Zencoder, a provider of AI agents integrated directly into developers’ environments, announced today that it has acquired Machinet, a developer of context-aware AI coding assistants with over 100,000 downloads in JetBrains IDEs. The strategic acquisition further cements Zencoder’s position in the rapidly expanding AI coding assistant market, while broadening its multi-integration ecosystem across popular development platforms.

Expanding the Developer Experience

Following the acquisition, Machinet users will gain access to a significantly enhanced developer experience, including:

• Enhanced JetBrains Integration

By combining Machinet’s specialized expertise in JetBrains IDEs with Zencoder’s existing support, developers can look forward to even more powerful tools tailored for these widely-used environments.

• Augmented Unit Testing

Machinet’s context-aware unit test generation technology will be integrated with Zencoder’s advanced testing agents, offering developers a more comprehensive and automated testing experience.

• Industry-Leading Customization

Machinet’s developer community will now benefit from Zencoder’s deep capabilities in understanding large codebases, adapting to team-specific coding styles, and aligning with organizational architecture patterns.

“This acquisition aligns perfectly with our mission to turn everyone into a 10x engineer by providing AI solutions that handle routine coding tasks and let developers focus on innovation,”

said Andrew Filev, CEO and Founder of Zencoder.

“By bringing our advanced coding agent to Machinet’s thriving JetBrains community, we’re fulfilling our mission to deliver the best AI coding experience regardless of development environment.”

Streamlined Transition for Customers

As part of the acquisition, Machinet’s domain and marketplace presence will be transferred to Zencoder. Current Machinet customers will receive detailed guidance on transitioning to Zencoder’s platform, which leverages its proprietary Repo Grokking technology and AI agents.

Existing Machinet users will now gain access to Zencoder’s full feature set, including:

• Advanced multi-file editing and refactoring capabilities
• Deep codebase understanding across repositories using Repo Grokking™
• Sophisticated self-repair mechanisms that automatically test and refine outputs
• Expanded integration with over 20 developer tools, including Jira, GitHub, and GitLab
• Access to Zencoder’s specialized coding and unit testing AI agents

Industry-Leading Performance

Earlier this year, Zencoder’s AI platform demonstrated benchmark-breaking performance:

• A 2x improvement over previous best results on SWE-Bench-Multimodal
• State-of-the-art results on the challenging “IC SWE (Diamond)” section of SWE-Lancer, outperforming top published results by 23%

With the integration of Machinet’s technologies, Zencoder aims to further enhance its capabilities, reinforcing its leadership position in AI-assisted software development.

Availability and Next Steps

Zencoder’s full suite of AI coding and testing tools, including the newly enhanced JetBrains integration, is now available through zencoder.ai, with subscription options ranging from free basic plans to comprehensive enterprise solutions.

Current Machinet users will be provided with detailed transition instructions in the coming weeks.

About Zencoder

Based in Silicon Valley, Zencoder offers powerful AI coding and testing agents designed to empower professional developers. Founded by serial entrepreneur Andrew Filev, Zencoder’s globally distributed team of over 50 engineers helps organizations accelerate innovation and ship impactful software faster. The company holds ISO 27001 certification, is SOC 2 Type II compliant, and is in the process of finalizing its ISO 42001 certification.

Snyk has introduced a groundbreaking solution to tackle the next wave of cybersecurity challenges. The company announced the launch of Snyk API & Web, a next-generation Dynamic Application Security Testing (DAST) tool engineered to secure modern, AI-powered applications.

Bridging the Security Gap in AI-Driven Development

Traditional DAST solutions have long struggled to keep up with the rapidly evolving architectures and increasing complexity of APIs brought by AI-centric development. Recognizing this critical need, Snyk acquired Probely in 2024, integrating its advanced DAST capabilities into Snyk’s broader security ecosystem—complementing existing offerings like SAST, SCA, container, and Infrastructure as Code security.

The result is a unified platform that delivers a holistic, end-to-end view of application security throughout the entire Software Development Life Cycle (SDLC).

AI-Powered Innovations for Modern Applications

Snyk API & Web introduces several forward-thinking features designed specifically for the AI era:

• AI-Driven API Testing: Leveraging in-house fine-tuned Large Language Models (LLMs), the platform automates API discovery and vulnerability scanning—detecting complex issues like Broken Object Level Authorization (BOLA) more efficiently.
• Code-Informed Dynamic Testing: By correlating DAST results with SAST findings, Snyk provides deeper context for vulnerabilities, supporting more accurate prioritization and enabling AI-powered auto-remediation via DeepCode AI Fix.
• CI/CD-Ready: Designed with DevOps in mind, the tool offers seamless CI/CD integration, allowing developers to perform self-service scans within pipelines, guided by organizational AppSec policies.

