The Algorithmic Work Feed: Why B2B Tools Are Solving the Wrong Problem

Instagram's CEO recently admitted what we all knew: people are retreating to DMs because authenticity only works in small groups. The public feed became performative, so users voted with their attention and went private.

Meanwhile, in B2B, we're sprinting in the exact opposite direction.

We're expanding collaboration surface area like it's our job—more Slack channels, more Teams threads, more recorded meetings with AI summaries. We've built enterprise tools that treat "more places to communicate" as progress. And somehow, despite all this visibility, we're more lost than ever.

Here's what's breaking my brain: Instagram can show me content from 1,000 strangers that's weirdly relevant to my life. But Microsoft Teams—with access to my role, my projects, my calendar, and my organizational graph—can't surface the 10 decisions from last week that actually affect my roadmap.

We've handed everyone 47 fire hoses of information and told them to drink from all of them simultaneously. Then we added AI to label each stream. But the problem isn't unlabeled water. Nobody can drink from 47 fire hoses, no matter how well-organized they are.

B2C Cracked Distribution. B2B Is Still Drowning in Broadcast.

Consumer platforms figured out algorithmic distribution at scale a decade ago. TikTok doesn't ask you to follow the right creators—it shows you what's relevant based on behavior, context, and engagement patterns. Instagram's Explore tab surfaces content you didn't know you needed. YouTube's recommendations understand your intent better than you do.

They solved the inverse problem: too much content, limited attention. The answer wasn't better organization. It was intelligent filtering.

B2B is still operating in the broadcast era. Every message goes to everyone in the channel. Every meeting gets recorded for "visibility." Every decision gets documented in threads that nobody reads. We've confused access with relevance, transparency with signal.

The result? Knowledge workers spend 28% of their week managing email and nearly 20% looking for internal information or tracking down colleagues. We're not working—we're triaging information overload.

What If the Answer Isn't More Visibility?

The instinct in enterprise software is always MORE:

• More channels for better organization
• More integrations for comprehensive context
• More AI summaries to process everything
• More dashboards to see it all

But what if the answer is the opposite?

Fewer places decisions can happen. Smarter distribution of what matters.

Constrained input. Intelligent broadcast.

This isn't about building better search or more sophisticated filters. It's about fundamentally rethinking how information flows through organizations. Instead of "here's everything, figure out what matters," the system should know what matters to you and surface only that.

The Missing Primitive: Contextual Revision

Current collaboration tools operate on a sacred artifact model—messages are immutable broadcasts. You write something, you send it, and everyone sees the exact same words.

But AI unlocks something radically different: contextual revision in real-time.

Imagine you write: "We need to prioritize the auth refactor."

• Engineering sees: "Auth refactor blocking 3 stories, estimated 2 sprints, reduces tech debt by 15%"
• Executive sees: "Auth work prevents security audit delays, unlocks Q2 revenue milestone"
• PM sees: "Auth refactor impacts roadmap items X, Y, Z—need prioritization decision by Friday"

Same core message. Different framing. The AI rewrites based on who's reading, what they care about, and what action you need from them.

This isn't editing after you send. It's recognizing that messages aren't sacred text—they're intent wrapped in words. And those words should be malleable based on recipient context.

What This Looks Like in Practice

Teams has @mentions to target people. It has "Discover" to surface followed threads. But it's missing the most important feature: revise what was written based on who's consuming it.

The features that should exist:

"Smart Send"
Before you hit send, AI analyzes recipients and shows you: "Here's what Engineering will see" vs. "Here's what Leadership will see." You approve or adjust. Each person gets the version relevant to them.

"Thread Digest for [Role]"
When someone gets looped into a 50-message thread, they don't see everything. They get: "As a PM, here's what matters: decision needed on X, context is Y, your action is Z." Engineers get a different digest. Execs get a different digest.

"Feed of What Actually Affects You"
Instead of surfing through channels and threads, you open Teams and see:

• "These 3 decisions need your input today"
• "This technical discussion changes your roadmap assumptions"
• "Your team's velocity suggests this sprint is at risk"

Everything else the system handles in the background. You're not hunting through Azure DevOps or scrolling Slack. The system hunts for your attention only when truly needed.

Minimal UI, Maximum Context

This requires building radically less UI but investing 10x more in intelligence.

The B2C social feed model is the template:

• Notification layer: "This needs you now"
• Approval/decision layer: Swipe, approve, reject, escalate
• Deep-dive layer: Only when you need full context

Instagram doesn't make you browse categories—it surfaces what's relevant based on behavior, time of day, recent activity. Your work tools should do the same.

The difference is stakes and transparency. B2C algos optimize for engagement (more scrolling = better). B2B needs to optimize for productivity (less UI time = better). And unlike TikTok, where you don't know why you're seeing content, B2B systems need explainability: Why am I seeing this? What am I NOT seeing?

The companies that solve this will build tools with a new kind of moat—not features, but attention efficiency. If your tool surfaces the right information at the right time with minimal friction, why would anyone go back to clicking through menus and scrolling through channels?

B2C and B2B Are Solving Inverse Problems

• B2C: Too much content, limited attention → Algorithmic filtering
• B2B: Too much communication, limited focus → Still trying broadcast + better labels

Consumer platforms learned that you can't organize your way out of information overload. You need intelligence that understands context and surfaces relevance.

Enterprise tools are still acting like the solution to "too many fire hoses" is color-coding them and adding AI summaries. But the real solution is: stop drinking from 47 fire hoses. Build a system that knows which three sips you actually need.

What This Means for Product Leaders

If you're building collaboration tools, the question isn't "how do we help users find information faster?" It's "how do we surface the right information before they even look?"

The PM skillset shifts:

• From designing comprehensive dashboards → designing attention algorithms
• From building feature-rich UIs → building context engines
• From maximizing visibility → maximizing relevance

You're not designing screens. You're designing what gets interrupted for, what gets batched, and what gets suppressed entirely.

The Platform That Cracks This Changes Everything

The company that builds algorithmic decision distribution for cross-functional teams will do to Slack what TikTok did to chronological feeds.

It won't be about better organization or more powerful search. It will be about fundamentally different information architecture:

• Current model: Everything is visible, users filter manually
• New model: System understands context, surfaces what matters

Microsoft has all the pieces—Teams for collaboration, Graph API for organizational context, Azure OpenAI for intelligence. They could build "Copilot revises your messages based on recipient context" tomorrow.

But they're stuck thinking about messages as immutable artifacts instead of contextual rendering engines.

Whoever moves first on this—whether incumbent or startup—won't just improve collaboration. They'll redefine what it means to work in distributed teams.

Because the future of work isn't everyone seeing everything.

It's everyone seeing exactly what they need, exactly when they need it, and nothing else.

Constrained input. Intelligent broadcast. Algorithmic relevance.

That's the play.

Learn. Build. Share. Repeat.

Sharing lessons from the trenches.

Anthony Ludwig