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Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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Fritz introduces a new command-line project we're building with C# together on his live streams, and recaps the initial decisions and construction of the project.
Source code is available at: https://github.com/FritzAndFriends/CodeMedic
Original video available at: https://www.youtube.com/live/R2HiNg2ACy0?si=xAF5kjlT1s8IdwTv
Watch Fritz code live here on YouTube and on Twitch
https://twitch.tv/csharpfritz
#csharp #dotnet #console
You’ve heard all about AI and IDEs. At this point, they are a dime a dozen, and many of them actually work pretty well.
But what sets them all apart?
A better UI? Better LLMs? Local AI?
I’ve used several of these IDEs, and most often they all do the same things and do them fairly well. When I saw yet another such IDE, I had to find out if there was anything that set it apart from the others.
It only took me about five minutes to figure out what makes Trae stand out. I’m going to show you what that is by way of creating a Python app that creates a Dungeons & Dragons character sheet. Yeah, let’s get nerdy.
Before we actually start using it, you might want to know how to install it. Trae can be installed and used for free (although you get more bang for your buck when you pay for a license) on macOS and Windows. There is also a waiting list for the Linux version, which you can sign up for on the project’s main site.
I installed Trae on my MacBook Pro running macOS Tahoe, and it installed perfectly. After the installation was completed, I opened Trae and discovered that I did have to sign up for an account. No problem, as it was free.
After signing up for an account and logging in, I was greeted by the Trae AI prompt (Figure 1).
Figure 1: The Trae AI prompt is very easy to figure out.
Alright, it’s time to get our D&D on.
With my decision made as to what I wanted Trae to do for me, I typed my prompt, which looked like this:
After hitting Enter, Trae went to work. At first, everything ran like any other AI-powered IDE. Out of nowhere, however, Trae gave me a warning that there was a Python library that needed to be installed for the program to run. To my surprise, Trae offered to install it for me.
Sure, Trae, go right ahead.
It worked. In seconds, Trae had the missing library added, without me having to figure out the exact name of the library and use PIP to install it.
Impressive.
This actually happened three times, and each time Trae handled it with ease.
I’m digging this.
It took Trae roughly two minutes to create the program. I copied the resulting text into a file named dnd_character_creator.py and ran it with:
The program asked me tons of questions related to creating a D&D character (Figure 2 – you know the routine). When the interrogation was complete, I could scroll through the terminal to see the results, but that’s all.
Figure 2: Running my new D&D Character Creator in a macOS terminal window.
Back to the AI prompt, where I said:
Hit Enter, and Trae went back to work.
Once again, Trae had to install another Python library, which I allowed, and it happened without fail. When Trae finished, I copied the new code into a new file and ran it.
To my curiosity, the program didn’t write the results to a file, so I had to go back to the prompt and inform it that it hadn’t written the results to the file. It ran through the troubleshooting process and worked its magic.
That’s when I realized something: I didn’t need to copy/paste the code because Trae actually wrote it to a file itself.
Nice.
I then changed into the folder /Users/jackwallen/Documents/trae_projects/DD/ and ran the correct file.
Huzzah! It worked. I now have a Python script to help me create D&D characters.
In the end, what I found that set Trae apart was its ability to install the necessary libraries required to create the program. I didn’t even need to know what libraries were necessary for the Python program, which was a big help.
Understand that I only scratched the surface of using Trae, but even just using it without getting too deep into the woods, the IDE really impressed me.
What other features does Trae offer?
As I mentioned, Trae can be used for free, but that plan is limited to:
If you upgrade to the paid plan $10/month (first month only $3), you get:
If someone like me can create complex Python programs by way of AI queries and follow-ups for troubleshooting, anyone can.
Give Trae a try and see if it doesn’t become your new favorite AI-powered IDE.
The post Trae IDE Auto-Installs Python Libraries as You Code appeared first on The New Stack.
JetBrains CEO Kirill Skrygan, 38, was all in on tennis — he played and was one of the best in the city of St. Petersburg. But at the ripe age of 10, his parents realized that the funnel of tennis professional begins very wide but quickly narrows for people who want to become professionals. So they took him to a Russian mathematical school, where he learned how to program. He went on to attend St. Petersburg State University, where he became a software engineer.
The Netherlands native began as a junior developer working for American health care companies. In his early 20s, he joined JetBrains as a team lead, eventually moving up to become the CEO of JetBrains, which specializes in creating integrated development environments (IDEs) such as IntelliJ IDEA, PyCharm and WebStorm. He joined the company as a junior developer in 2010.
Skrygan spoke with The New Stack about his journey from junior developer to CEO, and shared his advice for how other developers can make the transition from coders to management.
Skrygan is very clear on what brings him purpose in his work, which ultimately lead to him to transition into management.
“What drives me is actually the impact I can bring to the overall technological landscape of the whole [of] humanity,” he said.
