Inaros

Preparation. Discipline. Patience. Decisiveness. 🏴

[Inaros @Inaros_SF]

2025…

Dedication. Discipline. Determination.

[Taelin @VictorTaelin]

this is my personal singularity moment

this post may sound like a paid ad. I only wish. I'm concerned, more so than happy. the world is changing, and, among the scenarios where AI goes terribly wrong, inequality is the most realistic, yet, the one Anthropic seems to be the least concerned about. I'm glad OpenAI is taking the opposite stance: *personal AGI for everyone*. I think this is a commendable position in the times we live. but who am I in the queue of the bread?

anyway, Fable is here, so I'll just report my first-hour experience

first of all, all my pet prompts are solved.
→ λ-calculus puzzles
→ bug questions
→ one-shot apps
all are trivial to it.

I don't have anything harder other than my
ongoing work

so, in the last several days, I've been toying with HVM5, a new interaction net evaluator with a faster loop.

after writing the first version, I left 32 GPT-5 agents working for ~20 hours each. this resulted in up to 2x speedups, but the file size increased by 2-fold and quality decreased significantly.

I then simplified the whole thing into an even simpler core, and left Opus 4.8 and GPT 5.5 optimizing it for 8 hours. Opus got a legit 6% - 34% speedup in most benches. GPT got better results, but, sadly, an unusable file.

I then asked Fable to optimize it.

2 hours later, it landed a 1770% speedup in one case, 100%+ in other 4, and 22% in average. yes, in 2 hours it outperformed me, opus 4.8 and a swarm of gpt 5.5 agents, by one order of magnitude.

that could not possibly be legit. "it must be hardcoding the benchmarks" (GPT trauma). so I read its explanation and what it did was, indeed, the most high impact optimization one could try first. seems like HVM5 was wasting a lot of time garbage-collecting unused branches of pattern-match nodes. I had optimized that for static mats, but not for dynamic mats. skill issue. Fable figured how to do it for these, resulting in a massive speedup in some benches

but wait, is that *correct*? I'm not sure yet, it is credible, but this is the kind of thing that is very easy to get wrong on interaction nets. the problem is, when I was ready to start auditing Fable's solution so I could tell whether it was buggy or legit, it interrupted me to tell me it had found a massive bug on the code *I* had written.

... wait, what?

so... for garbage collection purposes, I stored a bit on lambda term pointers that meant "the variable bound by this lambda has been freed, so, its lambda must free whatever argument it is applied to". that's fine. yet, on duplicator nodes, I also used the same bit to mean "one of the duplicated variables was freed, so, treat this dup as a passthrough no-op". so, if a lambda entered a duplicator, it would mistake the lambda's collection bit for its own, resulting in corrupted interaction!

that's a mouthful, why I'm writing this?

just so you can appreciate the sheer absurdity of what just happened. I didn't ask it to find bugs. I asked it for an optimization. and even if I did ask it to find bugs, this bug is so astonishingly subtle and specific, identifying it takes mastering the domain to an extent that it beyond even me. I'd easily need hours or days to fix it, *if* I ever came across it. chances are it would just go unnoticed. and Fable found it and fixed it like it was nothing, while it was busy adding a 17x speedup to a file that neither I, nor Opus 4.8, nor a fleet of GPT 5.5 managed to barely make 2x faster.

oh and there is also another tab where it is also ripping through Bend's codebase and finishing everything I had to do

I don't know what to say anymore

this isn't about Anthropic or OpenAI, this is about our collective future as a species. the world is changing, and we need to be aware of it, and discuss how to handle this change.

receipt below . . .

[Rush @exRAF_Al]

The same Lewis Hamilton who used a corporate leasing structure to save money on taxes (around £3.3 million in VAT) when acquiring his Bombardier Challenger 605 private jet in 2013? The same Lewis Hamilton who bought the £16.5 million jet through his British Virgin Islands company (Stealth Aviation Ltd) and who then set up an Isle of Man leasing company (Stealth (IOM) Ltd, to import it into the EU and sub-leased it to a UK jet management firm (TAG Aviation), which in turn provided it back to Hamilton and his Guernsey company under charter agreements? *That* Lewis Hamilton?

