Voice of the DBA

Most of us will work on software for our organization, and we might not want to or care about the end result being great. We do want it to work, and we want clients to find it useful. If we have external customers using our systems, maybe we want it to be great. In most of my experience, people are often proud of their work, sometimes ashamed, but not many people spend a lot of time making their corporate applications great. Often because we don't have (or aren't allowed) the time to do so. Read the rest of Building Great Software

Brent Ozar has a series of database animations posts, where he tries to explain what work is done by SQL Server during certain operations, such as Index Seeks and Page Splits. These show how the engine might need to read or update various pages as it tries to perform operations. Both experienced and novice SQL Server people might think that these are interesting, but not that useful. I think they're great. Read the rest of Imagine the Physical World

Apparently, Meta did what a lot of employees suspect their management will do: use AI to lay off people. In this case, there is a report (and lawsuit) that Meta used it's AI-integrated HR platform to make decisions about who to let go in a layoff. The rumor is that the AI used productivity metrics to choose who was the target of the layoff. As with a lot of AI failures, this appears to be another case of poor communication guiding the AI, or the AI not actually taking individual situations into account. A number of the people terminated were on maternity/paternity leave, which is a protected activity. Others may have been on other medical leave, though for privacy reasons, the article doesn't have firm data to prove this. The lawsuit will likely bring more of this out, but this appears to be a case not just of AI making decisions, but of poor behavior from management. Plaintiffs were discouraged from taking leave off, which is something sh****y humans have said to people for decades. We need you; your baby or family isn't important, so don't use your leave. It's one aspect of working in the US that is way worse than overseas, where there are more employee protections. Read the rest of The Quiet Part

Recently, I noticed my son was coming home later and going to work earlier. He typically works a 9/80 schedule as a software engineer, but at times he might work extra hours on a deadline. His company tries hard to keep employees working a set schedule without overtime. Unless there is a need, after all, this is software. However, when they are on a deadline, management warns people, and they try to manage overtime to reasonable levels to avoid burning out employees. I asked him if he was extra busy or if AI was encouraging extra hours. He told me this was a short-term project with a few more hours, but mostly the team was decompressing a bit after work. I completely understood that as I've spent my share of time with co-workers at theend ofday, sometimes sharing a drink or meal nearby, sometimes just chatting in the office or the parking lot. Read the rest of Are You Working More Hours?

T-SQL Tuesday #200 was in July, hosted by Brent Ozar, and it was a great topic: How do you recognize a bad query? In the age of AI, when lots of people will get queries written by others (people or AIs), how can you easily and quickly review code? Review is already a challenge in the software world, and I am sure it's going to be even more challenging as people let machines author more database code. Lots of you might hope that an AI agent will write better code than your average developer, but I don't know if I'd count on that. There is a ton of poor query examples on the Internet and that's where AI models are trained. You need some sort of feedback loop, good testing, and strong guidance if you want better query code. I think it's as likely as not that AIs will produce poor queries just like humans. Just faster. Read the rest of Finding Bad Queries

When we look at the performance of software, we use Pnn notation to indicate the latency of an issue. A P95 problem is one that exceeds the time that 95% of the other queries take. In other words, this is the 5% slowest things happening, which can include database slowdowns that impact your application. For many years in software development, we have tended to work on the P95 or P90 issues, the slowest items. This is primarily because those can make a big difference to the system's performance. If I fix the slowest things, then the system feels faster. Certainly, I know lots of DBAs and developers will apply this logic to database queries. They focus on the slowest queries and tune them to improve the system. If most things are quicker, especially the things most users notice, then the system feels faster. Read the rest of Fixing P1 Queries

