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Tag: project management

Common Risks of Outsourcing Software Development, and How to Tackle Them

Both SMBs and large enterprises often choose software development outsourcing over developing software in-house. It is no surprise, as partnering with external developers enables companies to bridge IT talent gaps that cannot be filled internally, avoid time-consuming recruiting and training processes, and eliminate expenses associated with salaries and benefits, eventually accelerating software delivery and reducing development costs.

While software development outsourcing can be highly advantageous from the business perspective, it also introduces various risks, ranging from diminished project control to provider lock-in and security-related issues. Managing these risks proactively is critical to preventing them from escalating, minimizing their impact on the project timeline, budget, and software quality, and ensuring smoother project execution.

In this article, experts from Itransition, an outsourcing partner with over 25 years of experience, outline common risks of outsourcing software development and share recommendations for mitigating them.

Diminished Project Control

Since outsourced teams often operate remotely and without the direct oversight companies typically have over in-house employees, maintaining end-to-end visibility into the development process can be challenging. This lack of visibility can make it more difficult to track project progress and spot bottlenecks in the development process early enough to prevent project delays. To mitigate these risks, a company should establish strong oversight and control mechanisms from the very beginning of the project.

Recommendations:

Ensure your outsourcing partner assigns a dedicated single point of contact (SPOC ) and define strict communication cadences directly in the outsourcing contract to ensure that the provider’s SPOC regularly delivers project status updates.

Additionally, negotiate with a partner about implementing visibility dashboards that automatically pull data from the provider’s toolchain (project management apps, Git repositories, etc.) enabling your stakeholders to monitor project progress and milestones without requesting manual updates.

To maximize transparency and gain evidence-based insights into project progress, require your outsourcing partner to maintain documentation, wireframes, architectural designs, and other project deliverables in a shared, client-accessible workspace.

Security and Privacy Concerns

Software outsourcing partners often require access to clients’ internal systems to perform development-related tasks. For instance, a partner may need to access internal middleware or APIs to integrate software into the client’s existing tech ecosystem. External developers may also require access to CI/CD pipelines to run tests or deploy software updates. However, granting third-party access to corporate systems inevitably introduces various cybersecurity risks, such as data breaches, credential exposure, or intellectual property theft. Taking potential security risks into account and addressing them proactively is essential to avoiding them.

Recommendations:

Add dedicated external-facing roles, such as Partner, Partner Admin, or others, to your existing role-based access control (RBAC) framework to ensure third-party developers can only access systems required to complete their specific tasks.

To prevent permission creep, implement just-in-time (JIT) provisioning mechanisms so that permissions granted to external developers remain active only for a limited period and are automatically revoked when the allotted time expires.

Configure multi-factor authentication (MFA) methods and require outsourcing developers to use it when accessing your company’s internal systems to ensure that developer accounts cannot be exploited by malefactors to breach your IT infrastructure.

Provider Lock-in

Delegating coding, testing, maintenance, and other software development tasks to an outsourcing partner inherently introduces the risk of provider lock-in. This occurs when a company becomes so heavily dependent on a particular partner that switching providers or bringing development processes back in-house becomes too disruptive, technically complex, or prohibitively expensive. To reduce the risk of provider lock-in, consider implementing several useful practices.

Recommendations:

Verify that the contract with a partner clearly defines ownership rights for all intellectual property (software specifications, source code, UI/UX designs, AI algorithms, etc.) to eliminate ownership disputes if you decide to switch to a new software outsourcing provider.

Establish a centralized internal knowledge base containing key project documentation (system diagrams, developer guidelines, etc.) and require ongoing knowledge transfer sessions between in-house teams and outsourced developers. These measures will help you avoid a deficit of internal knowledge and skills in case you decide to transition the development in-house in the future.

It is also highly recommended to negotiate with a partner to provide transition support services for a set period after the contract terminates (several weeks or months) to ensure business continuity and seamless handover to a new agency, in case you decide to switch outsourcing providers.

