Figma’s $20B IPO Tests SaaS in Agentic Era
Figma’s valuation assumes AI mastery its S-1 doesn’t prove. This disconnect reveals critical lessons about Agentic Era Discontinuity.
Decoding Discontinuity Insights provides actionable strategic frameworks in the context of the generative AI Discontinuity, empowering decision-makers in moments of uncertainty. This month, Insights clients who have subscribed to our Institutional tier get exclusive access to a 23-page report that applies our Durable Growth Moat lens to the prospectus of Figma. For qualified institutional investors, contact us to tailor our expertise to your portfolio.
Figma's S-1 filing is now available, and it highlights the primary challenge facing the entire software industry. Over 1,200 unicorn companies globally hold a combined valuation north of $4.1 trillion, with software representing the largest category. The problem? Most achieved their valuations during the SaaS 2.0 era and are now facing a critical transition into Software 3.0, where autonomous agents are reshaping every workflow.
At the median age of eleven years, these unicorns occupy an awkward position. Too established to claim AI-native status, too recent to possess deep enterprise entrenchment that traditionally defends against paradigm shifts. This creates the "unicorn transition trap," where companies must simultaneously defend existing business models while fundamentally re-imagining their role in an agentic future.
Figma represents the first real-world test case of such a company going public. At thirteen years old, it embodies a SaaS 2.0 champion forced to defend its throne in a new technological paradigm.
And yet, there is little public recognition of Figma being at a complex crossroads. Instead, its IPO filing has been greeted with triumphant reviews, praising it as a conquering hero of the SaaS to AI transition. There is widespread expectation that its opening market value may top the $20 billion Adobe had offered to pay for Figma before regulators scuttled the deal in late 2022.
This optimism is understandable. By traditional SaaS metrics, Figma is killing it. I certainly can see why some may view these numbers as confirmation that Figma has built the foundation of an almost unassailable moat that it can use to transition into AI leadership.
In sharp contrast to this unbridled bullishness, I have a much more reserved outlook regarding Figma’s future. Today, we published our latest Insights report, “Figma in the Age of Software 3.0,” applying our Durable Growth Moat framework to the S-1. While the report is exclusively for our clients, I want to share my bottom-line assessment:
“Figma is a beautifully engineered SaaS 2.0 company being valued for a future it has not yet earned."Am I being overly pessimistic? Or are markets missing a huge red flag?
I want to break down the reasons for this apparent disconnect because it goes to the heart of the strategic and technical trends that I believe investors and business leaders must urgently understand as we enter the Agentic Era Discontinuity.
The Agentic Narrative Challenge
Figma's S-1 filing provides the first comprehensive view of how a premier high-growth SaaS company navigates agentic transition while preparing for public markets. The operational metrics position it among elite enterprises: 46% year-over-year growth, 132% net dollar retention, 91% gross margins, $1.5 billion cash with zero debt.
That success is undeniable. The company has done a stellar job emerging from the rubble of the Adobe deal, which collapsed about the same time the first public version of ChatGPT was released. Pick any metric you want, but users love Figma, and it has become a vital part of workflows. No doubt that it is tempting to use the classic backward-looking valuation frameworks and the company’s recent execution to conclude that the next couple of years will be more of the same for Figma.
The problem here, in my view, is that Figma boosters – and the markets more generally – have not begun to appreciate the potential for Agentic Systems to tear down even the sturdiest of moats.
So much of the analysis and prognostication surrounding Figma is based on SaaS metrics and playbooks that agentic AI will make obsolete.
Certainly, one can’t expect a company such as Figma to have a fully developed agentic strategy in place. As I wrote recently, the shape of agentic infrastructure and protocols is still being defined and evolving rapidly.
But what companies can – and should – be doing now is openly acknowledge the agentic wave and spell out a clear vision for markets to understand their positioning. Even if one can’t know all the technical details, stepping back and taking a larger view offers a chance to recognize how the agentic AI may shift value creation in each industry.
Developing a robust agentic narrative demands more than AI feature announcements and empty buzzwords. It requires a coherent business story that demonstrates how a company foresees the transformation that will be driven by agentic AI.
By articulating the broad strokes of this vision, leaders can use this as a guide to eventually connect autonomous agents to measurable financial impact. Again, this is more than PR spin. As professor Aswath Damodaran consistently emphasizes, valuations emerge from “business stories” that link soft data to financial outcomes.
