My take
Why I use Anthropic
Anthropic's models, tooling (computer use, MCP, Claude Code), and safety posture make them my preferred partner for serious enterprise work. The 1M context window unlocks workflows that were impractical a year ago.
Want the broader stack philosophy? Read about how Sri picks tools or browse engineering insights.
Honest assessment
Strengths & tradeoffs
No tool is perfect. Here's what shines and what to watch for.
Strengths
- Long context (up to 1M tokens on Sonnet)
- Strong instruction following and tone control
- Native tool use and computer use
- Model Context Protocol ecosystem
- Strong safety and refusal calibration
Tradeoffs (honestly)
- Smaller third-party ecosystem than OpenAI (catching up fast)
- Pricing premium on largest models
- Region availability evolving
Fit assessment
When to reach for Anthropic
Pick the right tool for the job.
Best fits
Long-document analysis and summarization
Code review and complex codegen
Enterprise copilots needing nuanced judgment
Agentic workflows using tool use
Research assistants over large corpora
Not ideal for
Use cases needing tightest possible image generation (use specialized models)
Bulk extraction where cheaper models suffice
Common use cases
Resources
Learn more
Curated official docs, tutorials, and writing on Anthropic.
Services
Where I apply Anthropic
Engagements where this technology shows up regularly.
Case Studies
Anthropic in production
Real engagements where this technology shaped the outcome.
Browse the full case study archive.
Applications
Solutions using Anthropic
See how this technology is applied in real-world solutions.
Stack
Pairs well with Anthropic
Tools and platforms I commonly combine with this one.
AI & ML
More in this category
Model providers, frameworks, and stores that power my AI work.
Need help with Anthropic?
Whether you're starting fresh or optimizing an existing implementation, I can help you get the most out of this technology. Read more in insights or get in touch.