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Automatically capture, search, organize, and export your chats from Claude, ChatGPT, Gemini, and more — all stored locally in your browser.

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Chat Central

AI Conversation Manager

React performance optimization

Let me explain the key strategies for optimizing React rendering performance. First, use React.memo for components that receive the same props frequently, then implement useMemo and useCallback hooks for expensive computations to avoid unnecessary re-renders across your component tree.

Claude·Today·4 messages

Python data pipeline design

Here's a robust approach to building ETL pipelines with Python. I recommend using Apache Airflow for orchestration combined with Pandas or Polars for data transformations, implementing idempotent operations and checkpointing for reliable failure recovery.

ChatGPT·Today·4 messages

Travel itinerary for Japan

For a 10-day trip to Japan, I'd recommend starting in Tokyo for the first four days exploring Shibuya, Akihabara and Meiji Shrine, then moving to Hakone for Mt. Fuji views before heading to Kyoto's temples and finishing with Osaka's street food scene.

Gemini·Yesterday·4 messages

Writing a technical blog post

Great topic! Start with a compelling hook showing a real performance comparison, then cover what WebAssembly is, when to use it, include a hands-on example with benchmarks, and wrap up with common gotchas and limitations developers should know about.

Claude·Yesterday·4 messages

Kubernetes deployment strategy

For production deployments, I recommend a rolling update strategy that gradually replaces old pods with new ones. Set maxUnavailable to 0 and maxSurge to 1 for zero-downtime deployments, and consider blue-green when database migrations make gradual rollout risky.

ChatGPT·2 days ago·4 messages

Understanding transformer architecture

The transformer model relies on self-attention mechanisms that process all tokens in parallel. Each token attends to every other token to determine relevance, replacing the sequential processing in RNNs. Multi-head attention runs several attention operations simultaneously, each learning different relationships.

Gemini·2 days ago·4 messages
v1.0.0

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Chat Central

AI Conversation Manager

React performance optimization

Let me explain the key strategies for optimizing React rendering performance. First, use React.memo for components that receive the same props frequently, then implement useMemo and useCallback hooks for expensive computations to avoid unnecessary re-renders across your component tree.

Claude·Today·4 messages

Python data pipeline design

Here's a robust approach to building ETL pipelines with Python. I recommend using Apache Airflow for orchestration combined with Pandas or Polars for data transformations, implementing idempotent operations and checkpointing for reliable failure recovery.

ChatGPT·Today·4 messages

Travel itinerary for Japan

For a 10-day trip to Japan, I'd recommend starting in Tokyo for the first four days exploring Shibuya, Akihabara and Meiji Shrine, then moving to Hakone for Mt. Fuji views before heading to Kyoto's temples and finishing with Osaka's street food scene.

Gemini·Yesterday·4 messages

Writing a technical blog post

Great topic! Start with a compelling hook showing a real performance comparison, then cover what WebAssembly is, when to use it, include a hands-on example with benchmarks, and wrap up with common gotchas and limitations developers should know about.

Claude·Yesterday·4 messages

Kubernetes deployment strategy

For production deployments, I recommend a rolling update strategy that gradually replaces old pods with new ones. Set maxUnavailable to 0 and maxSurge to 1 for zero-downtime deployments, and consider blue-green when database migrations make gradual rollout risky.

ChatGPT·2 days ago·4 messages

Understanding transformer architecture

The transformer model relies on self-attention mechanisms that process all tokens in parallel. Each token attends to every other token to determine relevance, replacing the sequential processing in RNNs. Multi-head attention runs several attention operations simultaneously, each learning different relationships.

Gemini·2 days ago·4 messages
v1.0.0

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Chat Central

AI Conversation Manager

React performance optimization

Let me explain the key strategies for optimizing React rendering performance. First, use React.memo for components that receive the same props frequently, then implement useMemo and useCallback hooks for expensive computations to avoid unnecessary re-renders across your component tree.