Final Thoughts

If you plan to delegate some part of your project or entrust its end-to-end execution to an external team, proactively managing the inherent risks of software development outsourcing is essential to ensuring smooth project delivery and its overall success.

The recommendations listed in this article will help you address and mitigate common risks involved in outsourced projects, including lack of project control, security issues, and provider lock-in.

To prevent these and other risks from escalating, it is equally important to choose an experienced outsourcing partner with a proven track record in your particular industry or domain. A reliable partner will help you develop software that meets your project requirements, as well as support knowledge transfer, protect your intellectual property rights, and ensure compliance with relevant data security and privacy regulations.

August 3, 2026
The Future of AI Development is Global: Building World-Class Teams Across Borders
As artificial intelligence (AI) continues to transform software development, companies face a critical challenge: How to build and maintain world-class AI development teams while managing costs and ensuring quality. As someone who has grown from a freelancer to CEO of a 30-person development company serving U.S. clients from Pakistan, I have learned that success in global AI development requires more than just technical expertise — it demands a carefully structured approach to team building, project management and quality assurance.

The foundation of any successful global AI development team starts with its structure. In our organization, we have found that a layered approach works best with UI/UX designers, native developers for Android and iOS, cross-platform specialists and dedicated AI experts working in tandem. This structure ensures that AI integration is not treated as an isolated function but is seamlessly incorporated into every aspect of development.

AI specialists lead model development, working closely with data engineers to ensure clean data and with machine learning (ML) engineers to optimize models for tasks like natural language processing (NLP) or computer vision. UI/UX designers collaborate with AI experts to ensure intuitive and user-friendly AI features. Native developers integrate AI into mobile apps, ensuring optimal performance across platforms, while cross-platform specialists ensure consistency and performance across devices. Clear communication and collaboration between these teams help integrate AI efficiently, delivering innovative, high-quality products.

However, building this structure requires more than just hiring developers with the right technical skills. When recruiting in emerging markets like Pakistan, we focus on finding talent that can bridge cultural and time zone gaps. Our team leads, for instance, maintain flexible schedules to ensure availability during U.S. business hours, while our developers are chosen not just for their technical prowess but for their ability to collaborate across cultural boundaries.

Distributed AI Development

Project management for distributed AI development presents unique challenges. We have implemented daily standup meetings and utilized a range of modern collaboration tools for task tracking, time management and communication. The key is creating transparency — our clients have complete visibility into which team members are working on specific tasks, sprint progress and development milestones. AI projects differ from traditional ones due to the iterative nature of data preparation, model training and validation. Unlike traditional coding, AI models require continuous optimization, frequent testing and close collaboration between AI experts, QA teams and developers. Tools like Slack for communication and Trello help manage these dynamic tasks, ensuring alignment and timely delivery.

One misconception about global teams is that quality suffers due to distance. In reality, we have found that distributed development can enhance quality when proper systems are in place. Our QA team works across all time zones, meaning testing can happen continuously. We have implemented rigorous code review processes and automated testing protocols specifically designed for AI applications, ensuring that our output maintains consistent quality regardless of where the development occurs.

The cost benefits of global teams are well-known — companies can often save up to two-thirds on development costs compared to U.S.-based teams. However, the real value goes beyond cost savings. With the rise of remote work tools and collaborative technologies, global teams can often deliver superior results by leveraging diverse perspectives and round-the-clock development cycles. When comparing costs, companies can save 30–40% by working with international teams, particularly in countries like Pakistan, where skilled talent is available at a fraction of the cost of U.S.-based developers. This cost efficiency allows companies to allocate resources to other growth initiatives, such as research and marketing.

In terms of ROI, the savings in labor costs can lead to quicker product launches, often reducing development time by 25–30%. Furthermore, the ability to work across time zones accelerates project completion, leading to faster market entry and a quicker ROI. By combining cost-effective solutions with 24/7 development cycles, companies can achieve high-quality results while maximizing their ROI.

For companies considering building global AI development teams, here are key strategies we have found successful:
1. Invest in Leadership: Strong project managers who understand both technical requirements and cross-cultural communication are essential.
1. Embrace Asynchronous Work: While maintaining some overlap in working hours is important, learning to work effectively across time zones can increase productivity.
1. Standardize Processes: Clear documentation, coding standards and quality assurance protocols help maintain consistency across distributed teams.
1. Leverage Local Expertise: Emerging markets like Pakistan offer a rich talent pool with specialized knowledge. For example, Pakistan’s universities, such as LUMS and FAST, train skilled AI professionals who excel in areas such as ML, data science and NLP. Companies like Cubix, VentureDive and 10Pearls are creating AI-driven solutions in sectors such as healthcare, fintech and e-commerce, contributing to innovative AI development globally.
The future of AI development is inherently global. As technology continues to evolve, companies that can effectively build and manage distributed teams will have a significant advantage. The key is moving beyond traditional outsourcing models to create truly integrated, global teams that can deliver world-class AI solutions.
February 7, 2025
Broadcom Adds On-Premises Edition of Project Management Application

Broadcom today at the VMware Explore 2024 conference added an on-premises edition of its Rally project management application for managing software engineering projects.

Jean-Louis Vignaud, head of ValueOps for the Agile Operations Division of Broadcom, said Rally Anywhere provides DevOps Teams with an alternative to the software-as-a-service (SaaS) edition of the platform that gives them more control over how their data is stored.

That’s a critical option for organizations operating in heavily regulated industries or any organization that is concerned about ransomware attacks that are increasingly being aimed at providers of SaaS applications, he added.

Broadcom is also looking to provide an alternative option to organizations that have been told that a rival on-premises edition of the Jira project management application from Atlassian will soon no longer be made available, noted Vignaud.

Finally, Rally Anywhere will also enable organizations to comply with any data sovereignty requirement that requires them to ensure data is stored within the physical borders of a specific country, he noted.

Rally is part of a portfolio of ValueOps value stream management (VSM) tools that Broadcom provides in both SaaS and on-premises editions. VSM traces its lineage back to lean manufacturing methods, which call for each step of a manufacturing process to be continuously measured. As software development has evolved from being a craft to a process that is automated as much as possible using DevOps best practices, an appreciation for the value of monitoring issues such as the impact of missed software development deadlines on the business has grown steadily, especially as more organizations realize how dependent on software they have become to drive revenue.

The overall goal is to make it possible to analyze normalized data collected from a diverse range of applications and services in a way that can also be more easily shared with applications such as Clarity, a workflow management application from Broadcom that is designed for business users, said Vignaud. That integration provides the business users regardless of what industry segment they operate in the visibility needed to manage an organization like a software company, he added.

It’s not clear how many software engineering teams might be looking to replace their existing approach to managing software engineering projects, but as it becomes simpler to automatically collect data from DevOps tools and platforms it’s becoming much easier to manage these projects. The days when project managers need to enter data they manually collected from software engineers have all but come to a close. Most of the data collection process has now been automated by modern project management applications.

The challenge now is applying artificial intelligence (AI) to that data to make it simpler to identify potential bottlenecks in software engineering workflows that might conspire to delay the development of an application. It may be still a while before those types of AI capabilities become pervasively employed but the one certain thing is that as project management continues to evolve many of the rote tasks that once made the job of the project manager tedious are rapidly being eliminated.

August 28, 2024
The Commonhaus Way to Manage Open Source Projects

Long-time Java developers may recall Codehaus, which combined a Java open source project hosting service and community. Now, inspired by its legacy, a new group of developers has established the Commonhaus Foundation.

At its core, Commonhaus embodies a vision of providing a neutral harbor for established open source libraries and frameworks seeking a home. The foundation’s mission is to ensure a nurturing environment where projects can flourish unabated, transcending generations of technology evolution.

Now, you may say that we already have this scenario with such organizations as the Apache Software Foundation, the Linux Foundation, and the OpenInfra Foundation. That’s all true, but they have clearly defined patterns for their child foundations.

What sets Commonhaus apart is its emphasis on offering guidance and support instead of imposing mandates. Instead of setting rules for how an organization must be set up and run, it empowers projects to navigate in their own way.

Its key principles include succession planning, which addresses the always tricky question of the “bus factor.” That is, it addresses how an open source project can keep going if one or more of its leaders die in a bus accident. The foundation addresses this by providing an intricate web of leadership transitions and contributor changes with grace, thereby safeguarding their influence and functionality over time.

Erin Schnabel, a founding member and chairperson of the Commonhaus Foundation, articulated the rationale behind this initiative. “The open source ecosystem has undergone profound transformations in recent years,” Schnabel remarked. “While existing foundations have laid the groundwork for numerous successful projects, the advent of fiscal hosting platforms and self-governance models has unveiled a clear need for a fresh approach.”

“Traditional governance structures may not align with the unique needs of projects that have cultivated their own practices and infrastructure,” Schnabel continued. “These projects often face hurdles when considering merging into existing foundations, leaving crucial needs unaddressed. Commonhaus seeks to bridge this gap, ensuring that projects of all stripes receive the support they need to thrive.”

Trisha Gee, a distinguished software engineer and Java Champion, echoed Schnabel’s sentiments. “Commonhaus fills a crucial void in the support ecosystem for open source projects,” Gee asserted. “Its focus on community and continuity is paramount for ensuring sustainability and mitigating maintainer burnout. Successful projects shouldn’t have to compromise their autonomy to access foundation support.”

The roster of projects joining Commonhaus at its inception reads like a Who’s Who of the open source world, including Hibernate, Jackson, OpenRewrite, JBang, JReleaser and Morphia. What these projects have in common is a desire for a stable, nurturing home without having to shift existing governance structures.

Gavin King, Red Hat distinguished engineer and parent of Hibernate, offered another reason to join Commonhaus. “We’ve never really overcame the perception that this is a project dominated by one company,” King said. “That’s something we want to finally change. Red Hat’s leadership and sponsorship have been a source of stability, continuity, and user confidence, and we don’t wish to undermine that. But what we would like to do now is open up space for other groups and companies also to feel included in the project.”

The Foundation extends an open invitation to developers, contributors, projects and sponsors to join its cause. Through sponsorship on platforms like GitHub, individuals, and organizations can not only provide financial support but also shape the strategic direction of open source development.

As the Commonhaus Foundation sets sail on its maiden voyage, it aims to chart a course toward a future in which open source projects can continue to thrive unfettered by the specter of obsolescence.

Photo credit: Luke Southern on Unsplash

April 15, 2024
DevOps: Addressing Communications Failures

The more complex software engineering becomes, the more apparent it is becoming that the communications processes relied on to manage DevOps workflows are fundamentally flawed. Every DevOps team has experienced multiple instances where, for example, a software package needed to build or deploy an application isn’t where it’s supposed to be when required. The outcome is additional delays that, in hindsight, were completely avoidable.

Fortunately, organizations are starting to realize that the tools used to build and deploy software create metadata that can be tracked and also harnessed to optimize workflows. For example, TestifySec’s Witness, an open source tool to generate and verify attestations that provide a verifiable record of the steps taken to build software, including the materials used and commands run during a DevOps workflow. A companion open source Archivista project manages storage, retrieval and retention of software build pipeline attestations and trusted telemetry observed by Witness.

“It’s really about being able to prove the provenance of your artifacts,” said TestifySec CEO Cole Kennedy. “It’s about communication.”

These and other tools are at the forefront of a broader effort to harness the metadata software build tools already generate in a way that not only helps ensure tasks have been completed but, ultimately, serves to make the software supply chain more secure.

“To effectively improve software supply chain security, it’s important to be intentional about observing DevOps workflows rather than hope to reconstruct data from workflows after the fact,” said Mitch Ashley, principal analyst for Techstrong Research.

In fact, as regulations requiring organizations to manage software supply chains continue to become more stringent, it’s now only a matter of time before compliance teams require software engineering teams to be able to document every interaction that occurred across the entire software development life cycle (SDLC).

The DevOps Documentation Challenge

DevOps teams today routinely employ multiple tools to create software artifacts, manage software engineering pipelines and, ultimately, deploy software. The level of DevOps maturity will vary widely from one organization to another, but they all have one thing in common: Somewhere, a project manager is trying to keep track of the interactions between those tools to ensure application delivery schedules are met. The challenge is, historically, those project managers have been forced to rely on manual data entry to capture those interactions in a way that can be used to verify a task was completed. In an ideal world, the tools themselves would automatically share the data required with an application that makes it easy to determine which tasks have actually been completed.

In the absence of that level of automation, it should come as no surprise that projects are delayed simply because one critical task or another was not completed in time for the next phase of the software development process was unable to begin on time. Inevitably, for want a proverbial nail, the battle is lost as delays that could have been avoided have a cascading impact throughout the software development life cycle.

Adding further insult to injury, no one effectively learned from that experience because the documentation that describes what occurred is either sparse or simply nonexistent. The truth is, software engineering teams are often at a loss when it comes time to explain to business and IT leaders what went wrong because there is no way to determine beyond a shadow of a doubt what occurred and precisely when during the software development process.

The Compliance Challenge

This lack of transparency into software development workflows has been an open secret for longer than most IT leaders care to admit. However, as software supply chain security concerns continue to mount, more organizations are being required to document the software engineering workflows that were relied on to build their applications. In the event of an audit, any inability to provide that documentation will only increase the size of the fines that might be levied.

The more complex the applications being deployed become, the more probable it becomes a critical event upon which an audit revolves will not have been captured by manual processes that, by definition, are prone to human error.

Unfortunately, as most IT leaders already know well, when it comes to compliance, there’s not a lot of forgiveness for human frailty.

Automation

As is almost always the case when it comes to DevOps workflows, the best path forward is to almost always rely on increased automation. One of the primary reasons most of these workflows are not well documented is that humans, in general, and application developers, in particular, are not overly fond of data entry. No one wants to spend time keying in data they know already resides in another application. In addition to wasting time, there’s also a high probability mistakes will be made as data is manually copied from one application to another.

Validating events that occur is how organizations manage risk. Otherwise, business and IT leaders are hoping that all the tasks that need to be completed to enable an application to be delivered on time are actually done. Hope is not a substitute for a platform that automatically captures, analyzes and validates each step that occurred to determine actual intent versus simply presenting a series of logs that don’t provide nearly enough meaningful context.

Summary

Slowly but surely, the processes organizations rely on to manage software are becoming more advanced. Capabilities that a few short years ago would have seemed far too difficult to provide are now readily accessible. Capturing metadata in a way that enables organizations to automate workflows at unprecedented scale is increasingly becoming commonplace.

The challenge and opportunity now is finding the simplest means possible to harness it at a time when application environments are becoming too complex to manage otherwise.

March 19, 2024
Atlassian Brings Generative AI to ITSM

Atlassian today added generative artificial intelligence (AI) capabilities to Jira Service Management, an IT service management (ITSM) platform built on top of Jira project management software already used widely by DevOps teams.

Generative AI is at the core of a virtual agent that analyzes and understands intent, sentiment, context and profile information to personalize interactions. Based on the same natural language processing (NLP) engine that Atlassian is embedding across its portfolio, the virtual agent dynamically generates answers from sources such as knowledge base articles, onboarding guides and frequently asked questions (FAQs) documents.

In addition, it can facilitate conversations with human experts any time additional expertise is required to respond to more complex inquiries.

Atlassian is also extending the reach of Atlassian Intelligence, a generative AI solution launched earlier this year, to provide concise summaries of all conversations, knowledge base articles and other resolution paths recommended by previous agents that have handled similar issues. It will also help IT staff craft better responses and adjust their tone to be more professional or empathetic if needed.

During setup, support teams can easily configure the virtual agent experiences to match how they deliver service without writing a single line of code.

Edwin Wong, head of product for IT solutions at Atlassian, said these additions are part of a larger commitment Atlassian is making to unify the helpdesk experience. The company plans to leverage Atlassian Intelligence to coordinate routing of all employee requests to the right tools as it aggregates requests from multiple communications channels such as web portals, email, chat and from within third-party applications, he noted.

The overall goal is to reduce the number of tickets generated by leveraging AI as much as possible to handle service requests in a way that costs less to implement and maintain, Wong said.

In the longer term, Atlassian will also apply generative AI to enable organizations to automate IT asset management further, he added.

There is little doubt at this juncture that AI will be pervasively applied across both ITSM and DevOps workflows. As those advances are made, it should also become easier to address issues that arrive either programmatically or by generating a ticket for a service request that is then processed by an ITSM platform such as Jira Service Management.

Each organization will need to decide how quickly to incorporate AI into ITSM, but hopefully, the level of burnout experienced by IT personnel will be sharply reduced as more tasks are automated. Less clear is the impact AI will have on the size of IT teams required to provide those services, but for the foreseeable future, there will always be a need for some level of human supervision.

In the meantime, IT teams should take an inventory of the processes that are likely to be automated by AI today with an eye toward restructuring teams as more tasks are automated. Ultimately, the goal should be to let machines handle the tasks they do best so humans can provide higher levels of service that deliver more value to the business.

October 31, 2023
Atlassian Strengthens Jira Navigation and Integration

Atlassian today made it simpler to navigate the Jira Software and Jira Work Management project management applications as part of an ongoing effort to make it simpler for DevOps teams to collaborate with other stakeholders of application development projects.

Megan Cook, head of product for Atlassian, said the ability to share release dates across multiple calendars, overviews that aggregate views of and summarize multiple projects along with command palette and importer tools make it simpler for, for example, marketing teams and other individuals outside of a DevOps team to keep track of application delivery schedules.

In addition, Atlassian has tightened integration between Jira and Confluence, a wiki-based collaboration application, and a previously launched Atlassian Intelligence capability that infuses generative artificial intelligence (AI) capabilities will also soon be added to Jira Work Management alongside existing support for Jira. There will also be connectors for Jira Work Management to integrate with Atlassian Admin, Atlassian Analytics, Access and Data Lake offerings, along with advanced security features.

Finally, Atlassian is adding support for a design tool developed by Figma that can now be directly installed in Jira.

Collaboration between application development teams and the rest of the business is becoming more crucial as organizations increasingly realize how much they depend on software to drive revenue. One of the primary reasons Atlassian is investing in generative AI is to make it simpler for anyone to understand the status of any given project and the downstream impact any change to a delivery schedule is likely to have.

Generative AI, of course, has already moved from being considered advanced technology to a set of capabilities that most end users will soon expect to be embedded within every application. One of the primary benefits generative AI provides is it makes a range of applications originally designed for specialists, such as a software engineering team, more accessible to a wider range of end users.

It’s not clear how much generative AI will change the relationship between DevOps teams and the rest of the business, but with increased visibility, there should be a greater appreciation for the challenges developers and DevOps teams face. Any member of an organization should be able to plainly see, for example, why more resources need to be allocated to a specific project to ensure that an application is delivered on time.

At the same time, application developers will find project management processes are about to become less disruptive as it becomes simpler to automatically import relevant data from the tools and platforms they use directly into a project management application such as Jira.

One way or another, software engineers should expect that as generative AI continues to evolve, the divide between them and the rest of the business will narrow. There may be times when that level of additional scrutiny may feel burdensome, but on the whole, it should make it easier for DevOps teams to get the resources required to achieve any given goal. After all, the root cause of any given delay to a project will soon be plain for anyone to see.

September 26, 2023
Atlassian Advances DevSecOps via Jira Integrations

Atlassian announced today it has allied with Snyk, Mend, Lacework, Stackhawk and JFrog to make it simpler to aggregate vulnerability data within the Jira project management software that many organizations rely on to manage application development and deployment efforts.

Andrew Pankevicius, a senior product manager for Atlassian, said the collaborations will make it easier to prioritize a list of vulnerabilities that need to be addressed and for DevOps teams to automatically assign that work to a continuous integration/continuous delivery (CI/CD) pipeline. Atlassian provides those third-party integrations via an Open DevOps initiative.

These capabilities, accessible via the Security Tab in Jira, will make it simpler for DevOps teams to manage output from the multiple application security tools that have become part of a larger DevSecOps workflow, noted Pankevicius.

These additions to the Atlassian portfolio are arriving at a time when there is a lot more focus on securing software supply chains in the wake of a series of high-profile breaches. Those breaches have led to a wave of legislative proposals in the U.S. and Europe that will soon require organizations to embrace DevOps best practices to address increased potential liability that might stem from an application breach.

For example, a proposed Cyber Resilience Act being negotiated by the member states of the European Union seeks to require organizations that sell internet-connected hardware platforms to ensure that their devices—and the software that runs on them—comply with cybersecurity best practices.

In the U.S., meanwhile, a National Cybersecurity Strategy proposal put forward by the Biden administration seeks to hold organizations that collect data or build software more accountable for breaches.

While both proposals are a long way from becoming the law of the land anytime soon, they are indicative of changing attitudes. Governments around the world are concluding the only way to ensure better cybersecurity is to require it. Previous suggestions made by government agencies are going to soon give way to actual mandates. As such, DevOps teams would be well-advised to get ahead of this sea change by implementing the tools and processes that inevitably will be required. As a result, many organizations are now embracing DevSecOps best practices that shift more responsibility for application security further left toward developers.

The challenge is finding the right set of cybersecurity tools that surface vulnerabilities as code is being developed to make sure context isn’t lost, said Pankevicius. Historically, cybersecurity teams have discovered vulnerabilities long after an application has been deployed in a production environment. By then, however, most developers have moved on to other projects, so remembering how a specific piece of code was developed and by whom can be a significant challenge, he noted.

There’s no doubt that when it comes to application security, a lot of progress has been made, but there is still much work to be done. The issue now is finding the best way to organize those efforts at a time when more applications are being simultaneously developed within organizations than ever.

June 6, 2023
ClickUp Adds Project Management Templates to Invoke ChatGPT

ClickUp is adding templates and collaboration tools to make it easier to access generative artificial intelligence platforms such as ChatGPT from within its project management application.

Haris Butt, head of product design for ClickUp, said ClickUp AI now includes pre-built department-specific prompts that any product managers, developers or designers can easily access rather than having to develop prompt engineering skills to engage a generative AI platform more effectively.

The templates, for example, make it simpler to produce summaries of project timelines in addition to the ability to automatically generate a whiteboard that lists tasks that need to be finished to complete a project.

In the longer term, ClickUp is also moving toward developing its own large language model (LLM) using its own data to provide a generative AI experience specifically optimized for project management, added Butt.

ClickUp is embedding AI into project management applications as part of an effort to eliminate drudgery, added Butt. One of the primary issues that makes project management challenging is that navigating workflows can be challenging, especially for stakeholders that might not be as well versed in, for example, how a Gantt chart flows.