Strategic Vision from the Top

“Our vision is to empower developers and AppSec teams to secure their entire application surface without slowing down innovation,”

said Geva Solomonovich, Snyk CIO.

“Snyk API & Web is the culmination of that vision—bringing together the speed of AI with the depth of full-lifecycle security.”

Momentum and Market Response

Since integrating Probely, Snyk has reported a 245% quarter-over-quarter growth in Annual Recurring Revenue (ARR) for DAST services—a clear signal of strong market demand for modern, AI-augmented security tools.

Looking forward, the company plans to deepen its AI capabilities, broaden API coverage, and provide even richer context for faster, more accurate vulnerability remediation.

In a significant stride towards bolstering software supply chain security, Docker has introduced the Docker Maintained Community Packages (MCP) Catalog and Toolkit. This initiative is designed to offer developers and organizations a repository of secure, high-quality open-source packages maintained directly by Docker, addressing the growing concerns over the integrity and trustworthiness of software components in containerized applications.

The Docker MCP Catalog serves as a curated collection of frequently used open-source packages, selected based on community usage patterns and relevance to contemporary development workflows. By standardizing these images under Docker’s stewardship, the company provides a more trustworthy alternative to packages that are often sourced from less vetted or anonymous contributors.

Complementing the catalog is the Docker MCP Toolkit, an open-source suite of utilities aimed at simplifying the processes of building, testing, and verifying Docker images. This toolkit not only assists developers in reproducing Docker-maintained packages but also empowers contributors to create similarly secure and reliable images tailored to their specific use cases.

“Security remains a top priority for the open source and container ecosystems,”

stated Docker in its official blog post.

“By offering both the catalog and toolkit, we aim to reduce uncertainty in the software supply chain and help teams ship with confidence.”​

Docker’s MCP initiative aligns with broader industry trends emphasizing software supply chain integrity, especially in the wake of high-profile vulnerabilities and dependency attacks. It also supports best practices such as Software Bill of Materials (SBOMs) and digital signing, both of which are integrated into the MCP offerings.

The project is anticipated to see widespread adoption among developers seeking vetted base images, DevOps teams aiming to enhance CI/CD hygiene, and organizations striving to meet compliance standards related to open-source usage.​

Docker encourages community feedback and contributions to the MCP initiative via GitHub, promoting transparency and collaboration in building a more secure container ecosystem.

As threats to the software supply chain continue to evolve, Docker’s MCP Catalog and Toolkit represent a timely and proactive measure towards fortifying one of the most critical layers of modern application infrastructure.

Microsoft has announced a series of significant updates to the Microsoft 365 Developer Program, aiming to provide developers with a more robust, secure, and accessible environment. These enhancements, shaped by community feedback, are set to roll out over the coming months.

Streamlined Tenant Provisioning

A new and improved tenant provisioning flow will become the default for all new qualified members of the Microsoft 365 Developer Program. These tenants are commercially enabled with add-on options. Existing members will have the option to transition by expiring their current tenant and provisioning a new one.​

Support for Commercial Add-ons

Later this year, members will be able to purchase additional subscriptions on their development tenants provisioned through the new experience, including Microsoft 365 Copilot licenses.​

Improved Tenant Ownership and Management

Microsoft is enabling clearer identification of tenant owners, making it easier for developers to manage and secure their environments.​

Option to Transition to Paid Subscriptions

Developers wishing to move beyond the Developer Program will have the ability to convert their development tenant into a standard paid Microsoft 365 subscription.​

Future Improvements on the Horizon

Microsoft is exploring additional ways to make the Microsoft 365 Developer Program more inclusive, flexible, and valuable for a broader global developer base. These improvements are currently in planning, with more details to be shared as the roadmap is finalized.​

What’s Next

A comprehensive update detailing the next wave of changes is expected by September 2025. Currently, no other changes are planned for existing Developer Program members beyond the enhancements mentioned.

Lace AI, a startup using artificial intelligence to supercharge customer service for home service companies, has raised $19 million in total funding, according to company’s website referring a TechCrunch article. The Mountain View-based company disclosed a previously unannounced $5 million pre-seed round led by Canvas Ventures, and a new $14 million seed round led by Bek Ventures. Other investors include Horizon VC, Launchub, Snowflake co-founder Marcin Zukowski, and Vivino’s Heini Zachariassen.

