The Quicksand Report: 12 Software Companies Being Aged Out by AI Workflows
There’s a clear line of delineation for whether a software product is becoming “legacy”—and it’s simpler than most realize.
Did the company reach product-market fit before the ChatGPT boom (end of 2022)?
If yes, that product was likely built on foundational assumptions about user value and feasibility that have shifted significantly over the last two years. Products built after the ChatGPT boom were designed for the new AI-native workflow from the start.
If this holds true, a lot of companies and products are in varying degrees of being aged out.
I call these “quicksand companies”—the harder they try to move toward AI, the more they sink because their business is set up, from CEO to newest hire, to serve a workflow that’s becoming less valuable.
The Framework
I’ve systematically evaluated 12 major software companies using four diagnostic questions:
Question 1: When Did They Reach PMF? If it was before November 2022 (ChatGPT launch), their product philosophy was established in the pre-AI era.
Question 2: What Workflow Assumptions Are Baked In? What foundational beliefs about how work gets done are embedded in their product architecture?
Question 3: How Are They Responding to AI? Are they adding AI features to the existing workflow, or rebuilding around AI-native workflows?
Question 4: Where Are New Builders Starting? This is the leading indicator that predicts everything else. If new builders (those starting their first projects in 2024-2025) aren’t adopting the tool, the pipeline is freezing—even if current metrics look healthy.
The 12 Evaluations
High Risk: Workflows Being Eliminated
1. Figma - Design collaboration
The core issue: New builders go from idea → working product in AI-native environments (v0, Bolt, Cursor). There is no separate “design phase.” The workflow that made Figma valuable—design, handoff, collaboration—doesn’t exist in AI-native development.
Current metrics: $1B+ ARR, 38% growth, 90K+ new paid teams
Leading indicator: “How I built this” posts from 2025 don’t mention Figma
Timeline: 2027-2028 pipeline crisis becomes visible
2. Zapier - Workflow automation
The core issue: AI agents can connect tools directly and reason about what needs to happen. Visual workflow builders become unnecessary middleware when AI can go from “what I want automated” to “make it happen.”
Current metrics: 7M+ users, profitable, 7,000+ integrations
Leading indicator: New technical builders choosing AI agent frameworks over Zapier
Timeline: 2027-2028 developer adoption declines significantly
3. Miro - Visual collaboration
The core issue: New builders brainstorm with AI through conversation, not with humans on a visual canvas. The sticky-note whiteboarding session is becoming obsolete for solo builders and small teams.
Current metrics: 60M+ users, $17.5B valuation
Leading indicator: “Day in the life” content from indie devs shows no Miro usage
Timeline: 2027-2028 small team adoption slows dramatically
4. Airtable - Flexible databases
The core issue: AI eliminates the “easy database” need. Non-technical users can ask AI to handle data directly. Technical builders use proper databases with AI generating queries. Airtable’s middle ground disappears.
Current metrics: 500K+ organizations, $11B valuation
Leading indicator: New projects choosing Postgres + AI or no database at all
Timeline: 2027-2028 new project adoption slows
5. Webflow - Visual web development
The core issue: AI builders (v0, Bolt) go from prompt to production-ready website in minutes. Visual builders that take hours or days can’t compete on speed. The “professional no-code” position gets squeezed out.
Current metrics: $4B valuation, agency-focused growth
Leading indicator: “How I built my landing page” posts show v0/Bolt, not Webflow
Timeline: 2026-2027 startup adoption declines sharply
Medium-High Risk: Value Proposition Weakening
6. Canva - Design for non-designers
The core issue: AI image generation eliminates the “templates + visual editor” need. But Canva is fighting back aggressively with AI features. The outcome is less certain.
Current metrics: 170M+ MAU, $26B valuation
Leading indicator: New content creators choosing AI generation over Canva templates
Timeline: 2027-2028 creator adoption patterns will determine outcome
Why not higher risk: Aggressive AI integration, strong brand habits, small business loyalty
7. Loom - Async video messaging
The core issue: AI can document processes instantly without video recording. Text explanations with AI are faster to create and consume than video. Loom usage declining in frequency, not abandonment.
Current metrics: Acquired by Atlassian for $975M
Leading indicator: Teams using Loom less frequently as AI docs handle more cases
Timeline: 2027-2028 usage frequency decline becomes measurable
Why not higher risk: Personal video still valuable for sales/onboarding, Atlassian integration
8. Mailchimp - Email marketing
The core issue: Double disruption—specialized tools winning each vertical (Beehiiv for creators, Klaviyo for e-commerce) AND email declining as the primary communication channel.
Current metrics: 11M+ users, acquired by Intuit for $12B
Leading indicator: New creators and businesses choosing specialist tools or de-emphasizing email
Timeline: 2027-2028 new customer acquisition weakens
Why not higher risk: Massive existing customer base, Intuit distribution, brand recognition
Medium Risk: Enterprise Protected, New Builder Risk
9. Slack - Team communication
The core issue: AI enables solo builders and tiny teams to accomplish what required larger teams. Small teams don’t need the coordination overhead. But enterprise remains sticky.
Current metrics: 20M+ DAU, owned by Salesforce
Leading indicator: Indie hackers and small teams not mentioning Slack in tech stacks
Timeline: 2027-2028 small team pipeline thinning becomes visible
Why medium not high: Large enterprises sticky, Salesforce integration, team coordination at scale still needed
10. Asana - Project management
The core issue: AI-augmented teams are smaller and coordinate where work happens (Linear, GitHub). Formal PM feels like overhead for 2-5 person teams. But mid-market and enterprise still need coordination.
