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"Do we need RAG?" comes up in almost every B2B SaaS scoping call, and in 2026 the honest answer got less interesting.
Million-token context windows changed the arithmetic. A few hundred pages of product documentation now fits in the prompt. Stand up retrieval for that and you've bought chunking decisions, an embedding pipeline, a vector store, and an eval harness to catch the day it stops returning the right passage.
Retrieval still earns its keep on corpora that are genuinely large, that change faster than anyone re-indexes by hand, or where every answer has to point at a source. Narrower than most roadmaps assume.
https://www.duskolicanin.com/blog/rag-b2b-saas-when-use-when-skip-2026
#AI #SaaS #RAG #SoftwareEngineering
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The real challenge is turning AI into a useful, reliable product that solves a real business problem.
A strong AI SaaS needs:
→ A clear problem and target user
→ Simple, intuitive UX
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→ Reliable APIs and backend infrastructure
→ Proper data handling and security
→ Fast responses and scalable architecture
→ A clear path from MVP to a production-ready product
The goal isn’t to make something look “AI-powered.”
The goal is to build a product where AI genuinely makes the user’s job faster, easier, or better.
That’s what separates an AI demo from a real AI SaaS product.
Well done !
Hey! I just shared a write-up on something I learned while rebuilding a product with AI agents:)
The main idea is pretty simple:
Don’t put all your product context in one giant agent file.
Keep the main file small, and put the real product knowledge inside structured docs that the AI can navigate when it needs them.
This has helped me a lot when working on a SaaS product with a lot of business logic!
Sharing the full breakdown here:
I'm offering consulting services to set this up! :)
The table-of-contents-in-the-main-file pattern is the key move here - it keeps the agent's default context small while still giving it a map to go fetch the architecture or naming-convention doc only when the task actually touches that domain.
Sales management becomes easier when performance, activity, and follow-ups are visible in one place.
This B2B SaaS concept is designed around the daily workflow of sales teams, with dedicated views for top sellers, deal progress, customer engagement, tasks, and team performance.
clean work