Re-founding: The Future of Software Companies in AI

Re-founding is the key question for software companies worldwide today: should they integrate AI into existing structures or start anew?

This term, embraced by the industry, highlights the magnitude of this decision. Companies like Airtable, Handshake, Opendoor, Block, MoneyGram, and Atlassian have all referenced it in the past year. The implication is clear: this isn’t just a new feature or minor update; it’s a critical pivot for the organization.

The Context of Re-founding

Significant changes surround his terminology. TrueUp reports that over 90,000 tech employees were let go in the first 97 days of 2026, averaging 933 layoffs each day. In March 2026, Oracle executed the most extensive single-day layoffs in tech history, parting ways with 30,000 staff members to facilitate a $2.1 billion AI infrastructure overhaul. Block also decreased its workforce by 40%.

Atlassian reduced its employee count by 1,600, even as cloud revenue experienced a 26% year-on-year growth. Meta is contemplating up to 15,000 additional job cuts while committing $115-$135 billion in AI capital expenditure for 2026, following substantial reductions in 2025, which saw over 124,000 layoffs among more than 271 tech firms.

These are not minor adjustments. Yet, do they signify the most significant reallocation of corporate resources from human capital to AI infrastructure ever seen?

The critical question is whether this shift will result in true transformation or if the rhetoric surrounding re-founding merely offers a more acceptable narrative for what would typically be termed layoffs in any other period.

The reality is that the outcome depends heavily on the approach taken by each company.

The Challenges of Re-founding Software Companies

Transitioning existing companies to AI-native status poses challenges, as building such a company differs fundamentally across nearly every organisational aspect. A framework from Redpoint Ventures illustrates this starkly.

In traditional software, the focus is on hiring executives with prior experience. In contrast, AI-native firms require first-principles thinkers since the landscape is largely uncharted in this context. The traditional model of product development is turned on its head: while traditional SaaS is driven by customer needs, AI-native teams must grasp what technologies are capable of and adapt accordingly, shifting focus from demand to potential.

The economics also shift. Traditional SaaS companies often operate with 75-80% gross margins and minimal additional costs per user. In contrast, AI-native firms typically experience 50-60% blended margins, facing real inference costs that correlate with usage. Additionally, engineering transitions from deterministic to probabilistic systems, requiring new quality assurance and testing methodologies.

Sales strategies evolve as well, moving from pre-packaged products to a field deployment engineering approach, where initial efforts focus on proof of concept along with substantial customer education. Pricing might shift from predictable ARR based on seats to consumption or outcome-based models, which remain experimental.

This illustrates why adding AI features to a traditional SaaS product and branding it as re-founding may represent more of a performative act rather than a lasting transformation. Genuine re-founding necessitates simultaneous changes in organisational structure, margin frameworks, sales methodologies, and product development processes.

Interestingly, this analysis counters the prevailing pessimistic narrative. When AI decreases coding production costs, businesses tend to create more software, not less—an example of Jevons Paradox in action.

Data from Citadel Securities, sourced from Indeed, indicates that job postings for software engineers have risen by approximately 11% year-on-year, despite an overall decline of 5.2% in Indeed’s job listings. TrueUp also reports that software engineering roles have doubled since their low point in mid-2023, with over 67,000 vacancies across 9,000 monitored companies.

There is a rising demand for software. However, the nature of the software being developed, the teams constructing it, and the business models supporting it are evolving.

The Spectrum of Execution in Re-founding

Satya Nadella stands out as the most successful re-founder in contemporary corporate history. Upon taking leadership of Microsoft in 2014, the company had missed the mobile revolution, was losing ground to AWS in cloud services, and faced cultural fragmentation due to internal silos and titles.

Microsoft was stuck in a cycle it had previously mastered while growth shifted to other areas.

Nadella’s re-founding was effective because it addressed multiple facets at once. He exited failing markets, closing the Nokia mobile division instead of persisting with losses.

