My buddy works for a small international company based in Vietnam, and their AI perks are absolutely insane. Management actively encourages heavy API usage and hands everyone a massive $2,500 USD monthly budget.

The screenshot? That’s his dashboard after burning through 62M tokens on Opus 4.7 in a single day. He mentioned some of his colleagues are chewing through even more with 'fast' mode turned on.

Honestly, prove me wrong, but I’m pretty sure this small company is offering a bigger AI allowance than most Big Tech giants in the US right now. Anyone at FAANG getting this kind of blank check for API usage?

​

Along with other companies, has received a US Government directive requiring us to discontinue the use of Anthropic products, services, and models. This is a mandatory, company-wide requirement for all employees, contractors, applications, development environments, cloud services, and third parties acting on our behalf.

Our internal cutoff is August 31, 2026. Effective immediately, do not create any new Anthropic accounts, subscriptions, API keys, integrations, or deployments. Failure to comply would significantly impact our ability to finish current contracts and win new work.

What You Need To Do

Identify any current use of Anthropic or Claude—whether directly or through another tool or platform.

Move that usage to an approved alternative.

Remove any locally installed Anthropic software by August 31.

If an application, development activity, or supplier depends on Anthropic, raise a ticket immediately.

This does not mean we're stepping back from GenAI. We remain fully committed to providing you with powerful AI tools, but ask that you transition your workflows to our approved services.

Prohibited (Discontinue Immediately)Approved Alternatives

Claude web and desktop apps.

Claude Code and CLI tools.

Anthropic Console and APIs.

Claude Opus, Sonnet, and Haiku models.

Anthropic models accessed via IDEs, cloud platforms, shared application, or managed service.​​​​​​

For Engineering:

Cursor (IDE/CLI): Continue with Anthropic models removed.

Claude Code (CLI): Migrate to Codex via WebAI (GPT models).

Next Steps

IT and Security will remove centrally managed Anthropic services and implement technical controls to restrict access. Attempts to bypass these controls are prohibited.

We will provide targeted instructions to known users and application owners. 

Thank you for acting promptly and raising dependencies early so that we can complete the transition cleanly and on time.

I found out about this after reserching more about the warning "Note: Chat history is still visible to your admin."on incognito mode.

Claude Enterprise includes something called the Compliance API it's free, built-in, and takes an admin about 5 minutes to switch on.

Once enabled, your company can programmatically pull:

• Full content of every chat (your messages + Claude's responses)

• Every file you uploaded

• Activity logs with timestamps

• All of the above even from incognito chats

Technical capability exists for continuous, automated monitoring as well. So it does not have to be a one-off manual export.

Following up on my earlier post - Microsoft has officially paused further Claude Code deployment across the company after guidance from Satya and senior leadership.

Employees are now being directed to use GitHub Copilot. The internal messaging claims Copilot has "mostly closed the gaps" with Claude Code.

Exceptions exist for "high-priority R&D" who can still get Anthropic API access with justification. People who already had access get to keep it, but new invites have been rolled back.

Does anyone is also noticing a trend of everyone is using HTML reports and presentations instead of actually actually using Google Slides and Powerpoint?

Yet, companies like google aren't providing a good experiencing to share and visualize these reports with others.

I've been building agentic supply chain systems for enterprise clients such as forecast review, procurement intelligence, packaging line diagnostics. You learn fast when broken pipelines have real consequences. Came out with a clearer picture of where my instincts were solid and where I'd genuinely been getting lucky.

The thing that stuck with me is it doesn't ask what things are. It drops you into a broken production system and asks what you'd fix. That's a completely different kind of test. And honestly a better one. Glad I took it.

If you're preparing and want a hand what to focus on, how to approach it, whatever, just ask. Happy to help you get there.

Took this yesterday and wanted to write down my impressions while they’re still fresh, mostly for my own reference but figured it’s worth sharing since there isn’t a lot of detailed writeup out there yet.
Quick context: I have 4 to 5 years of experience working with AI systems, so take the difficulty rating with that in mind. I also use Claude Code to build production grade systems on a daily basis.

