DevOps @Accenture | Tech | AI | Humor Sharing DevOps & AI insights + daily hustle ✨ Collabs: DM or 📩 nkcollabs.in@gmail.com
Pune
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- Followers 23,034
- Likes 59,457
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As a DevOps Engineer who’s worked with AWS/Azure, Deployment and Auto scaling InstaCloud caught my attention.
It’s built for AI agents they can deploy, create replica environments, test, and autoscale while InstaCloud handles the infrastructure.
They’ve raised $8M. Curious to see how this plays out against traditional cloud providers like AWS and AZURE.
We just raised an $8M seed round to kill AWS, GCP, and Azure.
Introducing instacloud.com, the agent-native serverless cloud.
Your team is shipping code like never before. But you're getting caught up in manual, tedious DevOps work trying to deploy it.
InstaCloud provides the serverless compute that lets your services autoscale, with all the infrastructure managed for you.
Agents branch into complete replica environments when working, keeping prod safe and iteration speed high.
And of course, it all works seamlessly with agents through MCP/CLI.
Get off the traditional, legacy cloud.
Start deploying your services on InstaCloud today.
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Nandkishor retweeted
This is what a truly revolutionary idea looks like.
Not just another model it can see, hear, and interact with you in real time.
A tutor, interview coach, mentor, or assistant that understands what you’re struggling with as it happens.
Helpful and a little scary at the same time. We’ll need to use it effectively.
Yesterday we previewed Griffin, a Human Interaction Model capable of seeing, hearing, sounding, and looking like a human does. There have been a lot of questions, so I wanted to take a moment to share our thoughts.
By way of introduction: Tavus is a research lab focused on enabling machines to meet us where we are, and to understand the nuances of how we communicate beyond words.
Griffin, our latest model, isn’t publicly available yet. Yesterday’s announcement was a limited research preview to demonstrate what the model is capable of. With AI progressing so quickly, we prefer to share breakthroughs openly and in real-time as we work on a safe public release.
Face-to-face is how we evolutionarily communicate, it carries the most meaning and intent, and we want computers to be able to help with work that benefits from that emotional understanding, expression, and immersion. Some examples of the kinds of use cases we care deeply about:
- A tutor that can build understanding of how a student learns, see exactly when there is confusion or disengagement, and adapt the lesson to fit them.
- A health expert that can answer any questions about your upcoming appointment or prescription, at the pace you want, at any time you need, even on a weekend.
- A language coach that you can practice speaking with, that can correct your movement and pronunciation, and help build confidence to have real conversations
- Or the perfect assistant for everyone, that understands intent, knows how you work and remembers what matters.
We’re working with partners on safeguards and systems for disclosure, as well as inviting discussions with officials around wider regulation and safe use. People will always know they’re interacting with AI, while providing an interface that removes the need to ‘speak computer’.
We believe in a future where computers understand us well enough to make technology more accessible, more useful, and make us more capable as humans. That is the world we want to build, and we understand the responsibility to do so safely.
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Nandkishor retweeted
Is the job market really cooked in 2026, or am I misunderstanding it?
For me, it took 6-7 months to make a proper switch I thought may be due to it's my 1st switch.
But while talking to my ex-colleagues, I’m hearing the same thing. Earlier, they could switch companies within 2-3 months, but now, despite having 5+ YOE and good skills, they’ve been struggling for the last 6-7 months.
- Fewer interview calls.
- No response from HR after interviews.
- Companies not matching expected salaries.
- Offers getting revoked at the last moment.
Is AI and the hiring slowdown really making the market this tough?
What’s your experience?
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Nandkishor retweeted
DevOps interviews get harder as you level up.
Here’s a simple roadmap to prepare:
Junior → Build fundamentals
• CI/CD
• Docker & Kubernetes
• Terraform
• Load Balancers
• Scaling
• Monitoring & Logging
• ConfigMaps & Secrets
Mid → Solve real problems
• CI/CD design
• K8s troubleshooting
• Deployment strategies
• GitOps
• Docker optimization
• Observability
• Blue-Green & Canary
Senior → Think beyond tools
• Production-grade K8s
• Reliability & Security
• Incident Management
• SLI/SLO & Error Budgets
• Supply Chain Security
• Disaster Recovery
• Cost Optimization
• Observability at scale
The real difference?
Junior engineers learn how tools work.
Senior engineers understand why a particular solution should be used.
Save this roadmap for your next DevOps interview.
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Nandkishor retweeted
If you’re a man, learn this early:
- Don’t get attached to everything.
- Start investing early.
- Build skills that pay you.
- Build a side hustle.
- Never depend on one income source.
- Travel whenever you can.