He identified the next platform before it became mainstream, establishing Azure as the company’s main focus rather than Windows. He transformed the culture from one of arrogance to one of learning. Additionally, he facilitated a multimillion-dollar partnership with OpenAI before many firms had formulated their AI strategies, hiring Mustafa Suleyman to lead Microsoft AI.

The outcome: Microsoft’s market capitalisation surged from around $300 billion to over $3 trillion within ten years, with revenue reaching $281.7 billion in the fiscal year 2025.

In January 2026, Nadella launched a personal blog where he declared the year to be a turning point for AI, emphasizing that the sector must adapt from models to systems. He admitted that the forthcoming phase would likely be chaotic. However, the Nadella playbook sets a clear benchmark: maintain what makes the company strong (developer relationships, enterprise connections, platform foundation) while eliminating what hinders progress (Windows-centric focus, internal competition, distractions from hardware). Re-founding isn’t about erasing the past; it’s about enhancing it.

Examples of Contemporary Re-founders

Among current re-founders, execution quality varies widely.

Handshake is a frequently cited example. The company established its new direction before publicising it, growing an AI division from zero to $100 million in annualised revenue in just eight months by shifting from a career platform to an expert network for AI post-training.

The AI department expanded from 15 to 150 employees, and the five-day return-to-office policy, combined with a cultural reset, formed a coherent strategy. CEO Garrett Lord remarked that winners and losers are being defined in real-time. Handshake demonstrated its business case first before announcing the re-founding—a sequencing that appears critical.

Airtable represents a conviction-driven initiative. CEO Howie Liu intentionally opted for “re-founding” instead of “relaunch” or “transformation,” stating that the stakes felt identical. The company unveiled Superagent in January 2026, its first standalone product in over a decade.

Airtable acquired DeepSky for multi-agent coordination capabilities and made AI the standard across all pricing tiers, including the free version. The company’s valuation has dropped roughly 66% from its peak in 2021 to approximately $4 billion on secondary markets. Nevertheless, Liu asserts that the company is cash-flow positive and retains half of its raised capital.

While it remains to be seen, the commitment to product depth appears substantial.

Opendoor exemplifies the risks associated with invoking re-founding language absent a solid operational basis. New CEO Kaz Nejatian proclaimed that they are re-founding Opendoor as a software and AI company. Yet quarterly results presented a different narrative, with revenues plummeting to $915 million from $1.57 billion in the previous quarter, a greater-than-expected loss, and contribution margins dropping to 2.2%. Following the announcement, the stock fell 23% in after-hours trading. Genuine re-founding necessitates credibility, which demands tangible results or, at the very least, a visible pathway toward them.

The patterns observed in these examples are insightful. Handshake validated its approach before announcing, Airtable made genuine commitments, and Opendoor pursued narrative before achieving supportive numbers.

Each case uses the same terminology, but the substantive content differs significantly.

The Talent Paradox

For any organisation contemplating re-founding, the implications for talent merit careful consideration.

Re-Founding in Software: Understanding the Shift

Re-founding signifies a pivotal change in how businesses approach AI technology and its consequences for employment. Recent academic data illustrates this nuanced transition.

Employment Trends and AI Adoption

A Harvard study conducted by Hosseini and Lichtinger in 2025 tracked 62 million workers across 285,000 U.S. firms. The findings revealed a decline of 7.7-10% in junior employment within six quarters at firms embracing generative AI. Interestingly, senior employment levels in these companies continued to rise. This phenomenon has been referred to as “seniority-biased technological change.”

Importantly, the reduction in junior employment is not occurring due to layoffs but rather a noticeable stagnation in new hiring. The pipeline for entry-level roles is diminishing.

Data Insights from Stanford

A study from Stanford’s Digital Economy Lab, led by Brynjolfsson, Chandar, and Chen, analysed payroll data from ADP. It reported an almost 20% drop in employment for software developers within the age bracket of 22 to 25 from its peak in late 2022 to mid-2025, while employment for those older than 26 remained stable or increased. The divergence in numbers began following the launch of ChatGPT in November 2022.