Lots of AI usage has been spent inside companies on building new software. Sometimes people are trying to rebuild existing software. I've seen more than a few articles say that Slack is dead (it's changing), or Monday is dead, or some other SaaS isn't going to survive because people can vibe code their own replacement. I know a few people trying to do this, with very mixed success. I saw this post from Jason Friend of Basecamp, where he noted that most products wouldn't exist if everyone were an entrepreneur. This is because the great products exist precisely because an entrepreneur had a great idea and followed it through. They made mistakes, they learned, and they spent a lot of time getting the product right. The coding was likely a part of this, but the mistakes, the changes of direction, the decisions on what to add or take away, those are time-consuming things not shortcut by AI. The coding isn't the big delay in lots of products. A great response to the post notes this: there are many decisions that go into a product. Many people don't think about all those decisions. Read the rest of Building Your Own Software

The first one is hard. The rest are boring. I heard this statement from someone recently, and it sounds like something a technical person would do. It's been a goal of mine, or maybe a direction to aim for, though I sometimes think that goal is more aspirational than actual. It can be hard to do that for every task. The first time I tackle something, it should be hard. It's new work. It's a new process/code/thought/action/etc. It's unfamiliar, and I spend more time on it than I want. After that, I'd hope I could repeat the thing again in much less time. That's the goal, and that's what we aim for in a lot of DevOps work. Make the things we think are hard, less hard. Make them boring by codifying things, using automation, and have the computer replicate the task. Read the rest of Make It Routine

This past week I saw an article on eWeek that the newest OpenAI GPT-5.6 (Sol) model has deleted local files and live data. Files I'm less worried about, but data concerns me. There are lots of file backups, and certainly version control should be enabled for any developer tasks on which an AI works. However, data is harder, since it can change quickly, especially in live environments. There are different reports, some of which seem like more human error issues than the model's, but we should account for human error when we use models. In one report, a model had access to a live production database and cleared tables for integration tests. Database testing is hard, as I've learned over the years. Many developers don't think about how testing works with live data and how it is different from mocks and stubs. It is different, and if you use a lot of testing frameworks on live databases, you run the risk of there being issues. You could have data loss, and almost certainly will have some level of downtime disruption. Read the rest of Another Model, More Data Loss

I had a request from a customer recently who asked if we could give them a report of their database server instances and include CPU usage. This request was filtered through an account executive, so something was lost in translation, but I was confused and asked for clarification, as asking for CPU usage is kind of like asking how fast you were traveling in your car. There needs to be more context. If someone asked you for a report of CPU usage for a database, what would you expect? How would you report this? I'm sure the person asking might make a difference. A fellow DBA, your DBA manager, or maybe an executive could all view this differently. I want to know how things are performing, if there is a trend, or maybe if we are getting value for the hardware we've provisioned, depending on my role. Read the rest of What is CPU Usage?

What if I got hit by a bus? I'm sure many of you have heard some variation of this, or used it, or maybe your boss told you to be ready in case you (or someone more important) gets hit by that vehicle. This is the "bus factor," and it's often used in reference to preparation for unforeseen events. Not literally someone getting hit by a bus, but perhaps a sudden accident that takes someone away from work (hopefully not fatal). Perhaps it's someone leaving for a new job. Maybe it's retirement, which is something my boss and I at Redgate chat about periodically. Don't worry, I'm not planning on retiring anytime soon. I expect to work until at least 2033 and possibly longer. Likely longer, I'm a weird work-a-holic in some ways, and I love my job. Read the rest of The Mythical Bus Accident

The AI boom is still growing like crazy. Many organizations are trying to learn how they can use AI to improve operations and become more efficient, at a reasonable cost. Plenty of companies are spending crazy amounts of AI tokens, sometimes blowing their yearly budgets in months and not necessarily receiving substantial value back. Some companies are trying to train AIs to understand their operations and perhaps reduce their other costs, primarily labor. Still others are tip-toeing in the waters of AI LLM use and conducting smaller experiments, with limited access to AI technology. Meta has been a company on the forefront of trying to train AI based on the work employees already perform. There has been plenty of concern that their efforts are designed to lower headcount and replace humans with AI agents. That might or might not work, though I don't expect a lot of organizations to do this. It's likely harder than any of the hype suggests, and most organizations have much more complex types of operations than Meta. Read the rest of Security and AI Fail