Founded in early 2022, Lace is the brainchild of Boris Valkov, a former AI engineer at Meta who helped develop PyTorch. Drawing from his early experiences in his family’s grocery store and later engineering roles at VMware and Meta, Valkov teamed up with Stan Stoyanov to launch a platform that blends AI with customer service.

Lace’s software analyzes 100% of incoming customer calls for home services companies—like HVAC, plumbing, and roofing—to detect missed sales opportunities and improve booking rates. The company says some clients have reported double-digit revenue growth and claims a 1,000% increase in annual recurring revenue (ARR) in 2024, after beginning sales at the end of 2023.

Currently working with over 100 businesses, including A1 Garage Door Service and Sage Home, Lace operates on a SaaS model, charging per agent. With 20 employees today, the company plans to triple its headcount using the new capital.

Bek Ventures’ managing partner Mehmet Atici told TechCrunch the firm was drawn to Lace’s strong team and its focus on applying AI to traditionally underserved industries—an approach he believes represents a major opportunity.

Photo: Lace AI

Meta announced new steps to expand protections for teen users across its platforms, including Instagram, Facebook, and Messenger. The update, shared via a company blog post, reflects Meta’s ongoing efforts to create safer, more age-appropriate experiences for younger users and to support parental involvement in their digital lives.

Scaling Up the Teen Accounts Experience

Since the initial launch of Instagram Teen Accounts last year, Meta has introduced a range of built-in safeguards. These include limitations on who can contact teen users, restrictions on sensitive content, and tools to help manage screen time. Teen users are automatically placed into these protective settings, and those under the age of 16 require parental or guardian approval to make changes.

As of April 2025, the company reports more than 54 million active Teen Accounts globally, with an impressive 97% of teens aged 13–15 choosing to remain under these default protections. The experience has since been extended to Facebook and Messenger, broadening the reach of these initiatives across Meta’s ecosystem.

Positive Feedback from Families

According to Meta, both teens and parents have responded favorably to these changes. In surveys conducted by the company, over 90% of parents said the Teen Account features were helpful in supporting their children’s online experiences.

Despite these encouraging numbers, Meta acknowledges the ongoing challenges parents face in navigating the digital world with their teens. “The internet can be overwhelming,” the company notes, emphasizing its commitment to continue evolving its tools in collaboration with parents and experts.

A New Call to Action for Parents

Beginning this week, Meta will roll out in-app notifications to parents on Instagram, encouraging discussions around digital safety and the importance of accurately representing age online. These notifications will include expert advice, such as guidance from Dr. Ann-Louise Lockhart, a pediatric psychologist, on how to initiate age-related conversations with teens.

This effort is part of a broader push to ensure that teens are not only protected by default settings, but also understand the importance of truthful age disclosure in online environments.

AI-Driven Age Detection Now in Testing

To further strengthen its teen safety efforts, Meta is testing a new AI system in the United States designed to detect accounts that may belong to teens—even if the listed birthdate suggests otherwise. Once identified, these accounts will be automatically placed in Teen Account settings.

While Meta has previously used artificial intelligence to estimate user age, this marks a more proactive use of the technology. The company states that it is taking care to ensure accuracy in identifying teens and is providing users with the option to update their settings if errors occur.

More details about this AI approach and Meta’s broader age verification initiatives can be found here.

Looking Ahead

Meta acknowledges that determining the age of users online remains a complex, industry-wide challenge. The company emphasizes that while AI and in-app protections play a critical role, parental verification and age confirmation at the app store level remain among the most effective tools for ensuring safe, age-appropriate digital environments.

The Washington Post has announced a strategic partnership with OpenAI to enhance access to reliable journalism within ChatGPT, the popular conversational AI platform. Through this collaboration, users will now see summaries, key quotes, and direct links to The Post’s original reporting when querying relevant topics.

A Shared Vision for Accessible, High-Quality Information

The integration underscores a joint mission to make factual, well-sourced reporting easier to access—particularly on fast-moving or nuanced issues. ChatGPT will now surface journalism from The Post on subjects including politics, global affairs, business, and technology, ensuring clear attribution and direct links to full articles for users seeking deeper insights.

“We’re all in on meeting our audiences where they are,” said Peter Elkins-Williams, Head of Global Partnerships at The Washington Post. “Ensuring ChatGPT users have our impactful reporting at their fingertips builds on our commitment to provide access where, how and when our audiences want it.”

