We are not talking just chatbots - albeit more intelligent ones!

An AI agent/assistant can be tasked to do specific things to reach a goal and work with other agents, either in parallel, or sequential (i.e. do all these things first, then does this).

The cool thing is each AI agent can use a completely different model i.e. you don’t have to tie everything into just chatGPT/Open AI. You might find a different model or model sets beneficial for certain things.

Also, the big component is a mix of RAG (retrieval augmented generation), goal setting and external “tools” or functions where you can call out to external systems.

I will be creating a video (Just Fifteen Mins! as if I ever stick to any timeline!) to explain a few of these concepts in more details. I am also going to be creating a workshop course too! not overly technical, but mostly from a business perspective about the concepts and how they could benefit companies. Again, we are not talking just fancy chatbots!

Until next time, take care everyone!

Please consider subscribing too! It’s okay, you don’t have to pay - unless you want to of course! :) If you do pay for a subscription, you will get a free weekly update from the chief unicorn - Ulysses :)

Well, for the time being, I am sticking with OneNote as I have so much in there!

However, the way Obsidian Notes is moving, is looking tempting. Of course, the notes/data stay on your device which is a plus however, for convenience, you will most likely need the data synchronised to your other devices. It is possible of course!

Also, AI is ever creeping in to everything in modern life - love it or hate it.

Obsidian

Obsidian Sync

Obsistants for Obsidian

Until next time, take care!

Okay, two suggestions for the price of one!

Both from my good friend Tim Abel who also has a podcast if you wish to take a listen.

In fairness, the first GitHub Action thing, I have little idea of what/how this is used and even when I looked at the use case, I was still a little baffled! I guess you need to be “an actual developer” to appreciate this! :)

On to the second suggestion, Playwright for browser web app testing. I get this and it is nice to remember that you don’t need to code lots of things like good old selenium. You can test your web app as a user would use your application. It has some wide support for different languages and seems to be easy enough to get started.

Thanks again Tim!

VMWare “Player” was always free, but the workstation (or Mac Fusion Pro) used to cost real money (not Unicorn dollars).

No you can create VM’s on your laptop/Mac for freeeeeeee

Here is the post for VMWare

“And now for something completely different”, as Monty Python once said:

VS Code Profiles! yes, if you are like me and have far too many extensions in VS Code, maybe use profiles to split up the different categories of development! with different themes too!

Why? oh why?

That is all…

Okay, free for as long as you have an Azure subscription ;)

Still, who doesn’t want a 32gb cloud-based Azure SQL database to play with?

Check out the details here

Of course you can then use something like Azure Data Studio to work with the database - again for free! it even has a free version of Copilot for Azure Data Studio so you can look like a SQL pro! (I did say “look like” ;) )

Hey and what the heck, why not throw a REST or GraphQL API at the database too - for free! using Data API Builder.

I will be showing some of the above in action via a new-fangled device called a “video” - apparently all the kids these days are doing this…

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I remember the days when we had to create Docker containers to deploy our apps…

Well, you still can use Docker - more on that later.

Fermyon Spin (and so much more) is a framework to build WASM (Web Assembly) apps. I covered a little of this back in Episode 65 and an intro to Fermyon a while back.

This episode was prompted by my good friend Tim Abel who also has a podcast called Software Should Be Free (check it out, some good insights here).

Quite a bit to get into in this episode - hence it ran over to 10 mins! which reminds me, I really should delve a little deeper into some of these articles and produce a video on my “Just 15 mins” YouTube channel… BTW, it is just full of tumbleweeds right now ;)

Anyway, Docker desktop also has beta support for running WASM modules too! Again, will get more details together and perhaps a video for that one!

Dotnet is not forgotten either! since dotnet 8, experimental WASM/WASI features have been thrown in.

Take a listen for more info

Memory-Optimized Tables, also known as In-Memory OLTP, were introduced in SQL Server 2014. This feature was further enhanced in subsequent versions of SQL Server, including SQL Server 2016, 2017, and in Azure. However, in Azure, they're only available in the Premium tier.

Memory-Optimized Tables in SQL Server are a feature that provides significant performance improvements by storing table data in memory and optimizing data access. Here's an overview:

* What are Memory-Optimized Tables? Memory-Optimized Tables are tables that have their data completely held in memory, eliminating disk access except for durability purposes. This allows SQL Server to redesign how data access is handled, including locking and latching, resulting in substantially improved performance.

* How do they work? Memory-Optimized Tables store their data in memory using multiple versions of each row’s data. This technique, known as "Non-blocking multi-version optimistic concurrency control", eliminates both Locks and Latches, thus achieving breakthrough performance. All row versions are maintained in the same table data structure. Row versioning is used to allow concurrent reads and writes on the same row.

* Durability of Data: Memory-Optimized Tables are fully durable by default, meaning that like transactions on (traditional) disk-based tables, transactions on memory-optimized tables are fully atomic, consistent, isolated, and durable (ACID). A second copy of the table data is maintained on disk, but only for durability purposes. Data in memory-optimized tables is only read from disk during database recovery (e.g., after a server restart).

* Non-Durable Tables: Besides the default durable memory-optimized tables, SQL Server also supports non-durable memory-optimized tables, which are not logged and their data is not persisted on disk. This means that transactions on these tables do not require any disk IO, but the data will not be recovered if there is a server crash or failover.

* Limitations: Memory-optimized tables and natively compiled stored procedures support only a subset of Transact-SQL features. Starting with SQL Server 2016, and in Azure SQL Database, there are no limitations for collations or code pages that are specific to In-Memory OLTP.