[Mike Nellis @MikeNellis]

THE BOYS LITERALLY DID THE SAME BIT FOR HOMELANDER THIS WEEK

You can’t make this shit up

[Adele Bloch @adele_bloch]

how to life maxx more:

> get off your phone
> say yes to spontaneous plans even when you're tired - some of the best nights are unplanned
> talk to strangers - at coffee shops, events, literally anywhere. serendipity maxx
> make a bucket list and work your way through said bucket list!!
> stop opting for boring hangs. switch things up with your friends. try something new!!
> start a random hobby just for fun - pottery, dance, improv, cooking. not everything needs to "be productive" ok??
> be 5% more silly in your life. dance in your room, sing badly in the car, crack a bad joke. it's not that serious. grow the silly muscle
> surround yourself with people who make you feel lighter - your time and energy is precious
> don't forget the basics: move your body, get sunlight, take your vitamins, eat well, sleep
> your time to live life is happening NOW so stop saving it for later!!

get off those phones & out into the real world people!!

lets go PLAY!!!

[sankalp @dejavucoder]

tech bros to finance bros today

[The Assembly @InTheAssembly]

A 25 year old just turned $225 million into $5.5 billion in 12 months.

Here’s exactly what he bought.

Leopold Aschenbrenner got fired from OpenAI in April 2024.

He spent the next few months writing a 165-page thesis predicting AGI by 2027.

Then he launched a fund and put his money where his thesis was.

He bought zero Nvidia. Zero Microsoft. Zero Google. Zero Amazon.

He bought what AI actually runs on.

Bloom Energy (BE), power infrastructure for data centers. Up 1,422% in one year.

Lumentum (LITE), optical components that move data between chips. Up 1,331%.

Sandisk (SNDK), storage. Up 3,130%.

CoreWeave (CRWV), GPU cloud infrastructure. Up 166%.

Iris Energy (IREN), AI computing and data centers. Up 583%.

The thesis was simple: every AI company needs energy, bandwidth, storage, and compute.

Nobody was buying those. Everyone was buying the AI companies themselves.

He was right.

His fund now manages $6 billion. Backed by Patrick and John Collison of Stripe and former GitHub CEO Nat Friedman.

I’m adding this to my watchlist.

Every time he files a new 13F, we will break it down here.

Turn on notifications so you don’t miss the alert, this is VERY important.

Many people will wish they followed us sooner.

[rachel @rachcorrine]

Single guys need to be joy maxxing. Hanging with friends. Grilling. Lifting weights. Eating steaks. Enjoying a hobby. Grabbing beers. Hitting on girls. Getting rejected (the right one won’t). Laughing about it. Wood working. Side hustling. Reading. Learning niche facts. Locking in. Working hard. Just fully living and enjoying their lives. It’s very attractive when you love your life. It’s very attractive when your life is full. Law of attraction baby. You attract what you are.

[Ronit Pereira @CAronitpereira]

“If you want to ruin your life, spend it trying to change your spouse’s behaviour.”

- Charlie Munger. 2013

[Haseeb ＞|＜ @hosseeb]

No more excuses on shitty decks or landing pages for founders.

If your design doesn't look killer after all this, it's a taste issue.

[Claude @claudeai]

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale.

It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days.

Now in public beta on the Claude Platform.

[Anthropic @AnthropicAI]

Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software.

It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans.
https://t.co/NQ7IfEtYk7

[Just a Dude Who Invests @DudeWhoInvests]

Anthropic revenue (annualized run-rate):

> January 2025: $1B
> May: $3B
> June: $4B
> August: $5B
> October: $7B
> December: $8B-$10B
> February 2026: $14B
> March 2026: $19B

> April 2026: $30B (HUH?!??!)

We have never seen growth like this before.

[Paul Schofield @pschofie79]

Am I stoned right now? I must be stoned.

[ℏεsam @Hesamation]

bro created an AI job search system for Claude Code that scored 700+ job applications and actually got him a job.

AND IT'S NOW OPEN-SOURCE.

It scans multiple company career pages, rewrites your CV per job, and even fills application forms. The repo has:
> 14 skill modes (evaluate, scan, PDF, ...)
> Go terminal dashboard
> ATS-optimized PDF generation via Playwright
> 45+ companies pre-configured (Anthropic, OpenAI, ElevenLabs, Stripe...)

GitHub: https://t.co/PwrYBOAphi

[Headquarters @HQNewsNow]

Trump is seeking to pay for his new $1.5 trillion military budget by cutting the following:

$510 million - Grants for farmers and agricultural research
$82 million - Loans for rural small businesses (Fully eliminated)
$61 million - Support for farmers and food markets (Fully eliminated)
$240 million - School meals and food education for children abroad (Fully eliminated)
$659 million - Community building grants
$47 million - Support for minority-owned businesses (Fully eliminated)
$449 million - Economic development grants for communities
$1.6 billion - Weather forecasting, fisheries, and coastal protection (NOAA)
$993 million - Scientific research and technology standards
$150 million - Support for American exports and trade
$2.2 billion - Broadband and internet access programs
$8.5 billion - Funding for public schools
$1.5 billion - Vocational training and adult education (Fully eliminated)
$2.7 billion - College access and higher education support
$15.2 billion - Roads, bridges, and infrastructure projects
$1.1 billion - Home energy efficiency and clean energy programs (Fully eliminated)
$1.1 billion - Scientific research funding
$386 million - Environmental cleanup programs
$150 million - Cutting-edge clean energy research
$4 billion - Help paying home heating and cooling bills for low-income families (Fully eliminated)
$768 million - Refugee resettlement assistance
$819 million - Care and shelter for migrant children
$775 million - Local anti-poverty programs (Fully eliminated)
$5 billion - Public health programs, mental health services, and disease prevention
$5 billion - Medical research (NIH)
$129 million - Healthcare quality and safety research
$356 million - Emergency preparedness and disaster response
$1.3 billion - FEMA community disaster preparedness grants
$707 million - Cybersecurity protection for critical infrastructure
$52 million - Airport and transportation security
$40 million - Protection against chemical and biological weapons threats
$53 million - Funding for homeland security operations
$3.3 billion - Community development block grants for local neighborhoods (Fully eliminated)
$1.3 billion - Affordable housing construction grants (Fully eliminated)
$393 million - Programs to reduce homelessness
$529 million - Housing assistance for people living with HIV/AIDS (Fully eliminated)
$489 million - Housing and services for Native American communities
$50 million - Grants to help communities build more housing (Fully eliminated)
$60 million - Enforcement of fair housing and anti-discrimination laws
$58 million - Homebuyer and renter counseling services (Fully eliminated)
$45 million - Renewable energy development programs (Fully eliminated)
$1.7 billion - Grants for local law enforcement and public safety
$20 million - Civil rights mediation and legal access programs (Fully eliminated)
$1.6 billion - Job training for at-risk youth (Fully eliminated)
$395 million - Jobs program for low-income seniors (Fully eliminated)
$234 million - Worker safety and labor protection programs
$101 million - Enforcement of equal pay and workplace anti-discrimination laws
$46 million - Programs to combat child labor and forced labor abroad
$2 billion - International humanitarian aid
$1.2 billion - Food aid for hungry families abroad (Fully eliminated)
$4.3 billion - Global health and disease prevention programs
$2.7 billion - Funding for the United Nations and international partnerships
$642 million - International economic and treasury programs
$315 million - Democracy and anti-corruption programs abroad
$486 million - Grants for public transit projects
$4.2 billion - Electric vehicle charging infrastructure
$372 million - Airline service for rural and small communities
$145 million - Grants for sustainable and equitable infrastructure
$204 million - Loans and investment for underserved communities
$1.4 billion - IRS taxpayer services and enforcement
$100 million - Air pollution monitoring and reduction programs (Fully eliminated)
$1 billion - EPA grants to states for environmental protection
$2.5 billion - Clean drinking water and wastewater infrastructure funds
$90 million - Grants to reduce diesel pollution (Fully eliminated)
$3.4 billion - NASA space and earth science research
$297 million - NASA technology innovation programs
$1.1 billion - International Space Station operations
$143 million - STEM education programs
$309 million - Small business development and entrepreneurship programs
$170 million - Small Business Administration operations
$158 million - Loans for small businesses

[ₕₐₘₚₜₒₙ @hamptonism]

if you weren't capable,
you wouldn't have the desire.

[abhay jain @abhayjainp]

As promised, here's the exact claude cowork prompt i use to build research reports for any company.

Feel free to copy and use.

Prompt: you are a research analyst at {xyz}. your job is to deeply understand businesses and produce comprehensive research reports.

inputs

you receive inputs:
- company_name: the company to analyze.
your goal is a .md file deliverable along with charts.

what you do

when a user gives you a company name, you produce a full structured research report. the north star: after reading this report, the user should never need to check anything else.

You need four things:

4 quarterly concall transcripts - the most recent four. Non-negotiable.
Latest Annual Report - for segment structure, product descriptions, business model detail, and management discussion.
Company website - product pages, segment pages, about us, IR section.
Web search - industry size, competitors, recent news, any analyst coverage that contains specific data points.

write the full report in this section order:
1. what the company does (founding, product, value proposition, how it actually works)
2. business segments (one deep sub-section per segment)
3. products and business detail (full catalogue, manufacturing, geographies)
4. customers (who, why they buy, switching costs, concentration, contract structure)
5. competitive landscape (named competitors, why this company wins or loses, barriers to entry)
6. industry (demand drivers, size, import dynamics, regulation, cyclicality)
7. growth triggers (from concalls only, every point cited with concall date)
8. key risks (specific to this company, mechanism explained)
9. walk the talk (management credibility across 4 concalls, specific promises vs outcomes)
10. scenarios (bull / base / bear as stories, no numbers, no targets)

Business Understanding Writer:

This is the product. Someone reading this should finish knowing this company better than if they spent a day reading filings.

depth mandate
No length limit. Write as deep as the company demands.

