Why I'm Burning Down Every SaaS Tool In My Business | PowerBI. tips
The shift most teams still do not see comingMost businesses still buy software like it is 2018. They stack app on top of app, glue them together with brittle integrations, then wonder why their process still. . .
The shift most teams still do not see comingMost businesses still buy software like it is 2018. They stack app on top of app, glue them together with brittle integrations, then wonder why their process still feels slow, expensive, and weirdly manual. That model is cracking. In this conversation, the argument is pretty blunt: the next generation of business software is not going to be a larger pile of SaaS subscriptions. It is going to beagent-driven, context-aware, and increasingly custom. That does not mean every packaged application disappears tomorrow. It means the center of gravity changes. Instead of forcing your team to learn ten interfaces, the interface starts coming to them. SaaS is not dead, but it is losing altitudeTraditional SaaS solved an important problem. It gave businesses fast access to capabilities without requiring them to build everything from scratch. That was the right move for a long time. The problem now is that many SaaS products have turned into rigid operating constraints:you adapt your process to the toolyou pay for features you barely useyou duplicate data across systemsyou manage permissions, exports, sync jobs, and edge-case workaroundsyou still end up opening Excel to actually get work doneThat last one is the joke nobody escaped. Excel has outlived half the software industry for a reason. The modern alternative is not “replace every app with a giant custom platform. ” That would be a terrible idea for most teams. The smarter alternative is this:keep core systems where they make sensereplace workflow friction with targeted custom experienceslet agents orchestrate the messy partsuse software components and models more like utilities than monolithsThat is the real disruption. Agents become the front doorOne of the strongest ideas in the discussion is thatagents should become the primary interface to your applications, not a bolt-on chat widget duct-taped to the side. That distinction matters. A bolt-on assistant answers questions. A real agent interface helps usersdo work. For analytics teams, that can look like:describing a business question in plain languagehaving an agent find the right data sourcegenerating a starter transformationsuggesting semantic model changesproducing draft measures or report layoutsexplaining tradeoffs before anything gets publishedThat is a much more important shift than “AI can summarize my dashboard. ”It turns the software from a passive tool into an active collaborator. Why this matters for Microsoft Fabric and Power BIThis is where things get interesting for our world. Microsoft Fabric already brings together storage, engineering, SQL, notebooks, semantic models, and reporting in one broader platform story. Power BI remains the business-facing analytics layer most teams actually live in. But there is still a giant gap between:raw business intentdata preparationmodeling decisionsfinal report deliveryThat gap is where consulting hours disappear, handoffs multiply, and business users get stuck. Agents can close part of that gap. Imagine a Fabric-native workflow where a user can say:I need a customer retention view by region, using the latest subscription data, and I want to compare rolling 12-month performance versus prior year. A good agent-enabled experience could:identify the relevant tablespropose the join pathdraft transformation logicrecommend semantic model structuregenerate starter DAXsurface assumptions that need confirmationproduce a first-pass visual layoutThat is not science fiction anymore. That is a product design problem. The real opportunity is smaller, faster, and more customA lot of service businesses are wildly overtooled. They buy generic platforms built for everyone, then spend months compensating for the fact that those tools were not designed for their exact delivery model. With modern AI tooling, many of those gaps can be closed with small focused builds instead of full software initiatives. That opens a big door for consulting firms and internal innovation teams. You do not need to recreate Salesforce, Jira, Notion, Airtable, and six automation layers from scratch like a maniac with a whiteboard and too much coffee. You need to identify:where the current stack creates dragwhere custom workflow creates leveragewhere agent interfaces reduce complexitywhere data and context can be reused across the businessThat is a much sharper strategy. Context is becoming the real moatAnother idea buried inside this conversation is that the best “second brain” setup may not be some magical all-in-one platform. It may simply be:a strong modela well-structured repositorymarkdown filesusable contextrepeatable workflowsThat sounds almost insultingly simple, which is usually a sign it is right. The issue is not whether your business has data. The issue is whether your systems make that data usable by people and agents. For Power BI and Fabric teams, this has serious implications. Your semantic model, business definitions, deployment patterns, documentation, and project notes are no longer just team artifacts. They are agent fuel. Messy context leads to dumb automation. Well-structured context leads to leverage. Consumption-based software changes how we buildThe conversation also points at a broader economic shift: more software experiences are moving towardpay-for-what-you-usemodels. That matters because it aligns much better with agentic systems. Instead of buying giant licenses for broad static functionality, businesses will increasingly pay for:inferencestorageexecutiontransformationorchestrationtask-specific software behaviorThat creates more flexibility, but it also demands better design discipline. If every interaction costs money, then sloppy prompts, bad model routing, and unnecessary compute become operational waste. Welcome to the future, where your architecture diagram now has a line item for “accidentally burning money with enthusiasm. ”What consulting teams should do right nowIf you work in analytics, data, or Microsoft Fabric, this is not a “watch and wait” moment. There are practical moves to make now:Audit your SaaS sprawlMap the tools your team uses across delivery, operations, knowledge management, reporting, and communication. Then ask:which tools are system-of-record platforms?which tools are just interface layers?which workflows could be replaced by a lighter custom experience?Design around workflows, not appsMost teams talk about software in nouns. They should be thinking in verbs. Not “What app do we use?” But “How does this work actually happen?”That shift changes everything. Treat your documentation like production infrastructureAgents are only as good as the context they can access. If your project notes, business definitions, semantic conventions, and architectural patterns are scattered or stale, your AI layer will inherit that chaos. Build one internal proving groundPick one painful internal workflow and rebuild it with:clear contexta small custom surfaceone or two targeted agentsmeasured outcomesDo not start with grand transformation theater. Start with one workflow that annoys your team every week. That is where the truth shows up. Final thoughtThe future is probably not “no software. ” It is also not “one giant SaaS suite to rule them all. ”The future looks more like this:core platforms where they make sensecustom workflow layers where leverage mattersagents as the operating interfacecontext as the strategic assetanalytics systems that help people act, not just observeFor Microsoft Fabric and Power BI teams, that is a big deal. Because once agents start becoming the front door to data work, the winners will not just be the teams with the best dashboards. They will be the teams with the bestworkflow design. And yeah, a lot of bloated SaaS tools should probably be nervous. Watch the full conversationIf this topic hits a nerve, it should. The shift away from rigid SaaS stacks and toward agent-first workflows is already underway. 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