Artificial Intelligence

How ChainGPT and Secret Network Bring Private, Verifiable AI Coding On-Chain

A step forward that could influence how smart contracts are designed and verified.

Updated

January 8, 2026 6:32 PM

ChainGPT's robot mascot. IMAGE: CHAINGPT

A new collaboration between ChainGPT, an AI company specialising in blockchain development tools and Secret Network, a privacy-focused blockchain platform, is redefining how developers can safely build smart contracts with artificial intelligence. Together, they’ve achieved a major industry first: an AI model trained exclusively to write and audit Solidity code is now running inside a Trusted Execution Environment (TEE). For the blockchain ecosystem, this marks a turning point in how AI, privacy and on-chain development can work together.

For years, smart-contract developers have faced a trade-off. AI assistants could speed up coding and security reviews, but only if developers uploaded their most sensitive source code to external servers. That meant exposing intellectual property, confidential logic and even potential vulnerabilities. In an industry where trust is everything, this risk held many teams back from using AI at all.

ChainGPT’s Solidity-LLM aims to solve that problem. It is a specialised large language model trained on over 650,000 curated Solidity contracts, giving it a deep understanding of how real smart contracts are structured, optimised and secured. And now, by running inside SecretVM, the Confidential Virtual Machine that powers Secret Network’s encrypted compute layer, the model can assist developers without ever revealing their code to outside parties.

“Confidential computing is no longer an abstract concept,” said Luke Bowman, COO of the Secret Network Foundation. “We've shown that you can run a complex AI model, purpose-built for Solidity, inside a fully encrypted environment and that every inference can be verified on-chain. This is a real milestone for both privacy and decentralised infrastructure”.

SecretVM makes this workflow possible by using hardware-backed encryption to protect all data while computations take place. Developers don’t interact with the underlying hardware or cryptography. Instead, they simply work inside a private, sealed environment where their code stays invisible to everyone except them—even node operators. For the first time, developers can generate, test and analyse smart contracts with AI while keeping every detail confidential.

This shift opens new possibilities for the broader blockchain community. Developers gain a private coding partner that can streamline contract logic or catch vulnerabilities without risking leaks. Auditors can rely on AI-assisted analysis while keeping sensitive audit material protected. Enterprises working in finance, healthcare or governance finally have a path to adopt AI-driven blockchain automation without raising compliance concerns. Even decentralised organisations can run smart-contract agents that make decisions privately, without exposing internal logic on a public chain.

The system also supports secure model training and fine-tuning on encrypted datasets. This enables collaborative AI development without forcing anyone to share raw data—a meaningful step toward decentralised and privacy-preserving AI at scale.

By combining specialised AI with confidential computing, ChainGPT and Secret Network are shifting the trust model of on-chain development. Instead of relying on centralised cloud AI services, developers now have a verifiable, encrypted environment where they keep full control of their code, their data and their workflow. It’s a practical solution to one of blockchain’s biggest challenges: using powerful AI tools without sacrificing privacy.

As the technology evolves, the roadmap includes confidential model fine-tuning, multi-agent AI systems and cross-chain use cases. But the core advancement is already clear: developers now have a way to use AI for smart contract development that is fast, private and verifiable—without compromising the security standards that decentralised systems rely on.

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Strategy & Leadership

Overcoming Barriers to Digital Fluency in the Workplace

The new workplace literacy is here, and it’s digital.

Updated

January 8, 2026 6:36 PM

Vintage beer pong posters showcasing colorful, diverse designs from different eras in one collection.

A group of office worker attending a presentation in a meeting room. PHOTO: UNSPLASH

The modern workplace is powered by technology, and success increasingly depends on how well employees can use it. Digital fluency—the ability to confidently and effectively use digital tools to achieve goals—is no longer a bonus skill; it’s a necessity. It goes beyond basic technical know-how, encompassing the ability to adapt to new technologies, integrate them into workflows, and use them to solve problems and drive innovation.

Yet, despite its importance, many organizations struggle to build digital fluency across their teams. Barriers such as limited access to technology, outdated training programs, resistance to change, and gaps in leadership support often stand in the way. These challenges can leave businesses lagging behind competitors who are better prepared to leverage the potential of the digital age.

Understanding and addressing these barriers is critical for creating a workforce that thrives in today’s fast-changing world. Below, we explore the key obstacles to digital fluency and provide actionable strategies to overcome them.

Common barriers to digital fluency
1. Outdated training practices

One of the challenges to digital fluency is the gap between the technology available and employees’ ability to use it effectively. Technology evolves rapidly, but many organizations lag behind in providing relevant, up-to-date training. Employees may receive a one-time introduction to new tools but lack ongoing opportunities to build confidence or master advanced features.

This issue is compounded by the fact that training often takes a one-size-fits-all approach, failing to address the diverse skill levels within a workforce. For example, while some employees may only need a basic overview of a tool, others may require in-depth knowledge to integrate it into their roles effectively. Without tailored and continuous training, even the most advanced tools can go under utilized, leading to frustration and resistance.

2. Resistance to change

Even with proper training, employees may hesitate to adopt new technologies. Resistance to change is a deeply rooted challenge that goes beyond technical skills—it’s tied to fear of failure, skepticism about the value of new tools, or discomfort with disrupting existing workflows.

