In 2025, major tech companies like Airtable and Handshake announced they were “refounding” their startups. The announcement sparked debate about whether this is genuine transformation or Silicon Valley buzzword engineering.
The confusion is understandable. What does refounding actually mean? Is it different from the pivots we’ve been executing for years?
This article clarifies what refounding is, how it differs from pivoting, and helps you assess whether the concept applies to your organisation. We’ll cover core definitions, key distinctions from pivoting, institutional drift as a motivating factor, and the characteristics of refounding initiatives.
For a broader strategic context, see our comprehensive guide to startup refounding.
What Is Startup Refounding?
Startup refounding is a comprehensive organisational transformation where mature companies fundamentally restructure their business models, culture, and value propositions. Unlike incremental changes, refounding involves rebuilding core aspects of the organisation to regain startup-like agility and intensity.
The 2025 refounding wave is driven by AI transformation. Established companies are rebuilding around AI-native architectures rather than adding AI features incrementally.
Airtable popularised the term in June 2025, stating that “instead of just adding more A.I. capabilities to our existing platform, we treated this as a refounding moment for the company.” CEO Howie Liu emphasised this wasn’t about fixing mistakes. Instead, he chose “the language of founding because the stakes feel the same.”
Refounding affects product strategy, organisational culture, team composition, and how the company creates and delivers value.
The concept applies to mature startups—companies 5-15 years old with established products and culture. It’s not for early-stage companies still finding product-market fit.
Current refounding is AI-centric because generative AI represents a fundamental technology shift. Incumbents face pressure from AI-native startups whilst dealing with organisational structures optimised for the pre-AI era.
For more on when refounding applies, see our decision framework for refounding vs pivoting.
How Does Refounding Differ from a Traditional Pivot?
A pivot is a strategic direction change in response to market feedback or failed assumptions. You adjust your product or target market whilst maintaining your organisational structure. Refounding is a comprehensive organisational rebuild affecting culture, business model, and operations—not just product direction.
A pivot changes what you build. Refounding changes how your organisation operates.
Pivots preserve existing team dynamics and processes. Refounding deliberately disrupts culture to restore “startup intensity.”
Pivoting responds to external market signals. Refounding addresses internal organisational drift and positions for fundamental technology shifts.
The time horizon differs as well. Pivots can execute in months. Refounding is a multi-year transformation.
For two decades, startups relied on pivot strategies, shifting direction based on market feedback. The current AI-driven refounding trend represents a departure from that incremental adjustment approach.
Consider Instagram’s pivot from Burbn to photo-sharing. The team maintained their culture and dynamics whilst changing product direction. That’s a classic pivot.
Now compare that to Handshake’s refounding. They implemented mandatory five-day office weeks with expectations for employees to operate “with a pace and number of hours that is meaningful and will help us hit goals.” That’s a cultural reset, not a product adjustment.
The distinction matters because it helps you assess what your organisation actually needs. If your product direction is wrong but your culture and operations are healthy, pivot. If institutional drift has eroded your agility whilst AI-native competitors are gaining ground, you might need to refound.
For concrete case studies, see our analysis of real examples of refounding.
What Is Institutional Drift and How Does It Lead to Refounding?
Institutional drift is the gradual erosion of startup culture, agility, and intensity as organisations mature. You accumulate processes, bureaucracy, and organisational bloat. Decision-making slows, risk-taking declines, and process overhead increases. The urgency and focus that characterised your founding period fades.
Think of it like technical debt. Both accumulate gradually. Both eventually require comprehensive restructuring rather than incremental fixes.
Research from Yale examines how iconic companies—Nike, Starbucks, Boeing, Target, and Intel—lost their foundational identity through institutional drift rather than isolated failures.
Boeing provides a stark example. The 1997 McDonnell Douglas merger introduced financial optimisation priorities that eroded the company’s commitment to technical rigour.
The manifestations are familiar. Meeting proliferation. Approval layers. Risk-averse culture. Slowed innovation cycles. The “that’s not how we do things” mentality.
Garrett Lord, Handshake’s CEO, explicitly cited institutional drift as his refounding motivation. He stated: “There are times in your life when you’re like, ‘Oh gosh we could not be more well-positioned.'”
But he recognised the competitive urgency: “Winners and losers are being defined right now.”
