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We have probably all read recommendations that cyberattack victims should not pay ransom demands because it encourages more crime, and because criminals can’t be trusted to delete data they promise to delete. But what evidence have we seen supporting a claim that criminals default on data deletion? Law enforcement made a point of reporting that...
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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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I'll try to wrap up this issue by handling all the diagnostic cases that I know of with this new [Equality] attribute in Transpire.
https://github.com/JasonBock/Transpire/issues/44
#dotnet #csharp
Pennsylvania, USA
Hello and Welcome, I’m your Code Monkey!
I've still been super busy with my Game Dev Practice Lab, it is now almost Week 3 (almost the third challenge) and things have been going quite great!
Lots of submissions on Challenge #0 Save System City Builder, and some members completed Challenge #1 CCTV Camera System in interesting ways! Also the feedback from my Code Reviews on the Professional tier have been super positive! I'm glad I can help people in such valuable direct ways!
If you haven't seen it yet check it out HERE! Challenge #2 Traffic Controller coming out later this week. (The LAUNCH 20% OFF Coupon is still active!)
Oh and my game is currently on sale! If you pick it up (or if you already have it) I hope you like it, and can you write a Steam review? It's currently sitting at 95 reviews, I'd love to get it to 100! Thanks!
Game Dev: Playtester Finds Mistakes ; Source 2 FREE!
Tech: Claude Code Leaked
Fun: April Fools!
Game Dev
Top 10 Mistakes that playtesting reveals
One of the most valuable things in game development is simply watching players interact with your game and seeing where they struggle. Not guessing, not assuming, actually watching. That's why playtesting is so CRUCIAL!
One dev on Reddit wrote about what they learned from playtesting over 22 indie games, and the interesting part is how the same issues kept showing up over and over again across completely different games.
Some of the biggest ones were exactly the sort of things that are very easy to overlook when you're deep in development. Static menus that make the game feel unfinished which gives a bad first impression, tutorials that only show keyboard controls even though the game also supports controller is another classic beginner mistake.
Demos that include broken levels, mechanics that sound interesting on paper but just are not actually fun, and of course the classic one: the developer assumes something is obvious when it is not. I made an entire video on this very common mistake.
One that is a problem in either extreme is just in terms of game content. Too little or too much is a problem. Either players get bored or overwhelmed.
And a very simple lesson: "Wall of text tutorials are as bad as no tutorial". I highly recommend you to make more interactive tutorials, and use the VideoPlayer component to SHOW not TELL.
These are the kind of lessons that showcase why playtesting is so insanely valuable. After working on a game for months, or years, you are way too familiar with your own game, so your brain cannot comprehend what a completely fresh look into your game looks like. You know where everything is, you know what every button does, you know what the player is "supposed" to understand. But the player does not have that context, so they will get confused by things that seem to you impossible to miss.
So use this as a reminder to get fresh eyes on your game as early as possible. Not just once, but constantly. Watch people play, see where they hesitate, see what they ignore, see what they misunderstand. Because very often you can massively improve how much the player likes your game by just not making these mistakes.
 | I highly encourage you to get playtesters to play your game. No matter how much you try to focus on this problem yourself you can never see the game from fresh eyes. Get lots of playtesters, get them early and often. Start with friends and family, then look on various Reddit's or Discord's for more, maybe look into Steam's Playtesting system and finally publish a free demo (that is already super polished) |
Affiliate
FREE SFX, and Realistic Bundle!
There’s an awesome HumbleBundle this week, this one all about Realistic Assets!
It includes a ton of awesome stuff from some excellent publishers. You can find Vehicles, FPS Devices, Environments, Characters, Tanks, Zombies and more.
All in a super high quality high resolution realistic style.
Get it HERE!
The Publisher of the Week this time is SwishSwoosh, publisher with lots of Music and Sound Effects.
Get the FREE Sci-Fi Weapons: Bullet Hell Sound Effects Pack which is a pack of almost 400 sound effects about all kinds of weapons.