For example, employees who have been using the same systems for years may feel overwhelmed by the idea of learning something new. They may worry that new technologies will complicate their work rather than simplify it. In some cases, they may even feel their jobs are threatened by automation or digital tools.

This resistance isn’t limited to employees—it can also exist at the leadership level. If leaders themselves are hesitant to adopt new approaches, it creates a top-down culture that stifles innovation.

3. Fragmented adoption across teams

The lack of organizational alignment is another significant barrier. Digital tools often roll out unevenly across departments, leading to fragmented adoption. For instance, one team might embrace a new project management tool, while another continues to rely on spreadsheets. This inconsistency creates silos, disrupts collaboration, and makes it harder for organizations to achieve the full benefits of digital transformation.

Generational differences can further exacerbate this issue. Younger employees, who are often more comfortable with technology, may adopt new tools quickly, while older employees may struggle to keep up. This divide can lead to frustration on both sides and uneven levels of digital proficiency across the organization.

4. Lack of leadership support

Leadership plays a critical role in driving digital transformation, but in many organizations, this support is inconsistent or absent. Some leaders fail to prioritize digital fluency as a strategic initiative, while others may not fully understand the tools themselves, making it difficult to set an example for their teams.

Without clear direction from leadership, employees may not see digital fluency as a priority. This lack of alignment can lead to half-hearted adoption, where technology is seen as an optional add-on rather than a fundamental part of the organization’s success.

Why these barriers matter

These barriers don’t exist in isolation—they are deeply interconnected. For example, outdated training practices can fuel resistance to change, while fragmented adoption across teams is often a symptom of weak leadership support. Together, they create a cycle that limits an organization’s ability to adapt, innovate, and thrive in a fast-changing world.

Addressing these challenges is critical for building a workforce that is confident, capable, and ready to embrace the future. By breaking down these barriers, organizations can unlock the full potential of their teams and position themselves for long-term success.

Strategies for building digital fluency
1. Make training tailored, ongoing, and accessible

Training should not be an afterthought or a one-time event—it must be a continuous and personalized process. Employees come with diverse skill levels, and a one-size-fits-all training program often fails to address these differences. Organizations should adopt a multi-pronged approach to training, offering workshops for hands-on learners, e-learning modules for self-paced learning, and one-on-one coaching for employees who need more targeted support.

For example, companies like AT&T have invested heavily in workforce retraining initiatives, providing employees with a structured path to build digital skills overtime. These programs not only improve employee confidence but also help organizations fully leverage their digital tools.

Moreover, training programs should evolve to keep up with technological advancements. Employees need regular refreshers to stay current, as even the most advanced tools can become obsolete or under utilized without proper guidance. By making training a core part of the organizational culture, companies can empower employees to adapt to new tools with ease and confidence.

2. Foster a culture of experimentation

Resistance to change is a major barrier to digital fluency, often fueled by employees’ fear of failure or inefficiency when using new tools. To address this, organizations should foster a culture where employees feel safe experimenting with technologies in low-stakes environments, such as “sandbox environments” that allow for practice without affecting real workflows. When employees are encouraged to test new tools and processes in a low-stakes environment, they become more comfortable with technology over time.

Recognizing and rewarding employees who embrace new tools or suggest innovative ways to use them reinforces this mindset. Early adopters can serve as champions for digital fluency, encouraging others to engage with and explore new technologies.

By normalizing experimentation, organizations can shift employees from resisting change to confidently adopting digital tools as opportunities for growth.

3. Align teams through collaboration

To avoid fragmented adoption, organizations must ensure that digital tools are implemented consistently across teams. This requires clear communication, cross-departmental collaboration, and alignment on how tools will be used to achieve shared goals.

Mentorship programs can help bridge generational divides, pairing younger employees with older colleagues to share knowledge and skills.

4. Lead by example

Leaders play a pivotal role in overcoming barriers to digital fluency. They don’t just drive the adoption of digital tools—they shape how employees perceive and engage with them. When leaders actively embrace technology, they demonstrate its value and set a standard for others to follow.

Leadership involvement must go beyond symbolic gestures. Employees are far more likely to adopt new tools or processes when they see their leaders using them effectively in day-to-day work. For example, a manager who uses a team collaboration platform to streamline communications or leverages data visualization tools in meetings signals the practical benefits of these technologies. This hands-on engagement builds trust and encourages others to follow suit.

Equally important is leaders’ ability to connect digital tools to broader organizational goals. Employees need to understand how these tools contribute to solving real problems, improving workflows, or driving innovation. When leaders clearly communicate the "why" behind digital initiatives, it helps employees see digital fluency as a shared mission rather than an abstract directive.

Conclusion

Digital fluency isn’t just about mastering tools—it’s about creating a workplace where adaptability, curiosity, and collaboration thrive. It’s about empowering employees to see technology not as a hurdle but as an opportunity to innovate, grow, and solve problems in new ways.

At its heart, digital fluency is a shared effort, requiring leaders who inspire, teams that align, and cultures that embrace experimentation and learning. When organizations commit to breaking down barriers—whether through better training, stronger leadership, or fostering collaboration—they unlock the full potential of their people and their tools.

The future belongs to organizations that don’t just adopt technology but embed it into their culture, enabling their teams to thrive in an ever-changing digital landscape. The question now is not whether we can keep up with change, but how far we can go when we embrace it fully.