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Perspectives from our engineers
Practical writing about AI, data and product engineering, from people who ship it. No trend pieces, no hype.
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Agentic AI
Where AI agents actually earn their keep
A practical guide to choosing agent work, setting boundaries and earning trust before autonomy expands.
6 min read · September 23, 2026
Generative AI
RAG is not a demo: what production retrieval takes
Production retrieval depends on freshness, evaluation and clear refusals, not just embeddings and a prompt.
7 min read · September 20, 2026
Data Engineering
Your AI roadmap is a data roadmap
AI delivery becomes predictable when teams make freshness, ownership and access part of the first use case.
5 min read · September 17, 2026
Generative AI
Build, buy or blend: choosing your LLM stack
Choose LLM stack boundaries by reversibility, data sensitivity and the product advantage you intend to own.
6 min read · September 14, 2026
Engineering Teams
The new math of engineering hubs in India
Engineering hubs create value through capability and ownership when leadership, rituals and retention are designed with intent.
6 min read · September 11, 2026
Product Engineering
Modernizing a legacy product without stopping the business
Incremental replacement reduces modernization risk while the existing product keeps serving customers and changing.
7 min read · September 8, 2026Turn the idea you are reading about into a delivery plan.
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