He spent 10 years leading the Rider IDE team, where the desktop application developer fell in love with the cross-platform language, Kotlin, which was used to create Rider’s frontend.
“I immediately fell in love with Kotlin because it’s so elegant and […] so flexible,” Skrygan said. “What amazed me from day one is [that] it could be very strict and enterprise-ish (like Java) on one hand, but on the other hand it might be very, very hipster-ish — like OCaml or Scala, or something like that.”
Then he became the department head across JetBrain’s IDEs, where he managed approximately 650 people.
“You can actually drive the business strategy, product strategy, marketing, everything. I love it,” he said.
But even when developers want to move into management, there can be bias and barriers that hold them in engineering roles. For instance, some companies suffer from a “grass is always greener on the other side” mentality that promotes outsiders over existing employees. I asked Skrygan if that was an issue he had encountered.
“You need to invest in hiring juniors [and] interns, raising them, because sometimes juniors are so active, passionate, and this is just very important for the whole spirit of the company, of the team.”
– Kirill Skrygan, JetBrains CEO
That wasn’t an issue at JetBrains, he replied, adding that companies should have to cultivate both promoting internal talent while scouting strong recruits.
“You couldn’t rely only on external ‘grass,’” he said. “You have to raise your own talents. Moreover, it’s not just about highly-paid stars you would hire from the outside. Yes, you need to hire those, but at the same time, you need to invest in hiring juniors [and] interns, raising them, because sometimes juniors are so active, passionate, and this is just very important for the whole spirit of the company, of the team.”
It helps to be in a company that prioritizes cultivating internal talent. JetBrians, for instance, collaborates with universities on internship programs.
“We’re doing a lot to invest our own money to educate young generation people; and yes, we also hire some of these talented people to JetBrains,” he said.
I asked Skrygan what skills or benefits programmers bring to management. He replied that good software engineers tend to be very structured and use engineering systems. They understand that you need a solid architecture before developing an application, he said. They have to show logical thinking about both structure and architecture, he added.
“This level, this way of thinking, is very good for managers because when you define business strategy, it’s basically some logic based on presumptions,” he said. “You have some sort of architecture of logic based on some prerequisites. So this structurality, this logical thinking, really helps.”
It’s a cliché to say programmers are introverts — but whether you are or aren’t, programmers who want to move into management should develop and demonstrate people skills if they want to move into management, according to Skrygan. This can take some real work and study, he added.
“Being a manager is not like writing code. You have to be empathetic. You have to work with people. You have to understand their things,” he said.
Developing people skills isn’t a simple step. You don’t just “solve” the people problem and move on.
“You have to be individual with all the people,” he suggested. “You cannot be, like, one size fits all for different kinds of people.”
Technical managers must have both logical capabilities and the ability to relate to and manage people.
– Skrygan
Only a small percentage of engineers have that skill, he said, but they need to have both the logical capabilities and the ability to relate to and manage people.
“What I would suggest is to dive deep — more into social, humanitarian aspects and sciences, psychology, group psychology, sociology, or some other things, because this just gives different angles,” he said. “Tech people are very logical thinkers, and they have their own strict angle, and sometimes they do not understand why humans, or humans at scale, behave this way, this strange way. It’s silly, but it’s the way it is, and you have to acknowledge that, and understanding [other] sciences should definitely help.”
He added it helps to be a very agreeable person, which some engineers are not. This can make it difficult to advance in the corporate hierarchy, he said. One thing engineers can do to show they’re agreeable is to realize roles overlap now. That means developers should be ready and willing to help with domains outside their speciality, such as product management or marketing.
But at the same time, you also have to balance that with having strong, deep opinions.
“You have to show it in, of course, in [a] correct way, so… the management understands, hey, he’s not just about this narrow scope; this person is about much broader sense-making, and this person has an opinion about that,” he said. “That’s valuable.”
He also recommended getting an MBA or taking MBA-style courses to understand business.
But after acquiring management skills, how can developers convince their company to give them a chance?
That will depend somewhat on the company culture, but he said at a basic level it means getting recognition from management.
“If I can generalize these things, I think that proactiveness and initiative right now would be also interesting,” he said. “Just being an operator in a very transparent way is not quite enough.”
For instance, if you’re given a job, do it with initiative and proactivity. That might look like, for instance, taking charge of tickets to ensure they’re handled if your company just pools them all and expects developers to just do them in their “spare” time.
Developers should also realize that the feedback loop for managers is different from that for developers. It’s much more complicated, he said, but it’s necessary.
“From my experience, people who are not learning because they’re too stubborn or too stuck up, [that] usually prevents them from being a good managers.”
– Skrygan
“It works through layers of people, levels of organizations, but you have to be honest with yourself; you have to get the feedback, and you have to improve yourself,” he said. “Being able to frankly get this feedback and get better is important stuff. From my experience, people who are not learning because they’re too stubborn or too stuck up, [that] usually prevents them from being a good managers.”