Current metrics: 145K+ paying customers, $600M+ revenue
Leading indicator: New startups defaulting to Linear or no formal PM
Timeline: 2027-2028 startup pipeline questions emerge
Why medium not high: Enterprise deeply embedded, non-technical teams value flexibility, cross-functional coordination still needed
11. HubSpot - Marketing automation
The core issue: New customer acquisition models (product-led, community-led, AI-driven) don’t map to HubSpot’s campaign-based workflows. Early-stage companies starting elsewhere. But mid-market B2B still needs platforms.
Current metrics: 200K+ customers, $2B+ revenue
Leading indicator: Early-stage startups using lighter tools or PLG approaches
Timeline: 2027-2028 early-stage adoption decline shows in metrics
Why medium not high: Mid-market B2B strong, enormous existing base, product breadth beyond marketing, agency ecosystem
Risk Distribution Summary
Risk Level Count Companies High 5 Figma, Zapier, Miro, Airtable, Webflow Medium-High 3 Canva, Loom, Mailchimp Medium 3 Slack, Asana, HubSpot
The Pattern Across All 12
Every company in this analysis shares the same pattern:
Phase 1 (Current): Strong financial metrics showing installed base strength. Enterprise customers sticky. Revenue looks healthy.
Phase 2 (2026-2027): New builder adoption slowing. The cohort starting their first projects in 2024-2025 is forming habits elsewhere.
Phase 3 (2027-2028): Pipeline crisis becomes visible in customer acquisition metrics. By the time it shows, the next generation has already formed different habits.
The key insight:
Current metrics are lagging indicators. They show you the installed base working on old workflows.
Where new builders are starting is the leading indicator. It predicts revenue 12-24 months out.
And right now, across multiple categories, new builders are starting elsewhere.
What Makes This Different From Other Disruption
This isn’t just “new technology making old tools obsolete.” It’s deeper:
Previous disruptions:
Desktop → Mobile: Same workflows, different interface
On-premise → Cloud: Same software, different deployment
Sketch → Figma: Better version of the same tool
This disruption:
AI is eliminating workflows entirely, not just making them better
The paradigm shift is “what work needs to be done,” not “how to do the work”
Products built for human→human workflows don’t translate to human→AI workflows
Example:
Figma made design collaboration better
But AI-native development doesn’t have a design phase to collaborate in
The workflow itself disappeared
The Investment Thesis
If this framework is accurate, there’s a 12-18 month window to act:
For investors:
Short opportunities:
Companies with strong current metrics but frozen new customer pipelines
High Risk companies where workflow elimination is clear
Look for: declining new logo acquisition, high enterprise concentration
Long opportunities:
Tools new builders are actually using (v0, Cursor, Linear for dev, Beehiiv for creators)
Infrastructure-layer companies that are workflow-agnostic
Companies successfully rebuilding around AI (GitHub as example)
The timing edge: This is equivalent to identifying mobile-first companies in 2009-2010 while desktop incumbents posted record growth. The metrics won’t show disruption until 12-18 months after new builder cohorts have formed habits elsewhere.
For operators:
If you work at one of these companies:
High Risk: 6-12 months to pivot your skillset
Medium-High Risk: 12-18 months to prepare
Medium Risk: Monitor closely, prepare contingencies
Focus on: AI workflow design, strategic oversight, exception handling. The shift is from execution to direction.
For founders:
If you’re building in a category with incumbents:
This is your window
New builders will choose tools designed for AI-native workflows
Don’t compete on features—compete on workflow paradigm
The quicksand companies won’t see you coming until their metrics show it
Track Record & Accountability
Each evaluation includes:
Specific predictions with timelines
Observable metrics to check
“What would prove this wrong” criteria
Date to revisit (December 2026)
We’ll revisit every evaluation in 12 months to see which predictions held and which didn’t.
This isn’t speculation—it’s a falsifiable framework with clear success criteria.
How to Use This Research
If you’re evaluating other companies:
Apply the four questions:
When did they reach PMF? (Pre or post-ChatGPT)
What workflow assumptions are baked in?
How are they responding to AI? (Bolt-on or rebuild)
Where are new builders starting? (The leading indicator)
If you’re tracking these 12:
Watch for:
New customer acquisition trends (not just revenue)
“How I built this” content from 2025-2026 builders
Which tools appear in new project documentation
Whether AI-native workflows mature as predicted
If you disagree:
Good. This framework is designed to be challenged. Each evaluation specifies what would prove it wrong. If you see evidence contradicting the thesis, that’s valuable data.
The goal isn’t to be right about every company. The goal is to identify a pattern that helps us understand which products are being aged out by AI workflows.
The Complete Series
Read all 12 evaluations:
High Risk:
Medium-High Risk: 6. Canva: A Quicksand Evaluation 7. Loom: A Quicksand Evaluation 8. Mailchimp: A Quicksand Evaluation
Medium Risk: 9. Slack: A Quicksand Evaluation 10. Asana: A Quicksand Evaluation 11. HubSpot: A Quicksand Evaluation
Plus: The Quicksand Companies Framework (full methodology)
About This Research
This analysis is part of The Heed Report, where we track AI disruption patterns, analyze production deployment data, and identify where the next generation of builders is actually working—not where incumbents say they should be.
The Quicksand Evaluations represent systematic application of our framework to predict which software products are being aged out by AI workflows.
We’ll track these predictions over the next 12-24 months to build a public track record of accuracy.
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.