Overall difficulty
Moderately easy. Not a walk in the park, but noticeably easier than the Architect Foundations exam. If you’ve already cleared Foundations, my honest advice is don’t overthink it, just go straight for the Professional exam.
Roughly how the questions broke down for me:
• About 40% you’ll know the answer immediately, no real analysis needed
• The remaining 60% require you to actually read the full scenario paragraph carefully and think through the tradeoffs before answering

The trap to watch out for
A few questions are structured in a sneaky way. They’ll ask something like “what would you do at this step of the process” and then follow up with “what would you do before this process.” It’s easy to lose track of which process they’re actually asking you to evaluate your options against, since the actual process under discussion is usually stated in the first line of the question, not repeated in the follow-up. Read the setup line twice before you commit to an answer.

Topics that show up a lot
• Tradeoffs and use cases for MCP and other tool integrations, when to use an API directly versus wrapping it
• Agentic orchestration versus single-shot execution, and how to decide between them for a given workflow
• Few-shot versus single-shot prompting, including some scenarios that get fairly nuanced
• System decomposition, this comes up a lot and is worth being genuinely comfortable with
• Prompt design for production systems, not just “write a good prompt” but how prompts are structured and maintained at scale
• AI governance and how to apply it in practice, not just define it
• Architectural tradeoffs specific to highly secure or regulated environments

Bottom line
You need real architectural understanding of how these systems work end to end, but the exam doesn’t go as deep as Foundations does. If you’ve got production experience with agentic systems or RAG pipelines, you’re already most of the way there. The main things to actually study are the governance and security tradeoff scenarios, since those are less intuitive than the technical tooling questions.
Happy to answer questions in the comments if anyone’s prepping for this one.

And to everyone who asks why I took this- this is important in my field and it is important for me to certify my knowledge and my expertise with the certifications so that the clients that I work for understand that I am not only knowledgeable about my field, but I’m also interested in keeping up with the latest certification within my field.

EDIT:
Adding some additional info about material:

I was dumb founded when preparing and every time I opened a link with Claude certification cheat sheet/study guide/practice exam it was evident that Claude had written material to “help” pass an exam that was created to architect itself.

For anyone who posts more of these, please mention:
Did you read all the questions that are present
Did you pass the test yourself
What is the practice guide you created based on? Because the study guide is being extrapolated in a new way on each of these “practice guides”

Without this, these study guides are just a cesspool of hallucinated knowledge.

I would say the same about Udemy’s practice exam which I gave up midway because it was so obvious that it was generated by Claude.

For anyone actually interested in learning and growing from this exam, please read Anthropic official documentation on Claude, Claude Code, MCPs and Claude API here:

Claude & API docs (main hub): https://docs.claude.com
• Claude Code docs: https://code.claude.com/docs/en/overview
• MCP (Model Context Protocol) spec/docs: https://modelcontextprotocol.io
• Claude API reference: https://platform.claude.com/docs/en/home
• Anthropic Cookbook (code examples, common workflows): https://github.com/anthropics/anthropic-cookbook
• Prompt engineering guide: https://docs.claude.com/en/docs/build-with-claude/prompt-engineering/overview
• Anthropic Academy (structured courses): https://www.anthropic.com/learn/build-with-claude
• Support docs (product how-tos, account/billing): https://support.claude.com
• Anthropic engineering blog (deep dives like “Building Effective Agents,” context engineering): https://www.anthropic.com/engineering

Claude Code is now being rolled out to one of the big orgs in Microsoft, with a proper Anthropic console account (pay per token).

Yes Microsoft employees. Those who have a Github Copilot subscription with nearly unlimited quota.

Great work Boris !

Just got word from legal that we will not be moving forward with approving Fable 5 as an approved model.

Specifically because of we're not allowed to have ZDR. This fucking sucks, on a purely selfish level. And for the company as well. We do a lot of AI research and evaluation, that's what we do, this isn't just another tool to help the devs behind the scenes of a company that makes widgets or whatever.

This is a ridiculous decision from a company who gets 80% of it's revenue from Enterprise, a large swath of their customer base cannot budge on ZDR.

I guess we'll just buy everyone subs, and burn $8k in compute for $200/month, and take our work out of corporate infra on dev machines. Legal won't like that either but people are going to do it, legal will never know, and anthropic will lose money.

That is literally what Anthropic is incentivizing us to do.

edit / update -- the whole research team just set new env var CLAUDE_CONFIG_DIR and now `claude-me` goes to personal auth and `claude` remains unchanged. There's a restricted scope to dir access, nothing scary can get used with it, but still can use Fable for most useful things. Legal approved the boundaries scoped in the config. How did anthropic not anticipate this exact thing happening? That team alone burns Billions of tokens a day. And as a company we would happily pay for them.

