Practical perspectives for founders and startup teams on AI product strategy, MVP development, agents, and knowledge assistants.
An approval can become outdated before an AI agent executes it. Learn how to handle changed actions, expired permissions and retries with clear execution checks.
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Can your chatbot access another customer’s documents? Use a two-workspace test setup to check retrieval, file downloads, caches and permission changes in Supabase RAG.
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A chatbot can find the right PDF and still return the wrong table value. Learn how to preserve table context, link answers to supporting pages, and test citation accuracy.
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Updated your documents but your chatbot still gives old answers? Learn how to trace stale information through ingestion, retrieval and caching, with a reusable document-refresh checklist.
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Learn how to scope an AI MVP before development. This guide covers AI MVP planning, data sources, features, success metrics, costs, safety, and launch strategy for chatbots, AI agents, RAG assistants, and automation tools.
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A practical guide to finding, designing, and deploying AI agents that reduce repetitive work without creating operational chaos.
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Learn how retrieval-augmented generation transforms scattered documents into accurate, source-aware answers for employees and customers.
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A failed execution does not always mean an email was never sent. Learn how to diagnose duplicate emails in n8n and design retries around reliable sending records.
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A decision framework for choosing between automation, an AI assistant, a custom model, or a full AI product.
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