Refounding aims to reverse institutional drift by deliberately resetting organisational culture, eliminating accumulated processes, and restoring founder-era focus.
For strategies on addressing drift, see our guide to cultural transformation during refounding.
Why Are Startups Refounding Now in 2025?
The 2025 refounding wave is driven by competitive pressure from AI-native startups that threaten to disrupt established platforms. Generative AI represents a fundamental technology shift requiring architectural rebuilding, not just feature addition.
The numbers tell the story. AI-native startups reach $1 million revenue in 11.5 months versus 15 months for traditional SaaS firms, whilst 74% of legacy companies struggle to derive value from AI adoption.
At the AI application layer, startups captured nearly $2 in revenue for every $1 earned by incumbents—63% of the market, up from 36% when enterprises still held the lead.
AI-native startups are building products with fundamentally lower cost structures, leveraging large language models to deliver functionality that previously required massive engineering teams.
Companies need to signal to investors and customers that they’re fundamentally AI-transformed, not just adding AI features. The market rewards AI-native positioning over “AI-washed” feature additions.
The window of opportunity matters. Companies recognise limited time to refound before AI-native competitors capture market share.
For a broader view of AI transformation strategies, see our overview of refounding strategies.
What Are the Key Characteristics of a Refounding Initiative?
Refounding initiatives combine business model innovation, cultural transformation, technical architecture changes, and market repositioning. All four dimensions move together.
Leadership commitment is required. Refounding needs CEO and board alignment, multi-year timelines, and acceptance of short-term disruption.
Cultural markers include returning to “startup intensity.” That means long hours and reduced remote work. It means eliminating bureaucratic processes and restoring founder-era urgency.
Handshake provides the clearest example. They told employees they have to be back in the office five days a week, operating with a pace and number of hours that helps them hit goals. CEO Garrett Lord announced a strategic pivot toward AI with a 15% workforce reduction affecting approximately 100 employees from a U.S. staff of 650.
The technical dimension separates refounding from feature additions. Adding AI features means recommendation engines, chatbot interfaces, and automated workflows built atop existing architecture. Refounding means data pipelines optimised for model training, inference at architectural centre, and product experiences redesigned for AI-native interactions.
The technical parallel: adding a mobile website vs rebuilding mobile-first. Refounding addresses architectural technical debt that prevents true AI integration.
Airtable transformed from a no-code collaboration tool by revamping its product structure and pricing in June, adding AI assistant “Omni” as a standard feature and repositioning as an “AI-native app platform.”
Opendoor CEO Kaz Nejatian stated: “We are refounding Opendoor as a software and AI company. In my first month as CEO, we’ve made a decisive break from the past — returning to the office, eliminating reliance on consultants, and launching over a dozen AI-powered products.”
Success requirements include board support, financial runway, leadership alignment, and change management capability. Risk factors include employee retention challenges, execution complexity, market timing, and customer disruption.
For specific implementations, see our Airtable and Handshake case studies.
Is Refounding Right for Every Mature Startup?
Refounding is not universally applicable. It suits mature startups facing serious competitive pressures or experiencing severe institutional drift.
Companies with healthy growth, strong market position, and functional culture may achieve better outcomes through incremental AI adoption.
Refounding requires adequate financial runway for multi-year transformation, strong leadership alignment, and willingness to accept short-term disruption and potential employee attrition.
Refounding makes sense when severe institutional drift threatens competitiveness, when AI-native competitors pose serious market threats, when your current business model is fundamentally incompatible with AI transformation, when you have strong financial position to support multi-year transformation, and when your board and leadership are aligned on comprehensive change.
An incremental approach works better when you have healthy growth and market position, when gradual AI adoption addresses competitive needs, when your culture remains functional and agile, in risk-averse contexts with limited runway or retention concerns, and when your technical architecture supports AI integration without rebuild.
You need to evaluate your situation across multiple dimensions. How quickly are AI-native competitors gaining share? Is institutional drift severe or manageable? Can your organisation sustain multi-year transformation? Does your current platform require rebuild or support integration?
Incremental innovation remains a viable strategy for many organisations. Not everyone needs to refound.
For detailed assessment tools, see our how to decide if refounding is right.
FAQ Section
Here are answers to common questions about startup refounding:
What companies have announced refounding initiatives?