It’s still early days as far as generative AI is concerned, but it’s already apparent that a wide range of templates are being developed to make it simpler to invoke these platforms. The need for project managers to become well-versed in all the nuances of prompt engineering techniques to optimize generative AI queries is likely to be limited.

In fact, the general expectation is that every application will eventually include templates for invoking generative AI capabilities. Less clear is the impact that should have on productivity. In the case of DevOps teams, however, many tedious project management tasks should become increasingly automated.

Generative AI will, of course, soon be employed across the entire DevOps workflow. Many of the tasks that have historically conspired to make DevOps processes tedious will be automated. In fact, many application developers are already using AI to test and review code. DevOps teams that have historically advocated ruthless approaches to automation are likely to be at the forefront of AI adoption.

There are, of course, concerns about the accuracy of generative AI platforms such as ChatGPT that have been trained using data that hasn’t always been verified. As a result, it’s possible that some of the results being surfaced by these platforms should be reviewed by humans before being acted on. However, LLMs trained on narrower ranges of validated data will soon become commonplace. As those AI advances are made, the accuracy of generative AI platforms that are optimized for specific use cases will increase.

In the meantime, DevOps teams should be more concerned about being left behind than about how generative AI impacts their employment prospects. There is no doubt generative AI will transform DevOps workflows along with a wide range of processes. The issue now is determining where DevOps teams can add value—and where machines can’t—in an era where IT environments are becoming more complex with each passing day.

April 27, 2023
Zenhub Brings Issues Management to Project Management Platform

Zenhub today announced it is adding an issue management module that makes it simpler for stakeholders to collaborate with developers on application development projects without having to log into a GitHub repository.

Fresh from raising an additional $10 million in capital, Zenhub co-founder Aaron Upright said Zenhub Issues is a plug-in for a project management application the company developed for GitHub environments to better streamline software development life cycles. The issue is that many application stakeholders, such as marketers, are not especially pre-disposed to logging into a repository for managing software components, he said.

Zenhub Issues provides an alternative means for collaborating with developers that doesn’t require stakeholders to log into GitHub, he said. In addition, organizations no longer need to acquire additional GitHub licenses for those users, noted Upright. Many of those end users wind up with read-and-write access to software components, which creates unnecessary cybersecurity risks should their credentials be compromised, he noted.

In some cases, organizations will also be able to eliminate the need for the project management applications many of those stakeholders have adopted because they can track issues via Zenhub Issues, he added.

Many organizations’ entire business strategies now revolve around accelerating the rate at which software development projects can be completed. Many elements of those projects, however, can’t go forward until a specific component upon which it depends is completed, so project management has become a critical function. Investors are holding business leaders more accountable for software delivery timetables that have direct implications on revenue generation, so that pressure naturally falls on DevOps teams.

It’s not surprising that there aren’t a wider range of end users of project management applications as various stakeholders seek to keep closer tabs on how updates to schedule impact their planning cycle. Everyone from the sales team to the board of directors now wants more visibility into the rate at which software development projects are being completed. The challenge DevOps teams face is that software development is an inexact science. Application development projects can just as easily fall behind schedule as they can leap ahead depending on how well code is written.

Regardless of how application development projects are managed, the relationship between DevOps teams and the rest of the organization has fundamentally changed. Unfortunately, expectations are not always realistically aligned with available development resources. A project management application that is widely employed across an organization should make that apparent to all interested stakeholders. In theory, at least, that should result in either the hiring of additional developers or a reassessment of the business strategy.

One way or another, project management applications designed for managing software development projects now play a pivotal role in business planning. The challenge is finding a way to populate those applications with the data needed without requiring developers to help enter data that can already be easily pulled from the DevOps tools and platforms. Otherwise, instead of being viewed as a benefit, the entire project management process becomes one more tedious task that development teams are not going to prioritize over writing code.

March 9, 2023