Claude·Today·4 messages
work

Python data pipeline design

Here's a robust approach to building ETL pipelines with Python. I recommend using Apache Airflow for orchestration combined with Pandas or Polars for data transformations, implementing idempotent operations and checkpointing for reliable failure recovery.

ChatGPT·Today·4 messages
work

Travel itinerary for Japan

For a 10-day trip to Japan, I'd recommend starting in Tokyo for the first four days exploring Shibuya, Akihabara and Meiji Shrine, then moving to Hakone for Mt. Fuji views before heading to Kyoto's temples and finishing with Osaka's street food scene.

Gemini·Yesterday·4 messages
personal

Writing a technical blog post

Great topic! Start with a compelling hook showing a real performance comparison, then cover what WebAssembly is, when to use it, include a hands-on example with benchmarks, and wrap up with common gotchas and limitations developers should know about.

Claude·Yesterday·4 messages
writing

Kubernetes deployment strategy

For production deployments, I recommend a rolling update strategy that gradually replaces old pods with new ones. Set maxUnavailable to 0 and maxSurge to 1 for zero-downtime deployments, and consider blue-green when database migrations make gradual rollout risky.

ChatGPT·2 days ago·4 messages
work

Understanding transformer architecture

The transformer model relies on self-attention mechanisms that process all tokens in parallel. Each token attends to every other token to determine relevance, replacing the sequential processing in RNNs. Multi-head attention runs several attention operations simultaneously, each learning different relationships.

Gemini·2 days ago·4 messages
learning
v1.0.0

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React performance optimization

Claude·Today

Let me explain the key strategies for optimizing React rendering performance. First, use React.memo for components that receive the same props frequently, then implement useMemo and useCallback hooks for expensive computations to avoid unnecessary re-renders across your component tree.

work

Python data pipeline design

ChatGPT·Today

Here's a robust approach to building ETL pipelines with Python. I recommend using Apache Airflow for orchestration combined with Pandas or Polars for data transformations, implementing idempotent operations and checkpointing for reliable failure recovery.

work

Travel itinerary for Japan

Gemini·Yesterday

For a 10-day trip to Japan, I'd recommend starting in Tokyo for the first four days exploring Shibuya, Akihabara and Meiji Shrine, then moving to Hakone for Mt. Fuji views before heading to Kyoto's temples and finishing with Osaka's street food scene.

personal

Writing a technical blog post

Claude·Yesterday

Great topic! Start with a compelling hook showing a real performance comparison, then cover what WebAssembly is, when to use it, include a hands-on example with benchmarks, and wrap up with common gotchas and limitations developers should know about.

writing

Kubernetes deployment strategy

ChatGPT·2 days ago

For production deployments, I recommend a rolling update strategy that gradually replaces old pods with new ones. Set maxUnavailable to 0 and maxSurge to 1 for zero-downtime deployments, and consider blue-green when database migrations make gradual rollout risky.

work

Understanding transformer architecture

Gemini·2 days ago

The transformer model relies on self-attention mechanisms that process all tokens in parallel. Each token attends to every other token to determine relevance, replacing the sequential processing in RNNs. Multi-head attention runs several attention operations simultaneously, each learning different relationships.

learning

Rust error handling patterns

Claude·3 days ago

Rust's Result and Option types provide compile-time safety for error handling. Use Result<T, E> for recoverable errors and reserve panic! for truly unrecoverable situations. The ? operator makes error propagation clean, and for libraries consider thiserror while apps can benefit from anyhow.

code

Home workout routine

ChatGPT·4 days ago

A balanced full-body circuit routine you can do at home with zero equipment. Three rounds of squats, push-ups, lunges, planks and mountain climbers with warm-up and cool-down stretches. Aim for 3-4 sessions per week with rest days between for optimal recovery.

personal

PostgreSQL query optimization

Gemini·5 days ago

Query performance depends heavily on proper indexing and query plan analysis. Start with EXPLAIN ANALYZE to understand bottlenecks, add indexes on WHERE and JOIN columns, use partial indexes for filtered queries, and consider PgBouncer connection pooling for production workloads at scale.

work

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