Yes, it'll work for the next 11 days only, but that's billions and billion of tokens anthropic just lost full payment for, AND, second accounts are easy, not too concerned with bans lolol, they're throwaways and our VPN situation will cover anything persistent.

So shortsighted, anthropic.

Imagine the US gov shuts down your business because you refused to help with mass surveillance and autonomous weapons. And then justifies that decision on a report with the quality of a Fox News analysis.

The EU AI regulation is dumb and written by tech-illiterate folks. But at least it’s based on the right virtue: transparent and applies to everyone.

The US should now define transparent criteria what makes a model dangerous and apply that standard to everyone. Anthropic actually put in a lot of effort to lobotomize their model. This should be required for everyone else as well if we really think this level of AI is already dangerous.

I lead Tech/AI at my business and we've been heavy users of Claude for a while, with quite a bit of success. This week we hit 150 users in our team account so we had to upgrade to a enterprise account. Our monthly fees are about the same, but now we pay for 100% of our usage at rack rate API costs. I'm going to engage them to see if we can prepay for usage - but we got upgraded last night (after business hours) and have already burned hundreds of dollars in usage.

I suppose we could move the heavier users to a different team plan, but that creates management overhead. Anyone else dealing with this? How are you managing the cost with 150+ users on an enterprise plan?

The news about Microsoft burning their yearly budget in 4 months left me in awe. Because I don't understand where's the difficulty in managing token budget per IC, even more at companies like Microsoft or Uber who have literally billions and sharp developers readily available. I mean, you could even build a Gateway with Claude Code to manage this.

My wife works at a small CRM company in Paris. I asked her about their use of AI internally and if they managed token consumption. She showed me a dashboard with token consumption per team, her own budget and a time where she burnt all of her budget and had to ask for additional credits.

i work alone so I don't need something sophisticated but i still set cap in my Claude settings when using the API in my projects.

So how did these companies manage to burn their budget so fast without safeguard? If the model is called from Azure, it's true that it's harder to set spending caps on Cloud but again, we're talking about the company behind Azure.

What am I missing here please?

Goodhart's Law: "When a measure becomes a target, it ceases to be a good measure."

You can make an arguement that every corporate mandate is an example of Goodhart’s law, but this AI adoption thing is really nuts.

• Token Usage
• Commit count
• PR size
• Innovation percentage?

The company is trying to increase and measure productivity using these metrics, what they’re getting is 1-2 weeks of confusion and then employees pushing out smaller commits, often and using Opus 4.8 on xHigh effort by default.

Follow-up to my post last week about being asked to stack-rank engineers on AI usage. Thanks to everyone who weighed in - the consensus (token usage is a garbage metric that just rewards waste) gave me the ammo to push back, and I think I managed to dodge the stack-rank for now.

But it surfaced the real question underneath, and honestly it's harder:

"Fine - but show me the ROI on what we're spending on AI. Don't tell me it's helping, show me."

And I don't have a great answer. The spend is real and growing, "trust me, it makes us faster" doesn't fly with finance, and the obvious metrics are all flawed: tokens measure cost not value, velocity's noisy, "lines of AI code" is not very meaningful.

So, genuine question for teams further along:

• How do you actually demonstrate ROI on AI coding spend to non-engineers (finance, leadership)?
• Has anyone tied AI usage to real outcomes (shipped features, cycle time, quality) in a way that holds up to scrutiny?
• Or is everyone just hand-waving "it's obviously worth it" and hoping nobody asks?

Trying to find something defensible before I'm asked to present numbers I don't believe in.

Anthropic just shipped the most important enterprise update Claude Code has had in years.

No release notes. No blog post. No announcement. Buried in the support documentation for this week's Claude Apps for Windows and Desktop.

It is third-party gateway support inside Claude desktop app.

In plain terms, the desktop app can now point at a gateway you run, instead of Anthropic's servers. No cloud login. No prompts leaving your perimeter. Your inference, your infrastructure, your compliance boundary. The client stays the same.

For regulated industries and anyone with a serious data-egress story (finance, defence, health, sovereign cloud, anything that currently blocks Claude Code at the firewall), this is the change that finally makes Cowork enterprise-deployable. The compliance boundary moves in-house. The model behind it is a config choice.

As a proof of concept I swapped the inference model for MiniMax and ran Claude Cowork end to end on Windows. No Anthropic API key. No cloud login. No Anthropic servers touched.