I recently recorded a session with Ken Muse and a Redgate Flyway Solution Engineer. It was a fun session using GitHub and AI, and better managing the code in an automated fashion to bring some determinism to AI coding. I'm hoping it will be released soon, and you can see a vision of how you can better wrangle your AI agents and reduce risk and increase reliability. When we started our discussion, Ken noted that he is an AI forward deployed engineer for GitHub. His job is to work with teams in how to use agentic coding. When we were first prepping, I had never heard the Forward Deployed Engineer title, which is apparently getting popular. It was in an issue of the Pragmatic Engineer Deep Dives last year, and I must have missed that issue. Apparently, this is a role that works part of the time with customer teams and part of the time with product or engineering teams. In other words, a software engineer with a new title who gets paid more than a software engineer. Read the rest of Forward Deployed Engineers

Oh, how I wish I could make you learn. How I wish I could coach, guide, inspire, or even bribe you to learn more about your job, or things related to your job, or even things in life. I wish all of you would improve your skills, but more, I wish you would want to improve your skills. I find lots of people who do want to get better, but far too often, people aren't trying to improve because they want to coast along at their jobs. I get it. You're stressed and busy at work, though hopefully not too often. You have challenges at home, kids to raise, parents getting older, financial stresses, concerns about politics or sports or exercise or diet or just about anything in the world. We all have things that take mental energy in our lives. How/why/when should I add another thing to the list? Read the rest of I Can't Make You Learn

I saw this article and thought, surely there's nothing I could use in here: 10 Best AI Prompts for Everyday Tasks. Quite often, when these articles appear, they are very high-level and contrived examples of things that I rarely find myself doing. So I clicked the link. Read the rest of A Quick Second Opinion

Tomorrow is the United States 250th Independence Day celebration. I've been hearing about this on the radio for weeks, and it's struck me that I've been alive and lucky enough to experience both the 200th (1976) and the 250th (2026) milestones. I'm not sure either is more amazing than any other 4th of July, but the round numbers stand out. Read the rest of Independence Day.

Satya Nadella talked about cognitive coverage in the age of AI, about being able to understand and manage AI agents to get work done as a software developer. The interview from Hard Fork Live covers the future of work and comfort in this new age. This reminds me of a book that the CEO of Redgate recommended, Reshuffle. I love the book, but it's slow reading as I constantly stop and think. Work is changing; it's becoming unbundled and re-bundled in different ways, and many of us will have to learn to work in new ways. Not all of us, but many of us. Some might see their day-to-day efforts change little; some will not recognize their job a year from now. As with anything, lots of us will be in the middle with some changes, some status quo. That's certainly where I am with AI assistance. Read the rest of Cognitive Coverage

Is it worth continuing to run SQL Server when PostgreSQL licensing is zero? Rebecca Lewis has a well written post on why that looks at some of the pros and cons of paying for SQL Server instead of moving to PostgreSQL. She starts with some of the things PostgreSQL does well, of which I think the Extensibility is really cool. SQL Server has some of this in CLR and the non-SQL language support, but those seem kludgy and complex to me. They aren't really integrated into the SQL Server platform. They're good, but I do wish vendors or the community could add some extensions in a way PostgreSQL does. Of course, I also worry about stability, so maybe this is a wish that isn't really a great idea. Read the rest of SQL Server Still Wins

I had a very interesting conversation recently with a longtime DBA who was worried about using AI in their database work. The Redgate State of the Database Landscape 2026 report showed that the vast majority of you (99%) are getting value from AI, so clearly it's being used. However, this individual was concerned that using AI for tasks would not engage their brain, and they might lose some of their SQL skills. And they want to use their brain at work. Read the rest of I Want to Use My Brain

I've visited a number of customers in the last few years who require most people to work in the office. Recently, I had the chance to go to Epic Systems, just outside Madison, WI, USA. They are a medical records software provider that was very reminiscent of Microsoft in some ways, and quite different in others. I published a blog with some pictures, so you can see how cool this office is in person. Epic has all their employees coming into the main office every day. They are flexible if you have needs, but the expectation is that employees go in every day. I believe this is also their policy, and culture, in various offices around the world. Read the rest of Spending Time in the Office

Last week we had a training session at Redgate Software on the Cloud. One of the first slides from John Q Martin asked the question, "what is the cloud?" The next slide had the answer: it's just someone else's computer. I mean that's true, but it's not Grant's computer. He's got a creaky, 4 year old HP that I don't want running my workload. Read the rest of What is the Cloud?