He also said there’s a difference between management and leadership. Leadership is actually about saying no rather than yes, he noted. That’s because leadership is giving a direction, a focus.
“It’s very easy to say yes to everyone, but if you will say yes to all the ideas you will have, … you will not deliver,” he said. “You need to lead people towards this focus, and you need to engage and inspire people so they actually want to do this.”
Finally — although it may be old-fashioned in today’s work world — Skrygan also believes loyalty is an important trait for those who want to move into management.
“It sounds silly, but it’s sometimes about some of the projects that your managers can delegate to you as a developer, which might not contribute to your salary bonus by the end of the year, but this is what the management asks you to do,” he said. “If you do this, they understand: hey, this is a person we can rely on, who values the interest of the whole company, of the whole organization, even more than their own.”
The post JetBrains CEO on How Developers Become Leaders appeared first on The New Stack.
Most of the conversation around AI agents today revolves around bots writing code. This didn’t come out of nowhere; Software engineering is the most common use case for AI systems, and code-writing tools are reaching eye-popping valuations. But inside companies, something more fundamental is shifting: AI agents are becoming internal “operating systems” that connect and orchestrate data flows between software tools, changing the way we all work, not just the engineers.
At Block, our engineers built an AI agent framework called goose and released it as an open source tool for anyone to use with any large language model. Initially designed for writing code, we quickly realized that for goose to reach its full potential, it needed a standard way to communicate with the dozens of tools that people use daily. Recognizing this same challenge, Anthropic was developing what would become the Model Context Protocol (MCP). We began collaborating early in MCP’s development to help shape this open standard that bridges AI agents with real-world tools and data.
Today, 60% of our workforce — around 6,000 employees — use goose weekly. It serves as a central conductor, reading and synthesising data across dozens of MCP-powered extensions including Slack, Google Drive, Snowflake, Databricks, Jira and others. Just months ago, it would take days of manual labor to read Snowflake dashboards, pull context from recent Slack chatter and generate a weekly Google Doc with insights and flagged anomalies. Now humans orchestrate this process in minutes, directing goose to the relevant data while applying judgment about what matters most.
Unlike the headlines, this isn’t a story about AI replacing jobs. At Block, we believe the shift is about redistributing access to problem-solving.
Most companies rely on handoffs. A product manager submits a ticket. An engineer builds it. A support team flags a recurring issue. A developer scripts a fix. These workflows protect quality, but they slow things down. AI agents like goose are collapsing that distance by helping people take action on their own instead of waiting on others.
Take customer support escalations. In the past, when a support agent noticed an unusual spike in refunds, they would file an escalation ticket and wait three to five days for the data team to pull transaction analysis, receive raw spreadsheets, manually create a summary and post findings to Zendesk. Now that same agent asks goose to “analyse the last 30 days of refund spikes” and within 30 seconds receives a complete analysis with patterns identified and an automatically generated Zendesk-ready summary.
By allowing users to choose a preferred model and by connecting to internal tools, goose enables teams to move from idea to prototype without waiting in a queue. A support agent can surface a dashboard. A security analyst can write a detection rule. A designer can test live functionality based on user feedback. None of this requires code expertise.
This kind of access was previously off-limits to most employees. That’s starting to change.
Goose is part of a wider shift within Block and at other forward-thinking companies: recognising that AI’s most valuable role may not just be in what it builds for users, but in what it unlocks for teams. By lowering the barrier to experimentation, internal AI tools are giving people the confidence to test, iterate and solve problems themselves.
This doesn’t remove the need for engineers. If anything, it strengthens their impact. It clears the backlog. It reduces bottlenecks. And it makes the space for more complex, strategic work to get done.
As with any new expansion of capabilities like this, this type of transformation requires careful design. At Block, we’ve implemented specific policies that govern how these AI connections work across our company. Any tool that handles sensitive information requires legal approval before it can be deployed. We maintain curated lists of approved extensions, so employees can only install tools that have passed our security review. And we’ve built smart boundaries directly into the tools themselves. Some automatically avoid accessing confidential databases, while others separate what users can read versus what they can modify. These aren’t bureaucratic barriers; they’re design choices that let teams move fast while keeping important information secure.
The long-term opportunity isn’t just speed or cost savings. It’s resilience. Companies that embrace this shift will be less dependent on rigid workflows and more responsive to the people closest to the problem. They’ll be able to move faster without compromising safety, and solve at the edge without losing control at the core.
That’s what we’re learning with goose. And that’s the direction we believe enterprise AI is headed. It may not make headlines, but it’s changing the way organizations function at their core.
The post AI Agents Are Morphing Into the ‘Enterprise Operating System’ appeared first on The New Stack.
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