Given you know domain better than customers rather than giving blank text box for interaction with LLM over deterministic domain model, give suggestions of what they could ask for.
SOFTWARE
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LLMs Simplify Search Interfaces Beyond Boolean Logic for All Users
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Rob: Lay users (non-engineers) don't understand boolean logic like AND/OR. We once relied on complex composed interfaces to do filtering/search, and/or pseudo-syntax. LLMs can reinvent some interfaces to make them radically simpler and more effective for users. Everyone can text
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Top Six In-Product AI Usage Patterns From Chat to Agentic
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In-product usage #1: "Chat" / conversational interface
#2: Generation
#3: Categorization
#4: Ingestion
#5: Analysis
#6: Agentic interfaces (MCP / CLI) -
Chat Interface Overused as AI Integration Model Says Expert
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Chat interface has overinfluenced builders. Just because it is traditional and relatively easy to spec out doesn't mean it is the ideal way to integrate into existing/wider software suite.
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LangSmith Deployments: Moving AI Agents to Production
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Building agents locally does not mean they’re ready to deploy in production LangSmith deployments helps with that
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Bootstrappers Gain Edge Designing LLM-Native Solutions From Scratch
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Because boostrappers are much more nimble than existing market, you can reasonably be on leading edge of "What does a solution in X space look like *if it is designed from the ground up in the knowledge that LLMs exist*, as opposed to shoehorning LLMs into a single screen?"
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AI Product Strategy: Bootstrappers Should Build Downstream of Labs
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AI as product: Difficult for bootstrappers to keep up with the labs on LLM/etc development. Very, very tractable to make something downstream of the labs.
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Deploy Features Without Hardware for Maximum Availability
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The ability to deploy new features without installing hardware enables faster scaling and maximum availability.
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How Bootstrapped SaaS Companies Are Deploying AI in Production
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Rob did informal survey of a few hundred TinySeed companies (he runs a VC/accelerator which invests in many bootstrapped-adjacent software companies) to see how its actually getting deployed in production. Taxonomy: six-ish ways that companies actually metabolizing it.
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Rob Walling on Using AI in SaaS at MicroConf
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Next up at MicroConf: @robwalling on How to use AI in SaaS. This has been something of an undercurrent in a lot of conversations here. Lots of unease and anxiety about it, and IMHO a bit overblown w/r/t impact on SaaS specifically. With that, Rob: