Solving the issues with current documentation practices

September 1, 2022

Software development is typically a team endeavor. Developers may work on separate projects but many times their work intersects with modules others are building. Even individuals creating their own applications must refer back to prior work to track source-code changes and limit vulnerabilities. Creating proper documentation for teamwork and legacy code should be a top priority for all developers.

The consequences of missing or inadequate documentation impede application updates and new feature additions, or worse, affect end users by delivering buggy products or missed delivery deadlines.

Phase Change President Steve Brothers was recently interviewed for an article published by SD Times titled, "Solving the issues with current documentation practices," about how software development and maintenance documentation remains an issue. In the interview, Brothers said many times documentation is not a priority because of time constraints – developers feel they are paid and assessed on the code they create, not on documenting the process. And when they do provide comments, once again, project constraints can lead to inaccurate information. This failure to transfer knowledge leads to "slower and sloppier development."

Brothers also talked about coming AI tools that will automatically capture the knowledge developers put into the code, thus creating its own documentation, which never leaves the organization, even when the developers depart. Phase Change's AI tool, COBOL Colleague, will also help automate the process of searching for relevant code and data, which minimizes the need for extensive documentation.

Read the entire article here.

Todd Erickson is a Technology Writer with Phase Change. You can reach him at [email protected].

Improving developer productivity on the mainframe with artificial intelligence

March 3, 2022

Mainframes are the central data repository in an organization’s data processing center. They support thousands of applications and input/output devices while simultaneously serving thousands of users. Most corporate data still lives on the mainframe, and these systems offer advanced capabilities, flexibility, security, and resilience to downtime. Unfortunately, mainframe management and modernization can be costly, risky, and can damage an organization’s reputation by crashing internal and customer-facing applications if developers don't know the system.

Phase Change President Steve Brothers recently authored an article for Techslang.com titled, "Improving Developer Productivity on the Mainframe with Artificial Intelligence," which discusses the roles mainframes play in multiple industries including finance, healthcare, and government, and the difficulties reliant organizations face maintaining and integrating them with modern tools.

To maintain and improve critical mainframe applications, software teams rely on seasoned developers who have developed an intimate understanding of their systems. Unfortunately, many of these experienced programmers are aging out of the workforce or opting for other opportunities – creating a loss of knowledge about those organizations' mainframe applications.

In the article, Brothers explains how AI can automate the process of precisely and accurately identifying code that requires attention — no matter how dispersed throughout the system it might be. By guiding these AI tools through describing the application behavior that needs to change, developers don’t have to search through and develop an intimate understanding of, massive source code bases to reveal the specific lines implementing that behavior. They can now collaborate with an artificially intelligent coworker to augment their own intelligence and be guided exactly to the code that matters.

Read the entire article here.

Todd Erickson is a Technology Writer with Phase Change. You can reach him at [email protected].

How banks should leverage the power of automation

February 16, 2022

Mainframes are widely considered the backbones of many global financial services firms because they deliver unparalleled security, stability, and processing power. From credit card payments and ATM transactions to loans and mortgages, mainframes are relied on by 44 of the top 50 banks to host core applications that deliver secure experiences based on real-time data analytics.

Phase Change President Steve Brothers recently penned an article for TechBullion.com titled, "Banking automation: How banks should leverage the power of automation," in which he examines how these critical mainframes systems also present modernization challenges.

Mainframe systems are complicated and require meticulous processes to continue providing core operational value. While they are fully capable of running newer applications and systems to create new products and revenue streams, their ongoing support and modernization are challenging.

Brothers believes automation and artificial intelligence (AI) could greatly assist banking firms in maintaining and enhancing their mainframes because the key to sustaining these systems is precisely identifying the functionality created by the source code that is intertwined throughout the system — and changing that behavior without unintended consequences. Using a new AI approach that's designed to sift through large quantities of code in the same way humans do, AI-powered tools can aid developers in their frequent search through the deluge of code to rapidly identify where they need to make a change.

Read the entire article here.

Todd Erickson is a Technology Writer with Phase Change. You can reach him at [email protected].

How Leveraging AI Technology Enables Developers

May 23, 2021

Phase Change Software President Steve Brothers was recently interviewed for a TechChannel article on how artificial intelligence (AI) can help software developers increase productivity and reduce risk.

The article, "How Leveraging AI Technology Enables Developers: AI technology enables productivity gains, reduces code querying time, and mitigates risk," was written by Sofia Haan and discusses how AI can assist developers in quickly finding code that produces specific behavior so they spend less time analyzing, refining, and iterating queries, and more time mending defective code and writing new code.

Read the article here.

Legacy system failures expose the application knowledge gap’s harmful risks

February 24, 2021

February 24, 2021

by Steve Brothers

Government system failures during the rush to provide public benefits to alleviate the economic effects of the COVID-19 pandemic publicly exposed the mainframe knowledge crisis that also threatens financial institutions, healthcare providers, and many other organizations foundational to the world economy.

Several states discovered the knowledge-gap’s potentially devastating consequences when waves of unemployment-claims poured into their systems as COVID-19 ravaged the economy in early 2020. The states’ unemployment computer systems crashed trying to process the deluge of claims using mainframes and decades-old programming languages.

But it wasn’t the mainframes or the legacy programming languages that failed, despite what you may have read. It was the lack of available expert programmers necessary to maintain and update these systems to handle the voluminous claims.

According to The Verge’s article, “Unemployment checks are being held up by a coding language almost nobody knows,” Colorado employed exactly one full-time programmer to maintain the state’s COBOL system prior to the pandemic. Back then, Colorado processed roughly 2,000 unemployment claims per week. In March and April 2020, that number rocketed to as high as 104,572 claims per week.

Now governments, non-profits, and private organizations are reviewing their systems’ strategies to learn from these mistakes. If your business relies on legacy systems, you probably should keep reading – and schedule some time with your IT people.

Mainframes are cornerstones

Legacy mainframe systems and software bedrock many of our most trusted institutions, including government services, finance and banking, healthcare, and insurance. In a substantial number of cases the expert developers that created and maintained these systems and software are retiring without a supporting workforce to replace them.

Besides the people that make your business run, your software is potentially the most important resource your organization has. Internal applications likely drive your employees' capabilities and productivity. Customer-facing programs attract new customers, close business deals, and increase revenue. New applications and features can open new markets and opportunities.

To maintain and improve your critical applications, your software team relies on individual engineers that developed an expert understanding of your programs through years of experience. They know the applications and all the accumulated system changes and challenges.

When those experienced engineers depart your business, the developers that replace them must acquire the same application knowledge through training, mentorship, and on-the-job programming. This exercise introduces several material business risks.

Learning on the job

Developers new to software applications typically require 6-12 months of on-the-job learning to become productive, depending on the size of the source code base. To become proficient, programmers may need up to 3 years.

Without qualified software developers knowledgeable about your applications, you endanger your business's operations, reputation, and security. You also risk a significant decrease in your software teams' productivity and efficiency.

Consider the monumental task confronting newly hired or transferred IRS developers last March. Congress passed the CARES Act on March 25, 2020, and then Treasury Secretary Steven Mnuchin announced that individual stimulus checks would be mailed in early April.

To assist with the delivery of economic stimulus payments, the new developers were required to immediately start working with the agency's source code base, which, in 2019, was estimated at nearly 20 million lines of code and includes over 60 years of legislative and system changes. As of mid-May 2020, nearly 20 million people had not received their stimulus checks, and some recipients had problems throughout the year.

These engineers didn’t have 6-12 months to become productive. They had to hit the ground running on day one. And without the benefit of weeks or months of training and on-the-job learning, they didn’t have the application knowledge necessary to understand how even simple changes could affect entire applications.

And let's not forget the productivity loss due to the remaining IRS's experienced engineers for training, mentoring, and supervising the new recruits.

What’s your risk?

Your situation may not be as dire as what the IRS faced – for now. But how much time can you really give your new developers to learn the system, and how much productivity can you afford to lose while your experienced programmers train and supervise them?

How much do you trust the developers that have just started working on your critical applications?

How confident will you be when your CEO or Board of Directors asks for assurances that the next customer-facing application update will not result in outages and lost revenue – especially if the update was programmed by a developer you hired just weeks ago?

Your software is a critical part of your organization, especially if you rely on legacy mainframe systems. You must have a plan or tool that keeps the code running and bridges the gap between retiring and departing developers and the people that will replace them.

Steve Brothers is the President of Phase Change Software. You can reach him on LinkedIn or at [email protected].

Can AI solve the engineer shortage?

May 28, 2020

May 30, 2020

by Todd Erickson

The COVID-19 pandemic has revealed workforce shortages in a number of industries, including healthcare, food retail, and cybersecurity.

The related financial crisis and government financial assistance requests have also demonstrated a critical need for legacy system developers. The recent performance issues experienced by these financial assistance programs have exposed how dependent our financial and public infrastructure are on legacy and mainframe systems.

Phase Change COO Steve Brothers recently penned an article for ColoradoBiz Magazine about how the legacy application skills shortage threatens the software that underpins a great deal of the world's large financial and government systems.

He also talks about how artificial intelligence (AI) can be extremely effective in helping legacy application maintenance and development by introducing automation into the process, improving project management efficiencies, and by shortening the steep training curve typically experienced by developers new to these systems.

Learn more about how the improved productivity and efficiency AI brings to software development could be instrumental in maintaining and improving our critical legacy and mainframe systems.

Can AI solve the engineer shortage?
by Steve Brothers
ColoradoBiz magazine
May 15, 2020

Steve Brothers is the President of Phase Change Software. You can reach him on LinkedIn or at [email protected].

Todd Erickson is a Technology Writer at Phase Change Software. You can reach him at [email protected].

Colorado Inno profile explains how AI agent improves developer productivity

May 8, 2020

May 8, 2020

by Todd Erickson

Colorado Inno.com Associate Editor Nick Greenhalgh recently interviewed Phase Change President Steve Brothers for a profile story titled, "Golden startup's AI aims to make developers more efficient," that explains how our technology operates as a subject-matter expert and will improve software-developer efficiency and productivity, especially for industries that rely on enterprise software.

Read more at ColoradoInno.com.

Todd Erickson is a Technology Writer at Phase Change Software. You can reach him at [email protected].

Phase Change CEO Steve Bucuvalas featured on the InfluenceNow! podcast

February 11, 2019

February 7, 2019

by Todd Erickson1

Phase Change’s Inventor, Founder, and CEO, Steve Bucuvalas, was featured in the January 31, 2019, episode of the InfluenceNow! podcast, hosted by Justin Craft2.

The InfluenceNow! podcast highlights startups, exceptional business influencers, and ideas from a variety of industries that influence the world.

Steve and Justin discussed how Phase Change and the technology behind Mia, the first cognitive agent for software development, became a reality.

The interview begins with Steve describing his career leading technology and artificial intelligence (AI) groups in financial services and insurance companies, and his subsequent entrepreneurial career starting and selling two different companies. He tells the story of how a single conversation with the buyer of his second company led to his interest in applying AI technology to the problem of software-development productivity.

At the closing, the buyer said to me, 'What's wrong with you guys in software? AI has changed financial services extraordinarily - increased our productivity 100 times,' which is accurate. 'Why can’t you do that with your own industry?'

That moment led Steve to research the barriers to applying AI to software development, and the development of the human-centric principles that led to the creation of the Mia cognitive agent.

The podcast continues with Steve and Justin discussing why organizations that rely on applications written in the Common Business-oriented Language (COBOL) programming language are Phase Change’s first target market.

COBOL is this 40-50 year-old language that has atrocious legacy problems. Because the code has been around [so long], it runs 85% of the world’s financial transactions and [there’s] 220 billion lines of [active COBOL] code. The programmers are all in their 60’s and they all want to retire, but they keep getting incentives to work a few more years because no one wants to learn COBOL. In fact, some of the kids in computer science [college courses] have never heard of it.

Justin and Steve conclude the interview discussing the productivity gains realized by Mia and Phase Change’s technology, and when it will be generally available.

To learn more about how Steve and Phase Change Software will radically improve software productivity, watch the podcast video below or listen to the audio podcast.


1Todd Erickson is a tech writer with Phase Change Software. You can reach him at [email protected].
2Justin Craft is the Founder and CEO of Cast Influence, a Denver, Colorado,-based turnkey marketing agency. Phase Change Software is a client of Cast Influence.

Phase Change unveils COBOL Colleague product website

December 19, 2018

December 18, 2018

by Todd Erickson

Phase Change announces the launch of its initial product website – CodeCatalyst.ai. The website will support the company's market entry product, COBOL Colleague, the first cognitive tool for software development, by targeting organizations that rely on COBOL-based applications for critical business operations.

The CodeCatalyst.ai website details how COBOL Colleague will assist COBOL reliant organizations with their unique issues, such as a vanishing workforce, lost application knowledge, and lagging productivity.

COBOL Colleague reads-in the source code, extracts the embedded concepts, discovers the dependencies, reveals the buried knowledge, and becomes an expert that never tires and never leaves.

Natural-language-interaction enables developers and stakeholders with limited COBOL experience to collaborate with the cognitive agent and work productively with their COBOL applications.

Find bugs and dead code in seconds, not minutes or hours. Make changes with full knowledge of the downstream impact. Confidently add new features, products, and services. Empower anyone with a basic understanding of COBOL to interact and engage with your COBOL applications.

Everything you dreamed of in COBOL-based environments is now a reality. Visit CodeCatalyst.ai.

Todd Erickson is a tech writer with Phase Change Software. You can reach him at [email protected].

Phase Change will bridge application knowledge silos

July 10, 2017

July 10, 2017

by Todd Erickson

Members of Phase Change's management team address how our technology will bring together an organization's siloed application knowledge to enable faster responses to market demands.

It's a paradox. Your most successful applications get larger and more complex with updates, upgrades, and new features until they become difficult to change and adapt. Now they are hard-to-manage legacy systems that cost ever more time and money to remain valuable.

One of the main reasons applications become difficult to maintain is that knowledge silos emerge – where various people in development and other departments understand small portions of the code, but no one person knows the entire code base.

Then when you bring people together to develop new features that will address market demands or opportunities, each contributor only knows his or her portion of the application code, each person has his or her own mental model of the code, and all of that knowledge is difficult to share.

Learn how Phase Change's assistive AI agent will bridge knowledge silos by understanding the entire code base, presenting a complete and accurate model, and collaborating with engineers and stakeholders.

Todd Erickson is a tech writer with Phase Change. You can reach him at [email protected].

Contact

Phase Change Software
13949 W. Colfax Ave
Building 1, Suite 205
Lakewood, Colorado 80401
Phone: +1.303.586.8900
Email: [email protected]

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