- Be strong - ife is hard on weak men.
- Don’t say yes to everything.
- Take care of your family.
- Take calculated risks early.
- Work on your communication.
- Don’t feel guilty spending on yourself.
- Work hard for the life you dream of.
Remember:
As men, life doesn’t always come easy.
You have to build the life you want.
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This is what a truly revolutionary idea looks like.
Not just another model it can see, hear, and interact with you in real time.
A tutor, interview coach, mentor, or assistant that understands what you’re struggling with as it happens.
Helpful and a little scary at the same time. We’ll need to use it effectively.
Yesterday we previewed Griffin, a Human Interaction Model capable of seeing, hearing, sounding, and looking like a human does. There have been a lot of questions, so I wanted to take a moment to share our thoughts.
By way of introduction: Tavus is a research lab focused on enabling machines to meet us where we are, and to understand the nuances of how we communicate beyond words.
Griffin, our latest model, isn’t publicly available yet. Yesterday’s announcement was a limited research preview to demonstrate what the model is capable of. With AI progressing so quickly, we prefer to share breakthroughs openly and in real-time as we work on a safe public release.
Face-to-face is how we evolutionarily communicate, it carries the most meaning and intent, and we want computers to be able to help with work that benefits from that emotional understanding, expression, and immersion. Some examples of the kinds of use cases we care deeply about:
- A tutor that can build understanding of how a student learns, see exactly when there is confusion or disengagement, and adapt the lesson to fit them.
- A health expert that can answer any questions about your upcoming appointment or prescription, at the pace you want, at any time you need, even on a weekend.
- A language coach that you can practice speaking with, that can correct your movement and pronunciation, and help build confidence to have real conversations
- Or the perfect assistant for everyone, that understands intent, knows how you work and remembers what matters.
We’re working with partners on safeguards and systems for disclosure, as well as inviting discussions with officials around wider regulation and safe use. People will always know they’re interacting with AI, while providing an interface that removes the need to ‘speak computer’.
We believe in a future where computers understand us well enough to make technology more accessible, more useful, and make us more capable as humans. That is the world we want to build, and we understand the responsibility to do so safely.
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Yesterday we previewed Griffin, a Human Interaction Model capable of seeing, hearing, sounding, and looking like a human does. There have been a lot of questions, so I wanted to take a moment to share our thoughts.
By way of introduction: Tavus is a research lab focused on enabling machines to meet us where we are, and to understand the nuances of how we communicate beyond words.
Griffin, our latest model, isn’t publicly available yet. Yesterday’s announcement was a limited research preview to demonstrate what the model is capable of. With AI progressing so quickly, we prefer to share breakthroughs openly and in real-time as we work on a safe public release.
Face-to-face is how we evolutionarily communicate, it carries the most meaning and intent, and we want computers to be able to help with work that benefits from that emotional understanding, expression, and immersion. Some examples of the kinds of use cases we care deeply about:
- A tutor that can build understanding of how a student learns, see exactly when there is confusion or disengagement, and adapt the lesson to fit them.
- A health expert that can answer any questions about your upcoming appointment or prescription, at the pace you want, at any time you need, even on a weekend.
- A language coach that you can practice speaking with, that can correct your movement and pronunciation, and help build confidence to have real conversations
- Or the perfect assistant for everyone, that understands intent, knows how you work and remembers what matters.
We’re working with partners on safeguards and systems for disclosure, as well as inviting discussions with officials around wider regulation and safe use. People will always know they’re interacting with AI, while providing an interface that removes the need to ‘speak computer’.
We believe in a future where computers understand us well enough to make technology more accessible, more useful, and make us more capable as humans. That is the world we want to build, and we understand the responsibility to do so safely.
Introducing Griffin, the first model to pass the video Turing test.
48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.
It’s the first Human Interaction Model (HIM).
Community note
The 48% figure and "video Turing test" claim are from Tavus's own study of 54 one-minute calls, not independently verified or using a standard protocol. Griffin-Lite leads NVIDIA's VideoFDB benchmark on their public leaderboard.
cellcog.ai/blog/tavus-gri…
research.nvidia.com/labs/amri/proj…
tech-ish.com/2026/10/02/tav
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1,100 followers ❤️
Might just be a number for some, but knowing that 1,100 people decided to follow along means a lot to me.
I’ve been sharing everything here. Building my SaaS, fitness, coding, random thoughts, wins, failures and everything in between.
Thank you to everyone who follows, replies, likes, gives advice or just silently watches the journey.
Really appreciate every one of you ❤️
We keep building. We keep growing. 🚀
#1100Followers #BuildInPublic #SaaS #Developer #FitnessJourney #BuildingInPublic
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