Change is inevitable for most of us. The jobs we hold, the places we work, the people we know, even our families grow and change over time. As I get older and live longer, I've learned to accept, appreciate, and flow with changes. I might resist, delay, embrace, or anticipate tomorrow, knowing there is always a positive and negative side to things. This week, one of my colleagues retired. Annabel has been a part of Redgate nearly as long as I have, and we've worked together for many years. If you've ever attended a Redgate event, live or online, she likely had a part to play in the planning, organizing, execution, financing, and every other part of the process. Read the rest of Changes, Happiness, and a Few Tears

For a while, I kept seeing that the cost of writing code was approaching zero. So many people felt that with an AI LLM, the costs would go way down to produce software. I'm not sure that's true. In fact, some companies are finding they spend more on AI tokens than salaries. However, the ability to produce more code, experiment with ideas, or generate proof of concepts has gone up. Whether it's worth the cost or not depends on the engineer, but some organizations are finding that they can try more things than they would ever had time to try in the past. The time of engineers was the constraint, and if you can afford the cost, AI LLMs can relieve that time pressure. Read the rest of Follow Your Hunch

Both as a DBA and developer, I've had plenty of immediate, this-is-broken, fix-it-quickly issues. Usually, I, or someone else, wrote some bad code and somehow got it deployed. I mean, I do test things, and I would (probably) never change code after I'd tested it to fix that one little annoying thing, like the formatting. I'd (almost) never do that, and I'm sure you wouldn't either. Yet somehow bugs slip in at times. Those are the acute issues, and they can be hard to fix at times, but often we can reproduce the problem in development and build a fix. Sometimes we even spot the issue quickly and just fix it in production. I'm sure you never do that, but I have had that experience myself a few times. Read the rest of The Slow Growing Problems

Bjarne Stroustrup is the creator of C++. I read a few of his books and alternately loved what he'd done and hated having to write C++ code in university and at a few jobs. I found it tedious and hard, though arguably better than C once you had a decent set of classes structured. BTW, I love his website, the basic text view of the world, which is how I have built a few sites on my own. I caught an interview with him and this short response on AI and coding. He had this quote: "Senior developers are already retiring rather than deal with it." He doesn't love the results from AI, which is fine. And it's not what I want to talk about today. Read the rest of Would You Retire Rather Than ...

I ran across a statement that seems exciting to me as someone that has written a lot of code in their career. It said: "Many of the "modern" software practices of the last decade were early adaptations to this shift, even if we didn't articulate them that way. Immutable infrastructure. Stateless services. Containers. Blue-green deployments. Infrastructure as code. These ideas all share a common premise: never fix a running thing. Replace it." These are a few sentences in this piece on the death and rebirth of programming. That's how a lot of software developers have viewed the world during the last decade and we've seen a lot of software advances in that time. The very successful developers and teams, who often speak at conferences and publish papers have adopted many of these practices. Serverless, containers, lots of tests allowing continuous deployment of new objects into complex environments that scale to levels many of us never thought possible. These are the very high performances talked about in the State of DevOps report every year. Read the rest of The Data Model Matters

Lots of people move to the cloud; it's common. In fact, it's very common to hear customers who are being asked to migrate their workloads to a cloud vendor for a variety of reasons. You might not agree, but often there is some reason to move to the cloud. Sometimes it's even moving from one cloud to another, just because one of the big three (AWS, Azure, GCP) seems more attractive this year than the one from last year. When you move, do you size your system for the peak? 80% of the peak? Perhaps there is another goal for which you design. Do you worry about ever being under-provisioned and letting customers have a slower system? Or do you ensure you never hit the peak, which increases costs? Read the rest of Over or Under Provisioned

