As an old Delphi guy, I remember well the “language wars” we had with the Visual Basic guys. An early codename for Delphi was “VBK” — VB Killer — and the VB community took exception. They’d come to our Delphi forums and pick fights. Naturally, we brash Delphi guys would fight back, engaging in big flame wars and getting all worked up over what wasn’t much more than a personal preference. Good times.
These days, we’ve moved the discussion up a layer — what is the better model for coding? Things aren’t quite as intense as the VB/Delphi dustups, but people have their opinions. Companies are taking a look at different models before choosing one for their teams. Most teams have arrived at a family of models that they use.
At some point, chatting with Claude or Codex started to seem a bit raw. It wasn’t long before scaffolding tools like GStack and Superpowers were adding underpinnings for interacting with LLMs — baseline instructions for handling prompts before they get to the model itself
As an old Delphi guy, I remember well the “language wars” we had with the Visual Basic guys. An early codename for Delphi was “VBK” — VB Killer — and the VB community took exception. They’d come to our Delphi forums and pick fights. Naturally, we brash Delphi guys would fight back, engaging in big flame wars and getting all worked up over what wasn’t much more than a personal preference. Good times.
These days, we’ve moved the discussion up a layer — what is the better model for coding? Things aren’t quite as intense as the VB/Delphi dustups, but people have their opinions. Companies are taking a look at different models before choosing one for their teams. Most teams have arrived at a family of models that they use.
At some point, chatting with Claude or Codex started to seem a bit raw. It wasn’t long before scaffolding tools like GStack and Superpowers were adding underpinnings for interacting with LLMs — baseline instructions for handling prompts before they get to the model itself
As an old Delphi guy, I remember well the “language wars” we had with the Visual Basic guys. An early codename for Delphi was “VBK” — VB Killer — and the VB community took exception. They’d come to our Delphi forums and pick fights. Naturally, we brash Delphi guys would fight back, engaging in big flame wars and getting all worked up over what wasn’t much more than a personal preference. Good times.
These days, we’ve moved the discussion up a layer — what is the better model for coding? Things aren’t quite as intense as the VB/Delphi dustups, but people have their opinions. Companies are taking a look at different models before choosing one for their teams. Most teams have arrived at a family of models that they use.
At some point, chatting with Claude or Codex started to seem a bit raw. It wasn’t long before scaffolding tools like GStack and Superpowers were adding underpinnings for interacting with LLMs — baseline instructions for handling prompts before they get to the model itself
OpenAI has introduced spend controls and enhanced usage analytics for ChatGPT Enterprise to enable organizations to monitor AI adoption, track consumption across teams, and set budgets for AI usage. But, analysts cautioned, it still can’t show how those costs lead to business benefits.
The new features provide administrators with centralized dashboards showing how ChatGPT is being used across an organization, enabling them to understand adoption patterns, and manage AI costs by setting budgets and tracking spending.
“The Global Admin Console brings ChatGPT and Codex credit usage into one view, so admins can see a more granular breakdown of credit consumption across users, products, and models — helping them understand where spend is coming from and how it maps to actual credit usage,” OpenAI said.
A shift toward AI cost governance
The introduction of budgeting and usage analytics reflects a broader change in enterprise priorities, according to Biswajeet Mahapatra, principal analyst at
For years now, Microsoft has been doing its level best to move you from desktop Office and Windows to Microsoft 365, Windows 365, and Azure Virtual Desktop (AVD). Since the company first started down this road, however, something changed: the AI revolution, which has become a huge deal for the guys from Redmond.
So, it should come as no surprise that the company is now combining its efforts to push cloud-based PCs and get as many users working with its AI services as possible.
First, Microsoft has reduced pricing for Windows 365 and AVD in select configurations by 20%. In particular, the company is slashing prices for persistent desktop deployments and lower-tier virtual machines (VMs). These are the instances commonly used by task workers and call centers, not by developers or white-collar office worker bees.
Microsoft is also expanding bundled discounts tied to existing enterprise agreements and Microsoft 365 subscriptions. This cuts the per-user cost for organizations already inve