Varun Shetty, Head of Media Partnerships at OpenAI, emphasized the importance of journalistic integrity in AI responses: “More than 500 million people use ChatGPT each week to get answers to all kinds of questions. By investing in high-quality journalism by partners like The Washington Post, we’re helping ensure our users get timely, trustworthy information when they need it.”

Expanding Media Partnerships in the AI Era

This collaboration builds on OpenAI’s broader efforts to integrate trusted news content into its tools. To date, the company has established partnerships with more than 20 publishers, expanding access to over 160 news outlets and hundreds of content brands across more than 20 languages.

AI at the Heart of The Post’s Digital Evolution

The Washington Post has increasingly embraced artificial intelligence as a tool to improve news accessibility and audience engagement. Recent innovations include Ask The Post AI, Climate Answers, and newsroom tools like Haystacker, all developed to leverage generative AI for journalistic purposes. The organization has also introduced AI-powered article summaries and audio formats to expand how readers consume news.

While many developers have mastered the basics, senior developers should be well-versed in advanced TypeScript concepts to write more maintainable, scalable, and efficient code.

Below are seven advanced TypeScript concepts that every senior front-end developer should understand.

What Every Senior Front-End Developer Should Know About Advanced TypeScript Concepts

1. Union Types

Union types enable a variable to hold one of several specified types, providing the flexibility of dynamic data handling while preserving type safety. It’s akin to having a multi-functional tool that fits diverse scenarios.

Example:

More Real-World Example:

2. Intersection Types

Intersection types combine properties from multiple types, ensuring that a variable satisfies all the conditions. It’s a way to merge the identity of different entities, useful for designing more complex types.

Example:

In this scenario, a SuperAdmin type ensures that a user has both User and Admin properties.

3. Type Guards

Type guards act as validation checkpoints within code, allowing for safer type narrowing during runtime checks. These are like checkpoints that only let specific types through, enhancing security and accuracy.

Example:

4. Conditional Types

Conditional types provide powerful type transformations based on certain conditions. They enable dynamic type manipulation, similar to how logic gates control paths in circuits.

Example:

Conditional types allow developers to build types that adapt based on other types, leading to more expressive and flexible code.

5. Mapped Types

Mapped types transform existing types into new structures by iterating over each property, making it easier to implement type-wide modifications.

Example:

6. Template Literal Types

Template literal types use string literals to create new types, providing a way to enforce naming conventions or combine string patterns for type safety.

Example:

These types make your type definitions more expressive, offering clearer guidelines for code patterns.

7. Recursive Types

Recursive types are crucial for representing complex data structures like trees, linked lists, or deeply nested objects. They allow types to refer to themselves, providing a way to model data structures that are inherently recursive.

Example:

Recursive types are like building blocks that enable you to model structures as intricate as a family tree or a file directory.

Conclusion

Advanced TypeScript concepts such as union types, intersection types, type guards, conditional types, mapped types, template literal types, and recursive types are essential tools in a senior developer’s toolkit. Mastering these features ensures that your code is type-safe, concise, and scalable, setting a strong foundation for complex application development.

Material provided by: Kristiyan Velkov

Photo by Austin Distel on Unsplash

Kristiyan Velkov, Contributor at DevStyleR, is with over 10 years of experience in JavaScript and open-source development. He has honed his skills in tools like React.js, Angular, Vue.js, and Next.js. He also dive deep into DevOps, web accessibility, and security—because great code is about more than just functionality!

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The Machiavellian Approach in Tech Leadership

Machiavellian leaders operate with a results-oriented mindset, focusing on long-term gains, often at the expense of short-term relationships. This approach is marked by key traits such as:

• Tactical Influence

The ability to influence employees, competitors, and investors to achieve their objectives.

• Pragmatic Decision-Making

Prioritizing efficiency and effectiveness over conventional ethics.

• Control and Power Consolidation

Ensuring that they maintain control over their company’s direction by eliminating potential threats or competition.

• Visionary Disruption

Using bold, sometimes controversial strategies to revolutionize industries.

Notable Tech Leaders with Machiavellian Traits

Several high-profile tech leaders exhibit qualities associated with Machiavellianism, helping them build empires while also attracting scrutiny for their methods.

Steve Jobs (Apple)

Steve Jobs was known for his intense focus, perfectionism, and an unyielding demand for excellence. His ability to manipulate situations, fire employees who didn’t meet his expectations, and cultivate a cult-like following around Apple products exemplified Machiavellian leadership. One of the most famous examples of his strategic approach was his ousting from Apple in 1985, only to return in 1997, orchestrating a dramatic comeback that redefined the company. Jobs also reportedly used a “reality distortion field” to push employees beyond their perceived limits.