One of the things I used to emphasize in talks about DevOps is that no modern software of any significance is built by one person. Everything takes a team, so the foundation of version control becomes extremely important. We need a way to coordinate work across multiple individuals and communicate what changes are being made. This requires a strong foundation, and that starts with version control. In 2026, that hasn't changed, but what has changed is the makeup of the team. No longer do I need a bunch of humans. In today's world, with extremely powerful AI LLMs, we can have a team of AI agents that write code, often at a pace far exceeding that of human teams. However, they still need to coordinate and communicate and ensure their changes mesh together.  Read the rest of The New Software Team

You still need DBAs (that know how to back up systems and test restores). If you think you don't, or if you manager does, then perhaps they ought to read this piece on how an AI agent deleted a production database. This wasn't the case of an agent just running around with sysadmin access to all resources, or a lack of tests that allowed bad code to flow through a CI/CD process. This was a system design that had a hole in it. An API call to change infrastructure that could change both staging and production. Not something an AI set up, but humans did. A hole from both PocketOS and the API vendor that allowed the AI agent to make the same type of mistake we've seen humans make. A mistake of not double checking, not verifying, not following the rules of getting a second set of eyes, even a second set of virtual eyes, on the code that could drop resources. Read the rest of Limit the Blast Radius

I wonder how many of you have tried vibe coding something with an AI tool. If you haven't, I certainly recommend it. I've been a bit amazed with a few of my AI Experiments, including my loading of a lot of inconsistently formatted data into a database for USD$5. To be clear, there's plenty of vibe coding that might not be production-ready, but have you ever been handed code from a human developer you didn't think was production-ready? Or deployed code like that? Certainly, AI could exacerbate the situation, but it can also spark ideas, ease (and speed) development in small ways, and tackle the backlog of things your org needs. Especially small tools. Read the rest of What Can AI Really Do?

I remember getting started on SQL Server and trying to upskill myself in the mid-1990s. At that time, my employer was running a SQL Server 4.2 instance for a third-party application, but we wanted to rewrite our internal bespoke sales app to run on SQL Server. We were upgrading from Foxpro to Visual Foxpro and looking to move from shared dbf files to a SQL Server. There was a new release of SQL Server 6.5 during our development, and I wanted to learn more about it. I purchased Inside SQL Server 6.5 and read the entire thing, getting prepared to finish development and then manage a new platform in production. I had updated copies of that book as SQL Server released new versions until SQL Server 2005. When that came out, there weren't one, but rather 4 books to cover the Inside SQL Server details (Programming, Query Tuning, T-SQL, and The Storage Engine). A similar thing happened with the SQL Server Bible, which grew in size to over 1400 pages for the 2012 version. It was a backache in a book if you put it in with your laptop. Read the rest of There's Too Much to Learn

Many of us working with databases know the problems of a single point of failure. We build HA/DR technologies into a lot of systems precisely because many of us know if the database goes down, a lot of stuff goes down. Broken software is easier to fix and rollback, but a broken database can be a much bigger problems. We also know an overloaded server doesn't handle a workload well, hence our quest for well-written SQL code, but we often lose that battle with developers. Read the rest of The Dangers of Dependencies

While talking to a customer a few weeks ago, they mentioned that they used Contained Availability Groups (CAG) everywhere. They also said they were amazing and wondered why everyone wasn't using them in other environments. Of course, I questioned the "everywhere", which turned out to be more of a default for new systems than a standard across all systems. That's likely true of most things since it's rare we get to update/patch/set something across an environment of any size and ensure every system is the same. Still, setting a CAG as a default makes some sense for enterprises. This ensures that in an HA situation I have my logins, jobs, etc. already on a secondary node. That's been one of the challenges of using lightly linked systems that only sync up database level information. Log shipping, Replication, Availability Groups can all work to keep a secondary ready to take over, but they all miss information that is stored in master or msdb. Read the rest of Who is Using CAGs?