The Economic Impact of AI

MIT’s Project Iceberg, in collaboration with Oak Ridge National Laboratory, estimates AI technology could perform tasks equivalent to 11.7% of the U.S. workforce, equating to around $1.2 trillion in wages. Presently, however, AI implementation is concentrated within just 2.2% of the workforce. This disparity between potential capabilities and actual deployment will shape the following five years.

Job Growth Despite AI Automation

The Vanguard 2026 economic forecast presents a complementary overview. It found that around 100 occupations facing significant exposure to AI automation are actually surpassing the broader labour market in job growth and real wage rises. Professionals adept at utilising AI tools are becoming more valuable, instead of being rendered obsolete.

Strategic Re-Founding Requirements

Re-founding represents a complex strategic challenge for established companies but yields immense value when executed correctly. It is crucial for companies to acknowledge what is truly required.

Key Components of Re-Founding

The first aspect demands alignment throughout the organisation’s hierarchy. Everyone from the CEO to product leaders must grasp that re-founding is not merely a directive to increase AI usage; rather, it represents a fundamental restructuring of how the company generates and provides value.

Second, leaders must confront difficult decisions about discontinuing certain operations. For example, Nadella’s decision to terminate Nokia mobile did not involve maintaining it alongside Azure. Companies attempting to re-found without these tough choices risk creating inefficient hybrid organisations.

Third, neglecting the process and personnel elements can lead to failure. General mandates to enhance AI usage can obscure the necessary work of retraining employees, redesigning workflows, and reshaping the product development culture.

The Competitive Landscape

According to ICONIQ Capital’s State of Software 2025 report, AI-native startups are expanding at rates two to three times faster than top-tier traditional SaaS companies. Some of these have achieved $30 million in ARR within just twenty months, which is significantly quicker than established SaaS routes. Incumbent firms cannot replicate this speed merely by adding AI features; they must entirely rework their workflows.

The Critical Timing of Re-Founding

Re-founding should be viewed as a singular opportunity. As noted by Handshake’s CMO, the effort invested must be substantial, as companies only have one window to effect this transition. A second attempt may be perceived as an indication of failure rather than ambition. Failing to accomplish a re-founding carries a heavier credibility cost than forgoing the effort altogether.

Stanford HAI’s forecast for 2026 captures this shift perfectly: the era of advocating AI is evolving into an age of evaluating AI, leading firms to examine its effectiveness, cost, and impact on specific audiences.

India’s Position in the Re-Founding Landscape

India’s software and SaaS ecosystem faces the re-founding challenge from a unique stance compared to Silicon Valley. Indian SaaS companies have diligently built for global markets over the past decade, with increasingly lean cost structures.

The presence of more than 1,800 Global Capability Centres and extensive participation in the global STEM workforce ensures a robust talent pool for AI-native product development.

The Threat of Complacency

Despite these advantages, there is a risk of complacency. Organisations that erroneously believe cost advantages alone will offer protection may misinterpret the profound changes instigated by AI, which alters product design, sales strategies, margin frameworks, and customer interactions.

Strategic Opportunities for Indian Companies

The opportunity is substantial. For leaders and founders in India, this moment signifies a chance to redefine the ecosystem. Those embracing AI-native development practices, exploring innovative pricing, and rethinking workflows will shape the future of Indian technology firms aiming at a global scale.

India’s inherent advantages in talent, affordability, and digital infrastructure position it favourably in the global landscape during this shift. However, these benefits necessitate proactive utilisation and will not endure without concerted effort.

The Ultimate Measure of Re-Founding

Ultimately, the term “re-founding” is significant only if it results in tangible outcomes. The true measure is whether the company emerges from this process with more relevant products, enhanced unit economics, a defined growth path, and an established reason for customer loyalty. This necessity outweighs mere narrative positioning and superficial indicators of success.

Founders who grasp this concept will cultivate the next tier of ground-breaking companies. This may consist of first-time founders innovating from scratch or the exceptional individuals who successfully rebuild from within.