Elon Musk (Tesla, SpaceX, X)

Elon Musk’s leadership is marked by his relentless pursuit of ambitious goals, sometimes pushing employees to extreme limits. He is known for making bold claims, disrupting industries, and strategically using social media to manipulate markets and public perception. A prime example was his infamous 2018 tweet: “Am considering taking Tesla private at $420. Funding secured.”—which led to an SEC lawsuit and a $40 million settlement. His abrupt decisions, such as mass layoffs at Twitter (now X) after acquiring it, demonstrate his cutthroat approach to leadership.

Jeff Bezos (Amazon)

Bezos transformed Amazon from an online bookstore into a global e-commerce and cloud computing giant through calculated strategy and unwavering ambition. His intense focus on efficiency, cost-cutting, and leveraging data-driven insights to dominate markets showcases a pragmatic and results-driven leadership style. One example of his strategic control was Amazon’s aggressive pricing tactics to undercut competitors, leading to market dominance and antitrust scrutiny. Bezos also famously enforced a “two-pizza rule” for meetings to maximize efficiency and productivity. This rule states that no meeting should have more attendees than two pizzas can feed, typically around six to eight people. The idea is to keep discussions focused, decision-making streamlined, and avoid unnecessary bureaucracy—hallmarks of Amazon’s data-driven and highly efficient culture.

Discover Your Leadership Style in the Tech Industry – Are you a modern-day Machiavelli… ?

Mark Zuckerberg (Meta, formerly Facebook)

Zuckerberg’s rise to power involved strategic acquisitions, aggressive competitive tactics, and a relentless pursuit of growth. His ability to navigate regulatory scrutiny, outmaneuver rivals, and retain control over Meta despite challenges from investors and government agencies illustrates his mastery of power dynamics and strategic manipulation. A notable example is Facebook’s acquisition of Instagram in 2012 and WhatsApp in 2014, moves that eliminated key competition and solidified Meta’s dominance. Additionally, the Cambridge Analytica scandal showcased how Facebook prioritized growth over user privacy.

Travis Kalanick (Uber)

Kalanick, the co-founder and former CEO of Uber, epitomized Machiavellian leadership with his aggressive expansion strategies, disregard for traditional regulations, and a workplace culture that prioritized rapid growth over ethical considerations. His approach included launching Uber in cities without regulatory approval, using “Greyball” software to evade authorities, and fostering a cutthroat internal culture. His leadership ultimately led to controversy, and he was forced to resign in 2017 after a series of scandals.

The Ethical Dilemma and Potential Balance of Machiavellian Leadership

While Machiavellian leaders drive innovation and industry disruption, their leadership style raises ethical concerns. Their focus on results often comes at the cost of employee well-being, ethical business practices, and, in some cases, regulatory compliance. However, certain elements of Machiavellian leadership—such as discipline, strategic decision-making, and setting clear boundaries—can be beneficial when used to maintain organizational structure and efficiency. When combined with leadership styles that prioritize employee well-being, such as transformational or servant leadership, Machiavellian elements can create a balanced approach that fosters both innovation and a supportive work culture.

The question remains: Is the Machiavellian approach a necessary evil in the tech world, or does it set a dangerous precedent for future leaders?

“Images in ChatGPT are wayyyy more popular than we expected (and we had pretty high expectations),” Altman wrote.

GPT-4o’s Image Tools Initially Reserved for Paid Users

The delay comes just one day after OpenAI introduced its new GPT-4o model, which includes native support for image generation and editing. The update allows users to upload, modify, and interact with images directly within ChatGPT.

In a blog post published Tuesday, OpenAI said these new features would roll out to all ChatGPT users “soon.” However, as of Wednesday, the capabilities remain limited to paying subscribers—specifically those on ChatGPT Plus, Pro, and Teams plans.

Ongoing Capacity Challenges at OpenAI

This isn’t the first time OpenAI has scaled back or delayed product rollouts due to infrastructure limitations. The company has repeatedly cited insufficient compute capacity as a bottleneck for launching new features.

Earlier this year, OpenAI faced a similar issue following the debut of its text-to-video model Sora. Signups for the product were temporarily paused just days after launch due to demand.

Looking ahead, OpenAI is betting big on infrastructure to address these recurring issues. The company is reportedly planning a $500 billion initiative, dubbed Stargate, to build one of the largest data centers in the world in partnership with Microsoft. The project is aimed at dramatically increasing the compute power available for AI workloads.

Image: OpenAI