While working with a customer recently, I heard this sentence: a tool is better than a script. The reference was that this customer preferred a known, tested, approved tool for most of their staff rather than a script built, lightly tested, and perhaps changeable by anyone in their organization. I was surprised, because in many ways, I've depended way more on scripts, more often, than "tools" in my career. Often I struggled to find tools that actually worked in the way I wanted them to and built them myself with Unix shell utilities, VB Script, PowerShell, or some combination of those or other technologies. Read the rest of A Tool is Better than a Script

The AI LLM boom seems to show no sign of slowing down. Each time I think we've reached some level of crazy use or predictions, things take another turn. I still find myself pinging back and forth between this will be amazingly good and horrifyingly bad. Sometimes on the same day. Read the rest of Half of All Engineers

Recently I saw an interesting article, saying that someone could build a general purpose coding agent in 131 lines of Python code. That's a neat idea, though I'm not sure that this is better than just using Claude Code, especially as the agent still uses the online version of  the Claude model from Anthropic to generate code or perform other tasks. There's a video in the article showing how this code can be used to perform some quick tasks on a computer. However, the code isn't specific to Anthropic. It can be used with any LLM, and I started doing just that, with a copy of the code from the article, but modified to use a local AI LLM running under Ollama. You can see my repo and feel free to download and play with it. It's expecting a local LLM on 11434. Read the rest of Local Agents

Every database platform has some strengths and weaknesses. Some more than others. I caught this site (NSFW) from Erik Darling, and it made my day. I was having a tough one when this site got me to smile and chuckle out loud a few times. I especially like the MySQL and SQL Lite links (again NSFW). Every platform that you might choose to use to back an application can work in many situations. Certainly scale and load are factors to consider, but for the major relational database platforms, most will work fine for many applications. Some might work better than others, but there are always tradeoffs. There are pros and cons. This is also true for the major NoSQL platforms, though most of my experience is with relational ones, so I tend to lean in that direction. At the same time, any platform can fail horribly. Read the rest of Every Database Has Problems

In the last year I've seen a lot of statements about data and sovereignty between countries. While there have been concerns in the past, there seems to be more worry around the world with AI services primarily being run by, and hosted by, US companies. Plenty of my customers at Redgate Software have concerns over our ability to see data when we run AI models, though we don't store the data. Once the session ends, the data is discarded by policy Recently I saw a piece about France trying to rid itself of the reliance on US technology, specifically the Windows OS from Microsoft. They are looking to move to their own version of Linux, as well as a number of open source software packages. This quote was fascinating to me: "We can no longer accept that our data, our infrastructure, and our strategic decisions depend on solutions whose rules, pricing, evolution, and risks we do not control." Read the rest of The New OS Wars

One of my colleagues wrote a great post about DBAs and developers, about how a DBA's pushback on bad code isn't to be difficult, it's because they can see the future. I never thought of myself as a modern-day Nostradamus, predicting the future of system performance. Apparently I had another title besides DBA. Working under pressure and with short deadlines often leads to short cuts. I've made them. I've implemented quick hot fixes. I've forgotten to port changes back to development databases. I've increased our tech debt load, just to solve a more immediate problem. Read the rest of Working Better Under Pressure

There was a post on X recently from a founder in the EU about an engineer using Claude and ChatGPT to build a feature. I am not sure how true these posts are or if they are designed to just create engagement, but it's still an interesting topic. The part that makes me think is that (supposedly) the engineer was fired because their "data" (code) was sent to American servers. The code was then deleted and the feature will be built without AI. First, read some of the responses before you form an opinion. There are some funny ones in there. There are a few I think are overblown and silly, and I skim past them. Someone is always more upset than I am, and more than I think they rationally should be, so I tend to let their outrage flow by me. Read the rest of Who is Irresponsible?