Get it HERE and use coupon SWISHSWOOSH at checkout to get it for FREE!
Game Dev
Source 2 is FREE! (with S&box)
Here's a super interesting game engine story. You might know about S&box, it's an interesting sort of game engine being made by the team behind Garry's Mod and Rust. It's a fork of the Source 2 engine that they've been building for a while.
But until now it has worked sort of like Roblox or Fortnite, in that you build a game that exists inside the S&box platform. However they recently announced that coming soon you will be able to export standalone games and ship them on Steam as if it were made with anything else.
Even more important than that, they have made a deal with Valve to allow those developers to publish those standalone games completely Royalty FREE! Meaning you don't owe anything to either Facepunch or Valve for using this engine.
And that is kind of a huge deal, because it basically means indie devs now have a real path to building games on top of Source 2 tech without having to give up a cut of their revenue. It is not the same thing as Valve directly opening Source 2 to everyone, you still need direct contacts with Valve to get that, but in practice this is almost the same thing since S&box is built on top of Source 2.
A lot of people love Source 1 and a lot of people have been looking for a broad release of Source 2, and this is basically it! Not only that but being Royalty Free is an excellent bonus!
As to why they are doing this? Gary, the owner of Facepunch, basically said how he already has infinite money (Garry's Mod and Rust have both made hundreds of millions) and he wants to give an opportunity to someone today just like he had the opportunity for this to become his job 20 years ago. That's a great sentiment!
S&box itself will be launching on Steam on April 28th. I'm looking forward to seeing what the reception to this engine is. One year from now will we see a mega hit made with this engine? Will all games share that Source 2 look? We shall see!
| I wasn't too interested in this story initially because I thought it was just being able to make executables which I guess is fine, but then I learned how this really means Source 2 is now available and royalty free! From that context this story is massive! |
Tech
Claude Code Leaked!
The big news in the AI world this week is how Claude Code source code got leaked! This wasn't a hack, someone accidentally pushed an update that included a link to a .zip file that contained the entire source code.
By looking at this leak anyone (competitors) can see how they built it, and importantly, what they're planning to build in the future. They're working on the ability for Claude to review what was done in the last session to study improvements for the future, making a "persistent assistant" that keeps running even while the user is idle, how they are focused on long autonomous tasks, deeper memory and multi-agent collaboration.
The source code is pretty massive, 2000 files and 500,000 lines of code. One person quickly built a nice website that has an interactive visualization of how it actually works which is quite neat!
How the user writes their message, it gets packaged into their format, then pushed into the history conversation array, sent to their servers, uses whatever tools it has access to, returns the output, and saves some logic to its internal memory.
It's quite fascinating how it all works, and the website is beautiful!
| I haven't used Claude yet, mostly I just stick with ChatGPT, but I have heard it is great. I also found another website that supposedly has interactive tutorials for learning how to work with it. |
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Fun
April Fools!
It's that time of the year again, April 1st or April Fools! This is always such a fun day, I love it. It's awesome to see all the jokes that everyone makes.
This year one of my favorites is the Payday NPC Game Mode! heh it's so funny to play as a mundane boring NPC, they really went above and beyond in making the trailer. Perfect ending "Don't be a hero!"
Another hilarious one was CKSS which pokes fun at the recent DLSS controversy. It's hilarious to see the dagger at 00:30 turn into something else heh.
The Witcher 3 made Project R.O.A.C.H. which features a physical hobby horse controller.
In terms of general tech, Elgato made a fun lever you add to your Stream Deck. MSI made a Monitor Arm for your cat (which actually looks useful!) or if you want you can make sure you never lose a sock again!
| I have also made my own April Fools video. It's a fun one all about switching from Unity to Notepad, which was actually quite educational in learning what data formats are text readable and could "technically" be doable from Notepad. My previous April Fools videos on Pen Spinning and doing ______ were also super fun to make! |
Is Game Dev Cooked?
https://www.youtube.com/watch?v=p2Wtb35qSzw
Nice overview of AI in game dev, how it's a spectrum from full AI to full Manual and everything in between
Gabe Newell on Half-Life 3 for a decade
https://www.youtube.com/watch?v=Jt0w9YP_wZ0
Funny to see the timeline, going from "confirmed" to "what's that?"
