Principal Software Engineer | Building Data & AI systems at scale | AI, Career, pay, architecture & hard lessons | Travel & lifestyle occasionally ✈️
Bengaluru, India
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Tanuj retweeted
This might be the most accurate AI model tier list as of today.
I’ve used almost 60% of these models myself and well this looks perfect.
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Tanuj retweeted
People still think Anthropic is winning the AI race……
Bro, look at the user numbers.
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Tanuj retweeted
Backend Interview Question:
Your cron job runs once every day at 2:00 PM.
One day, it executes 3 times.
You verify:
- No duplicate servers
- No manual trigger
- No deployment
- No code changes
- No duplicate cron entry
The scheduler shows only one job.
How can the same scheduled job execute three times in production?
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Tanuj retweeted
As a dev, do you know the difference between
- API Gateway
- Load Balancer
90% devs use them interchangeably
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Tanuj retweeted
Want to get good at backend? Start with these fundamentals:
HTTP & networking
• HTTP methods and status codes
• Headers and cookies
• HTTPS and TLS
• DNS and proxies
• Request/response lifecycle
Authentication & authorization
• Sessions vs tokens
• JWT access and refresh tokens
• OAuth 2.0 and SSO
• Password hashing
• Salting and peppering
• 2FA
• RBAC and ABAC
API design
• REST APIs
• GraphQL
• WebSockets
• API versioning
• Rate limiting
• Throttling
• Pagination and filtering
• File uploads
• Streaming
Server fundamentals
• Middleware
• Routing
• Error handling
• Logging
• Health checks
• Server-side rendering
Databases
• SQL vs NoSQL
• Schema design
• Relationships
• Indexes
• Query optimization
• Transactions
• ACID and isolation levels
• Normalization vs denormalization
• ORMs
• Connection pooling
• Migrations and seeding
Caching & performance
• Cache strategies
• Redis
• Memcached
• CDN caching
• Database optimization
• Connection reuse
Scalability & distributed systems
• Load balancing
• Horizontal vs vertical scaling
• Monoliths vs microservices
• Message queues
• Pub/Sub
• Event-driven architecture
• Idempotency
• Retries and backoff
• CQRS and Saga patterns
• API gateways
Infrastructure & DevOps
• Docker
• Kubernetes
• CI/CD
• Environment configuration
• Secrets management
• Service discovery
Security
• CORS
• CSRF
• XSS
• SQL injection
• Input validation
• Output encoding
• Secure headers
Background processing
• Job queues
• Worker processes
• Cron jobs
• Scheduled tasks
• Retry handling
• Dead-letter queues
Concurrency & runtime
• Promises
• async/await
• Event loop
• Threads
• Processes
• Memory management
• Garbage collection
Testing & tooling
• Unit testing
• Integration testing
• E2E testing
• Mocking and stubbing
• API testing
• Swagger / OpenAPI
• Git
• Code reviews
• Debugging
• Profiling and benchmarking
Production
• Deployment strategies
• Health checks
• Logging and monitoring
• Performance tracking
• Incident debugging
Once these concepts click, backend stops feeling like random pieces of technology.
You start understanding why the pieces exist and how they fit together.
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Tanuj retweeted
As a developer, do you know If I can download an AI model and run it without internet, where is everything it knows actually stored?
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Tanuj retweeted
Griffin feels like a meaningful step toward more human centered AI.
The potential is enormous, but as AI becomes more human like, safety, transparency, and responsible development become even more important.
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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Tanuj retweeted
It’s 2 AM.
Production is down.
You have 30 minutes.
Who are you calling?
1. Senior engineer
2. Claude Code
3. Codex
4. Both AI agents
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