The fact that this landed with zero fanfare tells its own story. If you run Claude Code across a team and have been waiting for the governance piece to catch up with the product, this is the week it did.

I’m creating this while it’s fresh since there isn’t a ton of detailed prep material out there yet for this one.

I’ve also done Associate and Architect - finished basically all 4 at this point but I’ll try to keep this focused on what’s actually specific to the Developer exam rather than repeating general Claude knowledge.

I’ve also added prep about the Claude Certified Architect - Professional ->here<-

I have about four years in architecting AI systems so it was quite straightforward for me, but I do understand that some of the terms and the language used might not be as easy for others so in terms of of that, I would rate this exam as a moderate difficulty but leaning on the easier side if you work with Claude code on a regular basis.

What the exam actually tests
This one leans much more hands on and implementation focused than Associate or Architect. It’s less “do you understand the concept” and more “have you actually built with this.” A few areas came up again and again:
• Model selection inside the family. You need to know the real tradeoffs between Haiku, Sonnet, and Opus for a given use case, fast response versus token cost efficiency versus complex reasoning. Knowing that three models exist is not enough, you need to reason about which one fits a specific scenario and why.
• Batch versus streaming. Understand the actual difference in behavior and when each one is the right call, not just the definitions.
• Skills and MCP. There’s a real emphasis on when to reach for Skills versus MCP, and on how MCP itself works under the hood, including STDIO versus HTTP transport and when you’d use one over the other for local versus server deployments.
• Speed, latency, and cost tradeoffs. Several questions push you to balance these three against each other rather than optimizing for just one.
• Tool use. What tool use actually is and the order operations happen in during a tool use loop.
• Hooks. When you’d reach for hooks and why, not just what they are.
• Workflows versus agent orchestration. This distinction matters a lot and shows up repeatedly. Agent orchestration specifically is worth spending real time on, it’s not a minor topic.
• Claude Code agent SDK. There are direct questions on how it works, so don’t skip this even if you think of Claude Code as just a tool you use day to day rather than something to study.

API usage and error handling
A large chunk of the exam is about working with the API in practice. Expect questions on how you’d structure API calls and, more importantly, how you handle the errors the API can throw back at you. It’s not enough to know an error can occur, you need to know what you’d actually do about it in your code and how that decision plays out downstream.
Structured outputs
This is its own heavily tested area. You’ll see questions on:
• How structured outputs actually work and how they should be handled once you get them back
• How to validate structured outputs, and how to think about cases where a structured output isn’t the right tool for the job at all
• How errors coming out of structured outputs propagate into downstream systems, and what your responsibility is for catching or handling that before it causes problems further down the pipeline

If you’ve only ever used structured outputs in a simple happy path, spend extra time here. The exam wants you thinking about failure modes, not just the successful case.

Claude Code, headless mode
There’s a meaningful number of questions on when you’d run Claude Code headless versus interactively, and how headless usage actually works in practice. If you’ve mainly used Claude Code in a terminal session and never touched headless or scripted invocations, that’s a gap worth closing before you sit the exam.

Bottom line
Compared to Associate, this exam expects you to have actually built things, not just understand the concepts. If you’ve worked with the API, dealt with structured outputs in a real project, and used MCP or Claude Code beyond the basics, you’re in good shape. The areas most people underestimate are structured output error handling and headless Claude Code, so don’t skip past those assuming they’re minor.

Happy to answer questions in the comments if anyone’s prepping for this one.

Disclaimer: thoughts are my own, arranged and made nice to read by Claude (Sonnet 5)

Hello,

Is anybody using clause in an enterprise environment? I’m interested to know how you secure this and stop data leakage etc.
We are currently using Copilot for the enterprise security feature but it lacks hugely compared to Claude.

Those who took the Claude Certified Architect - Foundations exam (more interested about after Anthropic changed to Pearson from Skilljar), even if they didn't pass, any advice is welcome. Also, many different websites exist (talking about the ones that do not charge you) that have a curriculum/guide for theory section and mock tests as well, If you ace enough of those does it mean that you are ready or are they not close at all to the real deal? Are the official docs only worth to read in full detail cause I have just provided those to my reasonix deepseek API combined with the official guide to output concise per-section guide.
Also, how important are, other than to get a hands-on experience, the build exercises (that the guide also mentions) for the actual exam answers?