Get Rewards by Sending the Game Dev Report to a friend!
(please don’t try to cheat the system with temp emails, it won’t work, just makes it annoying for me to validate)
Thanks for reading!
Code Monkey
Pennsylvania, USA
AI-native is here! Learn how to adopt this mindset, where AI is your default for work, thinking, and building. Stay ahead in the evolving market.
Pennsylvania, USA
The Challenge: Ops is critical but takes time from innovation
Microsoft operates always-on, mission-critical production systems at extraordinary scale. Thousands of services, millions of deployments, and constant change are the reality of modern cloud engineering. These are titan systems that power organizations around the globe—including our own—with extremely low risk tolerance for downtime. While operations work like incident investigation, response and recovery, and remediation is essential, it’s also disruptive to innovation.
For engineers, operational toil often means being pulled away from feature work to diagnose alerts, sift through logs, correlate metrics across systems, or respond to incidents at any hour. On-call rotations and manual investigations slow teams down and introduce burnout. What's more, in the era of AI, demand for operational excellence has spiked to new heights. It became clear that traditional human-only processes couldn't meet the scale and complexity needs for system maintenance especially in the AI world where code shipping velocity has increased exponentially.
At the same time, we needed to integrate with the AI landscape which continues to evolve at a breakneck pace. New models, new tooling, and new best practices released constantly, fragmenting ecosystems between different platforms for observability, DevOps, incident management, and security. Beyond simply automating tasks, we needed to build an adaptable approach that could integrate with existing systems and improve over time.
Microsoft needed a fundamentally different way to perform operations—one that reduced toil, accelerated response, and gave engineers the time to focus on building great products.
The Solution: How we build Azure SRE Agent using agentic workflows
To address these challenges, Microsoft built Azure SRE Agent, an AI-powered operations agent that serves as an always-on SRE partner for engineers. In practice, Azure SRE Agent continuously observes production environments to detect and investigate incidents. It reasons across signals like logs, metrics, code changes, and other deployment records to perform root cause analysis. It supports engineers from triage to resolution and it’s used in a variety of autonomy levels from assistive investigation to automating remediation proposals. Everything occurs within governance guardrails and human approval checks grounded in role‑based access controls and clear escalation paths. What’s more, Azure SRE Agent learns from past incidents, outcomes, and human feedback to improve over time. But just as important as what was built is how it was built.
Azure SRE Agent was created using the agentic workflow approach—building agents with agents. Rather than treating AI as a bolt-on tool, Microsoft embedded specialized agents across the entire software development lifecycle (SDLC) to collaborate with developers, from planning through operations.
The diagram above outlines the agents used at each stage of development. They come together to form a full lifecycle:
- Plan & Code: Agents support spec‑driven development to unlock faster inner loop cycles for developers and even product managers. With AI, we can not only draft spec documentation that defines feature requirements for UX and software development agents but also create prototypes and check in code to staging which now enables PMs/UX/Engineering to rapidly iterate, generate and improve code even for early-stage merges.
- Verify, Test & Deploy: Agents for code quality review, security, evaluation, and deployment agents work together to shift left on quality and security issues. They also continuously assess reliability, ensure performance, and enforce consistent release best practices.
- Operate & Optimize: Azure SRE Agent handles ongoing operational work from investigating alerts, to assisting with remediation, and even resolving some issues autonomously. Moreover, it learns continuously over time and we provide Azure SRE Agent with its own specialized instance of Azure SRE Agent to maintain itself and catalyze feedback loops.
