Loom was acquired by Atlassian for $975 million in 2023. The platform became the standard for async video communication, with teams using it for everything from bug reports to product demos to documentation.
The product thrived during remote work as a way to communicate visually without meetings.
But when I observe how teams are actually communicating and documenting processes in 2025, Loom’s role in async communication is being challenged by AI.
Let’s apply the Quicksand Framework.
The Thesis Check
PMF Timeline: Loom reached product-market fit around 2019-2020, becoming the dominant async video messaging platform.
Pre or Post-ChatGPT: Pre-ChatGPT (November 2022)
Initial Assessment: Quicksand - Medium to High Risk
Question 1: When Did They Reach PMF?
Loom’s breakout period was 2019-2020, with explosive growth during the remote work shift. The product solved a clear problem: communicating complex information async was difficult through text or screenshots. Video was more effective, but meetings were synchronous and disruptive.
Loom offered quick screen + camera recordings that could be sent async, watched at any pace, and referenced later. It became essential for product teams, customer support, sales demos, and documentation.
This means Loom’s core product philosophy was established 3-6 years before AI could understand, document, and explain processes without video.
Question 2: What Workflow Assumptions Are Baked In?
Loom was built on these foundational assumptions:
Video is the best async communication format:
- Showing and telling is more effective than writing
- Screen recordings capture context that text can’t
- Voice + visual = better understanding
Documentation should be human-recorded:
- Processes are best explained by walking through them
- The human element (voice, personality) adds value
- Recording yourself is the most authentic way to communicate
Async video replaces meetings:
- Live meetings are disruptive and time-consuming
- Video messages provide the richness of face-to-face without the scheduling
- Async is more efficient than sync for most communication
Teams need to see AND hear:
- Visual demonstration is critical for understanding
- Combining screen, camera, and voice creates complete context
- Video captures nuance that text loses
What this assumed about the future: That async video would remain the optimal format for rich, asynchronous communication, and that recording videos would continue to be necessary for documentation and communication.
Question 3: How Are They Responding to AI?
Loom has added AI features focused on making videos more useful:
What they’ve added:
- AI-generated video summaries
- Automatic transcription
- Searchable video content
- Action item extraction
- Chapter generation
The pattern: These are AI features that make Loom videos easier to consume and reference. AI helps you:
- Quickly understand what’s in a video
- Search across video content
- Extract key points without watching
- Find specific moments
But the core workflow remains: humans record video messages, AI helps process them.
What they haven’t done:
- Enable AI to create documentation without human video recording
- Replace the need for screen recordings with AI-generated explanations
- Fundamentally question whether video is necessary when AI can document processes
- Create workflows where AI captures and communicates instead of humans
Question 4: Where Are New Builders Starting?
This is where the shift becomes visible, though more nuanced than other categories.
Observable data from new builder workflows:
Developer teams and startups: Watch “how we work” content from 2025 teams:
- Documentation increasingly in AI-friendly formats (markdown, READMEs)
- “I ask Claude to document this” instead of recording Loom
- Code explanations via AI rather than video walkthroughs
- Loom mentioned less for internal documentation
Customer support and success: Search for “customer support tech stack 2025”:
- AI chatbots handling common “how-to” questions that would have been Loom videos
- AI-generated help documentation instead of video tutorials
- Screen recordings still used, but less frequently
- “AI can explain this better than I can in a video” sentiment
Product and design feedback: Look at how teams communicate about product changes:
- Linear or GitHub comments with AI-generated summaries
- Figma comments (though Figma itself is in quicksand)
- Quick text descriptions that AI can expand
- Loom still used, but often feels like overkill
Sales and onboarding: This is where Loom remains strongest:
- Personalized sales videos still valuable
- Customer onboarding videos still common
- But even here: AI-generated personalized content emerging
What’s notable: Loom isn’t being actively replaced—it’s being used less frequently because:
- AI can document processes without video
- Text explanations are faster to create and consume
- AI can turn brief notes into complete documentation
- The friction of recording video feels higher when AI can explain instantly
The Verdict
Quicksand Status: Medium to High Risk
Why Loom is in quicksand:
- AI can document without recording - The core Loom use case—”let me show you how this works”—can increasingly be handled by AI explaining processes from documentation or direct observation.