Airtable announced a refounding in June 2025 focused on AI transformation and platform expansion. Handshake implemented a comprehensive refounding including mandatory 5-day return-to-office and cultural reset to combat institutional drift. Opendoor positioned its transformation around AI-integrated real estate technology. These companies share characteristics: mature startups (5-15 years old), facing AI-native competitive pressure, and experiencing institutional drift.
Does refounding mean the original business failed?
No—refounding addresses success-induced institutional drift, not failure. Companies refound because they’ve matured and accumulated bureaucracy that now limits competitiveness. The original business succeeded but organisational structure optimised for the previous era now creates barriers. Refounding is proactive transformation in response to technology shifts, not reactive response to failure.
How long does a startup refounding take?
Refounding is a multi-year transformation, typically 2-3 years for meaningful cultural and technical change. Initial phases—announcement, policy changes, cultural reset—occur in 6-12 months. Technical platform rebuilds around AI require 18-24 months. Cultural transformation is ongoing. Restoring startup intensity whilst managing employee retention takes sustained effort beyond initial announcements.
Will refounding cause employee attrition?
Yes, refounding typically causes some attrition, especially from cultural changes like RTO mandates and “startup intensity” expectations. Companies accept this attrition as necessary for cultural reset. The critical question: Does attrition affect key contributors or primarily self-selection of culture misfits? You must balance cultural transformation goals against retention of technical talent.
Can you refound without implementing return-to-office?
RTO is not definitionally required for refounding, though many refounding companies implement it as a cultural transformation tool. The core requirement is restoring startup intensity—rapid decision-making, reduced bureaucracy, increased focus. Some companies might achieve this through distributed models with strong communication and decision-making norms. However, many executives believe physical presence enables the collaboration intensity they seek, hence RTO prevalence in refounding initiatives.
Is refounding just for AI transformation or applicable to other technology shifts?
The current 2025 refounding wave is AI-centric because generative AI represents a fundamental architectural shift. However, the refounding concept could apply to any technology transition requiring comprehensive organisational restructuring. Historical examples include mobile-first transformations (2010-2014) or cloud migrations. What distinguishes refounding from gradual technology adoption is the comprehensive organisational scope—business model, culture, and architecture—not just product features.
How do investors view refounding initiatives?
Investor perspective depends on execution credibility and competitive context. Refounding signals recognition of AI transformation imperative, which investors value. However, investors scrutinise execution capability—does leadership have a track record for managing transformations? Financial implications matter: refounding requires investment runway and may depress short-term metrics. Companies must balance transformation investment against growth expectations. Successful refounding can unlock new valuation multiples through AI-native positioning.
How do you measure refounding success?
Current refounding discourse lacks clear metrics frameworks. Potential measurement dimensions: Cultural metrics (decision velocity, process overhead reduction), technical metrics (AI integration depth, platform capabilities), business metrics (market positioning, competitive win rates), team metrics (retention of key talent, attraction of AI-specialised hires). You need 30/60/90 day indicators showing transformation progress vs disruption costs.
What happens if a refounding initiative fails?
Refounding failure scenarios are underexplored. Potential failure modes: excessive attrition of key talent, cultural transformation backfires creating dysfunction, technical platform rebuild falters, market rejects new positioning, or competitors move faster despite transformation effort. Failed refounding leaves companies worse off—disrupted culture, depleted resources, damaged morale, lost time against competitors. This downside risk explains why risk assessment frameworks are needed when evaluating whether to refound.
Can smaller startups (under 50 employees) refound?
Refounding addresses institutional drift in mature organisations. Smaller startups typically haven’t accumulated the bureaucracy and culture loss that motivates refounding. Early-stage companies pivot or iterate rather than refound. Refounding applies to companies roughly 5-15 years old with 100+ employees where institutional drift manifests. Smaller organisations experiencing cultural issues should address those directly rather than adopting refounding framing designed for mature companies.
What role does the CTO play in a refounding initiative?
Technical leaders are central to refounding success. The role includes assessing technical architecture implications, leading platform rebuilds, evaluating team capabilities for AI transformation, and managing technical talent through cultural disruption. Responsibilities include: honest assessment of whether current architecture supports AI integration or requires rebuild, risk evaluation of transformation vs incremental approach, technical roadmap for platform evolution, hiring strategy for AI capabilities, and retention strategy for technical talent during cultural changes. You must balance technical transformation ambitions against execution risk and team capacity.
