Naano

  • Share your brief with the creator
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How does this price compare? B2B creator rates 2026

Who engages with my posts

Based on 32 people who reacted to or commented on my posts. Percentages use the profiles that could be classified.

Founder / C-level1 of 1

X followers

Sample of 300 public X follower profiles. Public X data, not the audience of a specific post. This follower sample is partial.

Bengaluru, India5.9%
India3%
Nairobi, Kenya2.2%

Posts on X

X

Childhood: Dreamed of becoming an engineer 12th: COVID hit College: AI entered the chat Graduated: AI started taking jobs Job hunt: 500 applicants for one opening We really went through all this just to become engineers 💀 What a great loop

Views
284
Likes
2
Replies
1
Reposts
0

https://t.co/yYKdnO0gbI

Views
58
Likes
0
Replies
0
Reposts
0

A PAPER JUST DECLARED THE END OF SOFTWARE ENGINEERING. ITS OWN DATA SAYS AGENTS STILL CAN'T MAINTAIN A CODEBASE. the argument: code stops being the product and becomes disposable tooling. agents write it, run it, throw it away → old flow: ai → software → result → new flow: agent → result → engineers turn into intent architects, agent coordinators and outcome auditors but the evidence it cites cuts both ways: → agents clear 80%+ on isolated tasks → drop to 38% at best when they have to keep evolving the same codebase commit after commit → context drift, compounding errors, no sense of tech debt writing code is getting cheap. maintaining it isn't. so what's actually ending: the engineer, or the 10-year-old monolith nobody wants to touch?

Views
536
Likes
8
Replies
5
Reposts
2

OpenAI is shutting down Prism, its free LaTeX tool for scientists https://t.co/9sWlomjJL0

Views
279
Likes
2
Replies
0
Reposts
0

bro got rejected for the one question they didn't ask 👀 https://t.co/laTXS0qhyY

Views
745
Likes
8
Replies
0
Reposts
0

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Booking Vaishnavi Tikke: frequently asked questions

Vaishnavi Tikke is a B2B LinkedIn creator based in India with 8,505 followers, posting about Software, AI, and Productivity. On Naano, one sponsored LinkedIn post by Vaishnavi Tikke costs €500, a fixed price per post. A sponsored X post costs €500. Vaishnavi Tikke is not taking new bookings right now.

How much does Vaishnavi Tikke charge for a sponsored LinkedIn post?
One sponsored LinkedIn post with Vaishnavi Tikke costs €500 on Naano. It is a fixed price per post, the amount your brand pays. A sponsored X post costs €500. Compare with the B2B creator rates 2026 report
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