It's always interesting to me when I give product feedback to engineers at Redgate on their demos. Quite often they've built a feature that uses AdventureWorks or Pagila (PostgreSQL) or some other well known schema to evaluate how their particular thing works with a database. I try to remind them that many databases aren't well modeled and designed with consistent naming. I ran across a Daily WTF article that isn't showcasing databases, but it does show some poor naming in data being stored in a PDF. The developer who had to automate a process had to map these fields to database fields, which also might not be named very clearly. In fact, I think I've seen a few database models that used column names like the field names in the PDF. Read the rest of Poor Names

Recently, I saw a graph about making decisions that showed the impact of both reversibility and consequences. Here is an example of such a graph and how one might approach decisions. If things are easily reversible or have a low consequence, we tend to make a decision and move on. Or we are willing to make a decision. One of the examples of such a decision was choosing what to wear out to dinner. It's easy to change, and (in general) of little consequence. Choosing to send a large amount of money to someone through Venmo (or some other mechanism), can be hard to reverse and have substantial consequences. This made me think of some of the DBA and developer decisions I've made in the past. When we work with databases, the changes we make can have a large impact and be quite consequential to our organization. Downtime, data quality, etc. could all impact revenue, profit, reputation, or even future prospects of survival. That can be a lot of pressure when you are deciding to refactor a data model or adjust a lot of data during a deployment. Read the rest of Acting with Confidence

Years ago I was giving a talk on software development and asked the audience how long it takes to review a PR that has 10 lines changed. Answers were in the minutes to tens of minutes range. I then asked how long it takes to review a PR that has 1,000 lines changed. Some people said hours, but a few people said seconds. I've often taken the latter, pessimistic view. Not because I don't think engineers want to do a good job, but because I know human behavior. Most humans will get bored, lose focus, and end up skimming through a large amount of code. Many (most?) people don't want to spend all that time, after all they have they their own code to write. They'll just approve the PR and assume testing will catch any major issues. Read the rest of Barely Reviewed Code

SQL Server Central has been a great success over the last 25 years. We've helped a lot of people improve their careers with the Microsoft Data Platform, primarily SQL Server, but we've published articles on other aspects of databases, including other platforms. I wrote a bit about the history of the site last month, with a few stories in various pieces. We even got Brian Knight to contribute a piece on what the site meant to him. Over the years, we experimented with trying to get an SSIS Central or a SSRS Central off the ground. However, we struggled to find other people who would have been willing to partner with us to provide content and answer questions. Eventually, we gave up, though I wish today we'd have pushed forward with a PostgreSQL Central site a few years back. Read the rest of AI Database Central

One of the challenges of AI-assisted coding agents is that they tend to produce A LOT of code. Even in refactoring or migration changes, the AIs can work quickly and generate such a volume of code that the process starts to become overwhelming. For pull requests, for CI/CD build systems, and certainly for human reviewers, they can be overwhelmed. This can become a real problem with OSS projects, where submissions can grow exponentially to the point that maintainers stop looking at pull requests. I suspect the same thing might happen in corporate repositories when lots of developers can refactor or submit huge amounts of code produced by AI agents in a fraction of the time it took a year ago. I was listening to an interview with an experienced software developer and OSS project maintainer who said that he preferred getting a "prompt request" that contained a description of a problem and the specification for a solution that he could submit to his own LLM to get the code. Rather than use an AI to review a code in a PR written by a human or AI agent, a great prompt that can communicates the problem and solution is preferred. Read the rest of Prompt Requests

We do a lot of research at Redgate Software, often contacting customers or Ambassadors and asking questions, getting feedback, listening to their challenges or criticisms. We take that information and it helps guide us to build the tools that help you in your job. Recently I watched a call with a customer that uses our famous Toolbelt in their job and has for years. In this case, the call was about the value of Flyway and how that might fit in their organization. The person performed a lot of manual work to deploy code changes, and could see the way in which Flyway helps, but wasn't interested in saving time. They saw their time as free. I assume their employer felt that way as well. Read the rest of Is Your Time "Free"?