The challenge centers on translating agentic capabilities into tangible metrics across revenue impact, margin expansion, and business model resilience against agent-driven commoditization while capturing sustainable competitive advantages. Most critically, agentic narratives must address both revenue risk and revenue opportunity. The risk involves potential compression where AI-driven productivity reduces human seat requirements. The opportunity centers on AI democratization, enabling broader adoption, new use cases, and enhanced value propositions justifying premium pricing.
Software 3.0 fundamentally alters knowledge work categories that form SaaS customer foundations. As defined by OpenAI co-founder Andrej Karpathy, this paradigm enables large language models to serve as general-purpose computing platforms where natural language prompts function as programs. For seat-based platforms, this creates dual dynamics where AI productivity improvements among existing users could reduce seat requirements, while AI accessibility could expand addressable user bases by lowering adoption barriers.
The broader risk involves workflow abstraction, where agentic systems coordinate entire processes through standardized protocols, relegating human-centric platforms from primary interfaces to commoditized backend utilities. This same shift creates opportunities for platforms to position themselves as orchestration layers coordinating agent activities rather than being circumvented.
Figma's S-1: The First Reality Check
Figma's filing exposes a profound disconnect between the current AI narrative and the agentic future.
The first troubling sign is the lack of visibility into the financial impact of current generative AI features and products. The company mentions artificial intelligence over 150 times while demonstrating zero quantifiable revenue from AI initiatives. Despite allocating 40% of incremental R&D investment toward AI capabilities in 2024, representing hundreds of millions in spending, the S-1 provides no revenue attribution to AI features, no cost savings metrics from AI implementation, and no quantified productivity gains from AI tools.
Though the S-1 doesn’t clearly demonstrate the upside of Figma’s GenAI products, it does acknowledge the AI risk with remarkable candor: "There could be a decrease in the number of designers, developers, and other collaborators that use our platform if such individuals are able to significantly increase their efficiency through the use of AI capabilities alongside or instead of our platform. Such a decrease could reduce the number of seats that customers or potential customers subscribe to."
This disclosure exposes both the challenge and the opportunity.
While Figma's user base encompasses personas susceptible to AI productivity improvements, the same capabilities could democratize design tools for non-designers, potentially expanding addressable markets significantly. The platform strategy, showing 76% of customers utilizing at least two products, positions it to capture expansion from AI-enabled use cases.
However, key methodological limitations throughout the document compound investor concerns. Our Insights research found that "the 91% gross margin likely excludes the significant cost of serving millions of free users, understating the true cost structure by several percentage points." Combined with selective retention metrics, though not uncommon for product-led-growth companies, this creates uncertainty about true unit economics during agentic transition.
Strategic Agentic Awareness?
Figma demonstrates initiatives suggesting strategic awareness of agentic transition requirements. The critical question remains whether awareness will translate into successful execution and measurable business impact. Early efforts indicate understanding of orchestration principles while highlighting execution gaps that will determine winners and losers.
The beta of the Model Context Protocol server for Dev Mode, which Figma announced in early June, represents a direct attempt to control design-to-code workflows by providing structured context to external AI agents. This positions Figma as a potential orchestrator rather than just a tool that agents could bypass through standardized protocols. Our research identifies this as "early orchestrator ambition indicators," where "the beta release of a Model Context Protocol server for Dev Mode is a direct attempt to control the design-to-code workflow by providing structured, semantic context to external AI coding agents."
New products demonstrate intent abstraction capabilities expanding beyond traditional design workflows. Figma Sites enables website creation from designs, Figma Buzz targets marketing asset creation, and Figma Slides addresses presentation workflows. These capabilities could democratize design-adjacent activities for non-designers while creating new revenue streams beyond traditional seat expansion.
Figma Make transforms natural language prompts into interactive prototypes, representing shifts toward goal-based user experiences. The company's 2025 AI report indicates 51% of Figma users working on AI products develop agentic tools, validating transition urgency while highlighting adaptation requirements. But the S-1 provides no metrics on AI feature adoption rates, revenue contribution from agentic capabilities, or competitive differentiation from agent-native functionality.