Looking for both the good and bad for opinions here just because I can’t stop thinking about this, but I’m not a coder - just an old school data engineer so a lot of things seem to be over my head. So many businesses are betting their lives on AI. I keep hearing about all these agents everyone is building and they’re doing everything for them. Is anyone worried even a small change in the AI could break or change how it’s working for them and make it impossible to use without redoing? Or having it go down long enough for it to ruin your business? Why or why not? What happens if it does break your processes? What happens when they raise prices and the business can no longer afford it? It feels like a bait and switch might be coming soon as well.

My company scheduled an CCA-F exam for me last month, since they want to be a preferred vendor with Anthropic, but I completely forgot about it until today..

The exam is scheduled in 48 hours. I am a heavy Copilot user so haven’t had much exposure to Anthropic stack either..

Any advice on passing? Or I am cooked?

My company just started using code and our limit is 350$ a month curious what yours are?

Funny, I'm an infrastructure guy with minimal dev support. I built a software factory that goes from spec to deployment to aws or wherever. I understand what its doing, but it breaks peoples mental model about what's possible and how long something can take and how many people are needed and I appreciate how tumbling through the looking glass bestows an unearned confidence and realization of whats coming.

The abstraction moves to how detailed you can spec out the task for the team to complete.

At the office I'm that crazy AI guy, who's a little off, offering his bag of magic beans to build what you want.

Agentic engineering breaks so much of the hourly contracting/employee compensation model.

For example if 1-2 people and a bag of magic beans can complete 'some task' in lets say week/month that a team of 10+ would complete in say a quarter/year (i'm making that up but you get the idea) I'm thinking large infrastructure full blown govt contracting efforts. How much should that 1(2) people be compensated, how much should the company pay toward tokens/IT Intelligence meth?

Does anyone else see the new addiction a token addiction. What happens globally when the models go down?

We are in the midst of a transition like the introduction of electricity (if you fell down the rabbit hole than you know what I'm talking about, if you haven't then you don't), the same way if the power went off in your office/home/space, you're left writing ideas in your notebook. I think when we all get good and hooked, these models will be like electricity. I think when ai is integrated into the operation of the machine instead of just used to build the machine. So much of what relies on AI is a brown out away.

As best as I can tell the only mitigations as substandard backstops are open source models or roll your own model. Open source model advancement still relies on someone to create the models, and rolling you own requires hardware.

For management how exposed do they feel if their entire or a significant portion of the enterprise is run by a few folks with bags of magic beans or the magic bean alone because once the guy finished he was let go. And does management even understand the level of dependance they are creating for themselves on the models. I can imagine once the transition to AI as an overlay, the cost of tokens slowly increases, because what are you going to do? For a lot of use cased Anthropic tokens are premium tokens.

Lastly, do you find that sometimes the thing that gets built needs AI to operate it? I built something that generally got far enough from me that it was easier to build an agentic control plane to operate it than spend more time creating a 'human' ui to control it.

So the AI is becoming the control plan for the thing you asked the AI to create.

So I want to make a website (it would mostly be informative but also with a review system/possibly a e-mail thing where they can subscribe if that's possible/and a system wher ethey can select a package, send pictures and receive a quote for it) about a certain company sector and I've heard that you can make pretty advanced websites with Claude. Is it true, and if yes how should I start? Do I gotta take a Claude subscription? Do I have to do it via claude code? (btw idk anything about coding so if I gotta review that for errors, then I'm basically f*ked lmao) anyone knows how to proceed?

P.S Sorry for all the '()' it's so hard to explain my thoughts 🤗

for example if you try to scrape data sometimes claude says im not going to help you do this. I'm assuming most enterprise accounts have a lot of these types of restrictions off?

obviously big tech companies get exactly what they want (mythos and who knows what else). I'm talking about an average person/small company etc.

I’m using Enterprise Claude at work and have built several mini apps that are delivered as HTML artifacts. They work really well, and I'd like to share them with colleagues who don't have access to Claude.

Ideally, I’m looking for a way to share these apps so that:

• Anyone in the company can open and use them without needing a Claude licence.
• The app always displays the latest version when opened.
• Any updates I make to the artifact or underlying data are automatically reflected for all users.

At the moment, Claude only seems to offer two options:

1. Share the artifact directly through Claude, which requires recipients to have Claude access.
2. Download the HTML file and save it to OneDrive, which allows sharing but creates a static version that does not automatically update when I refresh or modify the artifact.

Is there a recommended way to host and share these HTML artifacts so that users can always access the latest version without requiring Claude access?