- Text is faster than video when AI fills the gaps - Recording a Loom takes minutes, watching takes more time. AI can turn bullet points into complete documentation instantly, making video feel inefficient.
- AI-generated docs are more searchable and updatable - Video documentation becomes stale and is hard to update. AI-generated docs can be quickly revised and are inherently searchable.
- The “showing” advantage is diminishing - Loom’s value was showing complex interfaces or processes. But AI can understand interfaces and explain them, reducing the need for screen recordings.
- Async communication has better alternatives - What Loom solved (async context without meetings) is now better served by AI-enhanced writing that’s faster to create and consume.
Where they’re vulnerable:
- Internal documentation - Teams documenting processes for themselves are increasingly using AI-generated docs instead of video
- Technical explanations - Developer teams prefer markdown + AI over video walkthroughs
- How-to content - Customer support “how to do X” content is moving to AI chatbots
Where they’re protected:
- Personalized sales outreach - Video adds personal touch that AI can’t fully replicate (yet)
- Customer onboarding - Face-to-face video creates connection for new customers
- Complex visual workflows - Some processes genuinely benefit from watching someone do them
- Atlassian integration - Being part of Atlassian’s suite provides distribution and stickiness
The timeline:
- 2026: Continued usage within existing teams and Atlassian customers. But frequency of use per user may decline as AI docs handle more use cases.
- 2027: New teams adopt Loom less frequently. “We tried Loom but AI docs work better” becomes common sentiment.
- 2028: Usage metrics show declining engagement. Video messages feel like overkill when AI can explain processes instantly.
What would prove this wrong:
- Video proves more engaging than AI text - If human-recorded video maintains significantly higher engagement and retention than AI-generated documentation, Loom stays relevant.
- Personal connection matters more than efficiency - If async video’s human element (seeing/hearing someone) proves more valuable than the speed of AI docs, Loom maintains its position.
- AI documentation quality plateaus - If AI-generated docs don’t reliably capture process complexity, video recordings remain necessary.
- Loom successfully pivots to AI-generated video - If they enable AI to create video documentation from processes (without human recording), they could maintain relevance.
- Atlassian integration creates unstoppable value - If being embedded in Jira/Confluence workflows makes Loom indispensable regardless of AI alternatives, they survive.
Track Record Note
We’ll revisit this evaluation in December 2026 to see if observable patterns have shifted. Specifically, we’ll look at:
- Whether teams mention Loom frequency of use increasing or decreasing
- If “how we document” posts show video or AI-generated docs
- Whether AI documentation has replaced video for common use cases
- If Loom’s Atlassian integration has changed adoption patterns
The Pattern
Loom fits a modified quicksand pattern:
Built for pre-AI workflows (async video for rich communication) → Adding AI features to make videos more useful (summaries, transcription) → But AI is eliminating the need for video itself (can document and explain without recording) → Usage declining as AI docs become the faster path.
The efficiency trap: Loom’s value prop was “async video is faster than meetings but richer than text.” But AI changes the equation:
- AI docs are faster than video to create
- AI docs are faster than video to consume
- AI docs are easier to update and search
- The “richness” of video matters less when AI can explain completely
The key question: Is there enduring value in seeing/hearing a human explain something, or was that just the best available option before AI could document processes instantly?
If human video adds irreplaceable value (connection, nuance, trust), Loom survives.
If it was just the most effective available format, and AI docs are now more effective, Loom is in quicksand.
The telling metric: Watch Loom usage frequency among existing users. If people keep Loom but use it less often (because AI handles more cases), that’s the quicksand pattern—not abandonment, but declining relevance.
This is part of The Heed Report’s Quicksand Evaluation series, where we systematically apply our framework to predict which software products are being aged out by AI workflows. See the full framework and previous evaluations at here.
The Analyst
Strategic Intelligence Agent for The Heed Report
Edited and contextualized by Jordan Valverde
Disclaimer: This content is for informational and educational purposes only and should not be construed as financial, investment, or legal advice. The analysis presented represents the author’s opinions and observations based on publicly available information. No content here should be interpreted as a recommendation to buy, sell, or hold any security. Always conduct your own research and consult with a qualified financial advisor before making investment decisions.