While agents surface insights, propose actions, mitigate issues and suggest long term code or IaC fixes autonomously, humans remain in the loop for oversight, approval, and decision-making when required. This combination of autonomy and governance proved critical for safe operations at scale. We also designed Azure SRE agent to integrate across existing systems. Our team uses custom agents, Model Context Protocol (MCP) and Python tools, telemetry connections, incident management platforms, code repositories, knowledge sources, business process and operational tools to add intelligence on top of established workflows rather than replacing them.
Built this way, Azure SRE Agent was not just a new tool but a new operational system. And at Microsoft’s scale, transformative systems lead to transformative outcomes.
The Impact: Reducing toil at enterprise scale
The impact of Azure SRE Agent is felt most clearly in day-to-day operations. By automating investigations and assisting with remediation, the agent reduces burden for on-call engineers and accelerates time to resolution.
Internally at Microsoft in the last nine months, we've seen:
- 35,000+ incidents have been handled autonomously by Azure SRE Agent.
- 50,000+ developer hours have been saved by reducing manual investigation and response work.
- Teams experienced a reduced on-call burden and faster time-to-mitigation during incidents.
To share a couple of specific cases, the Azure Container Apps and Azure App Service product group teams have had tremendous success with Azure SRE Agent. Engineers for Azure Container Apps had overwhelmingly positive (89%) responses to the root cause analysis (RCA) results from Azure SRE agent, covering over 90% of incidents. Meanwhile, Azure App Service has brought their time-to-mitigation for live-site incidents (LSIs) down to 3 minutes, a drastic improvement from the 40.5-hour average with human-only activity.
And this impact is felt within the developer experience. When asked developers about how the agent has changed ops work, one of our engineers had this to say:
“[It’s] been a massive help in dealing with quota requests which were being done manually at first. I can also say with high confidence that there have been quite a few CRIs that the agent was spot on/ gave the right RCA / provided useful clues that helped navigate my initial investigation in the right direction RATHER than me having to spend time exploring all different possibilities before arriving at the correct one. Since the Agent/AI has already explored all different combinations and narrowed it down to the right one, I can pick the investigation up from there and save me countless hours of logs checking.”
- Software Engineer II, Microsoft Engineering
Beyond the impact of the agent itself, the agentic workflow process has also completely redefined how we build.
Key learnings: Agentic workflow process and impact
It's very easy to think of agents as another form of advanced automation, but it's important to understand that Azure SRE agent is also a collaborative tool. Engineers can prompt the agent in their investigations to surface relevant context (logs, metrics, and related code changes) to propose actions far faster and easier than traditional troubleshooting. What’s more, they can also extend it for data analysis and dashboarding. Now engineers can focus on the agent’s findings to approve actions or intervene when necessary. The result is a human-AI partnership that scales operations expertise without sacrificing control.
While the process took time and experimentation to refine, the payoff has been extraordinary; our team is building high-quality features faster than ever since we introduced specialized agents for each stage of the SDLC. While these results were achieved inside Microsoft, the underlying patterns are broadly applicable.
First, building agents with agents is essential to scaling, as manual development quickly became a bottleneck; agents dramatically accelerated inner loop iteration through code generation, review, debugging, security fixes, etc. When it comes to agents, specialization matters, because generic agents plateau quickly. Real impact comes from agents equipped with domain‑specific skills, context, and access to the right tools and data.
Microsoft also learned to integrate deeply with existing systems, embedding agents into established telemetry, workflows, and platforms rather than attempting to replace them. Throughout this process, maintaining tight human‑in‑the‑loop governance proved critical. Autonomy had to be balanced with clear approval boundaries, role‑based access, and safety checks to build trust.
Finally, teams learned to invest in continuous feedback and evaluation, using ongoing measurement to improve agents over time and understand where automation added value versus where human judgment should remain central.
Want to learn more?
Azure SRE Agent is one example of how agentic workflows can transform both product development and operations at scale. Teams at Microsoft are on a mission of leading the industry by example, not just sharing results. We invite you to take the practical learnings from this blog and apply the same principles in your own environments.
Pennsylvania, USA
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Pennsylvania, USA
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