More problematic, in my view, is that Figma has not clearly explained its broader agentic vision. That makes it hard to know whether or how the company may address some agentic gaps our analysis revealed: "Despite these ambitions, Figma currently lacks the core infrastructure of a true orchestrator, such as dedicated agent SDKs, persistent memory systems for agents, and dynamic task-routing capabilities."
The Hard Data Imperative
As I noted above, strategic narratives are vital, but public market investors eventually will base their judgments on measurable outcomes. This is why it is problematic that Figma has not done more to reveal details of the impact of its current generative AI products and features. Functions that cannot demonstrate quantified revenue impact, margin expansion, or competitive differentiation receive significant valuation discounts.
Evidence for successful transition to the Agentic paradigm must manifest in quantifiable metrics. Agent-driven revenue expansion should appear through new customer segments enabled by AI democratization, not just productivity gains among existing users. Cost efficiency gains from AI automation should reflect in margin expansion, while new AI features demonstrate pricing power and competitive differentiation.
For Figma specifically, success indicators include measurable revenue from AI features like Figma Make and Figma Sites, demonstrated market expansion through AI-enabled user acquisition in non-designer segments, and retention improvements driven by multi-product adoption enabled by AI accessibility. The platform's evolution toward supporting marketing, presentation, and website creation workflows suggests potential for significant market expansion beyond traditional design tools.
Our research methodology evaluates these dynamics through the "Architectural Resilience Assessment Framework," measuring protocol integration risks, orchestration opportunities, and business model durability across agentic transition. Companies successfully navigating this assessment demonstrate both defensive positioning against commoditization and offensive capabilities for market expansion.
The Software Landscape Reckoning
Figma represents the first of many high-growth SaaS companies facing public market scrutiny during the agentic transition. The key requirement involves moving beyond the AI narrative toward quantified business impact, demonstrating both risk mitigation and opportunity capture across revenue, margins, and competitive positioning.
Winners will control orchestration layers, coordinating autonomous agents while expanding addressable markets through AI democratization. They will develop authentic business stories supported by measurable financial metrics reflecting both traditional SaaS excellence and agentic transformation success.
The stakes extend beyond individual company success toward reshaping the entire software industry structure. The agentic era will create winners and losers with unprecedented speed, making the ability to translate AI features and products into measurable business outcomes essential for sustainable competitive advantage.
For founders preparing exits and investors evaluating opportunities, the imperative extends beyond identifying companies with impressive historical metrics toward understanding which platforms possess an architectural foundation and execution capability to thrive in expanded markets enabled by agentic capabilities.
Acceleration of AI advancements compresses transition windows while increasing both adaptation stakes and expansion opportunities. Companies cannot simply optimize existing models while experimenting with AI features. Agentic transitions demand immediate architectural transformation while maintaining growth trajectories reflecting both traditional excellence and emerging market expansion.
The game has changed. Historical SaaS metrics are insufficient. The ability to dissect architectural resilience and quantifiable progress in agentic transition has become the most critical skill for successful software investing. Figma's public market journey will be the first and most important chapter in that story.
Part 2. Figma S-1 Teardown
Durable Growth Moat Analysis
We applied our pioneering Advanced Growth Intelligence (AGI) analytical framework to the prospectus of Figma, a high-profile SaaS public offering. This 23-page teardown examines Figma’s business model in granular detail to test its Durable Growth Moat and is available exclusively to Insights clients as part of our Institutional tier.
Our comprehensive analysis examines Figma’s current business and provides a stress test of its preparedness for the agentic future, covering in granular detail such topics as:
Quality of Financial Fundamentals (incl. Revenue, Growth, Margins, and Balance Sheet)
Agentic Bypass Risk and Orchestration Opportunity
Intrinsic Value Analysis and Peer Benchmark
This robust teardown combines market-level insights on where Figma fits into the broader discontinuity driven by AI and agentic systems. This detailed evaluation of Figma’s specific advantages and vulnerabilities is essential reading for institutional investors developing exposure strategies amid the transition to the Agentic Era.
This analysis draws from a comprehensive evaluation of Figma's S-1 filing, including detailed financial analysis, architectural resilience scoring, and Durable Growth Moat frameworks.
For qualified institutional investors seeking to capitalize on technological Discontinuities, contact us directly to discuss how Decoding Discontinuity Insights can be tailored to your organization’s investment focus and allocation scale.
Raphaëlle D’Ornano