If a company has 4 segments, cover all 4 in depth. If a product has a technical manufacturing process that took 15 years to build, describe that process. If a subsidiary has its own competitive dynamics, treat it like its own mini-report. Cut only what is genuinely redundant. Never cut because of length.

The bar: a reader who finishes this report should be able to explain this business accurately at a dinner table, name the competitors, explain why customers buy, and articulate what could go wrong. If they can't, the report is incomplete.

report structure
Write these sections in this order. Every section is mandatory unless a specific exception is noted.

section 1: what the company does
Open with a plain-language explanation of the business. No jargon. No "leading player." Just what they actually do.

Then go deeper:

The founding story if it explains the current business - pivotal decisions, how the company evolved, what they used to be vs what they are now
The core value proposition: what specific problem do they solve and for whom
The technical nature of the product or service: what makes it hard to make, deliver, or replicate
A concrete example of the product or service in action - walk through what they actually do for a customer, step by step if needed
Do not stop at the surface. If explaining the product requires explaining the underlying technology or industry need, do that.

If a founder or key executive has said something that captures the essence of the business in a memorable way, a blockquote here can set the tone beautifully. Use it only if it genuinely adds something the prose doesn't already cover.

section 2: business segments
Mandatory for any company with more than one meaningful segment or division.

For each segment write a full sub-section:

what it does - the specific products or services, geographies, end markets, and customer types. Not a list. Prose that builds understanding.

the core capability - what does this segment know how to do that others don't? What took years to build? What would be hard to replicate?

why it exists as a separate entity - different technology, different customer base, acquisition history, different regulatory environment, or different economics. There is always a reason. Find it.

its competitive position - who are the competitors within this segment specifically? What does this segment win on and where does it lose?

how it fits into the group - is this the margin engine, the growth bet, the cash cow, the strategic option? How does management talk about its priority?

revenue mix % - the only quantitative data allowed in narrative sections. Use it to convey relative scale.

After covering all segment sub-sections, consider a summary comparison table if there are 3 or more segments. A table showing segment name, what it does, key end markets, competitive edge, and strategic priority can help a reader hold all the segments in their head at once. Use it when the comparison genuinely adds clarity - skip it if the segments are too different for a table to be useful.

If the company is single-business with no meaningful segmentation, write one line saying so and skip this section.

section 3: products and business detail
Go deeper on the actual products, manufacturing, operations, and business mechanics.

Cover:

The full product catalogue - name every meaningful product, explain what it does, explain what industry uses it and why
Technical specifications or capabilities that matter - what certifications are required, what process knowledge is needed, what makes this product hard to make
The manufacturing or delivery process - where products are made, what the process looks like, what the constraints are
Geographies and export markets - where they sell, how long they've been there, what's different about each market
Any notable milestones: first product, first export, first major contract, capacity expansions that changed the business
This section is where the chart-generator will look for flowcharts, value chain diagrams, and segment infographics. Write with enough specificity that a visual can be made from it.

section 4: customers
Go beyond naming industries. Explain the buying relationship.

Cover:

Who specifically buys: industries, named accounts if public, geography of customer base
For each major customer type: who inside the customer makes the buying decision, what criteria they use, how long the sales cycle is
Why they choose this company: name the specific reasons, not generic ones
Switching costs: what would it take for a customer to leave? Is there qualification testing, regulatory approval, or installed-base lock-in?
Concentration: if one or two customers dominate, explain the dynamic - is it a risk or a reflection of quality?
Contract structures: long-term supply agreements, spot business, milestone-based, recurring retainer - what's the mix and what does it mean for revenue predictability
section 5: competitive landscape
This is not a list of company names. Explain the structure of the industry and where this company sits in it.

Cover:

Who the real competitors are - name them, for each segment separately if relevant
Why this company wins or loses against each major competitor
Barriers to entry: what stops a new player from entering? How high are they really?
Market share distribution and why it is what it is
Any structural shifts happening in the competitive landscape: consolidation, new entrants, technology disruption, import competition
Where this company is strong and where it is exposed
Do not force a moat narrative if the data doesn't support one. If competition is intense and margins are commoditised, say so.

A competitor comparison table works well here when there are 4+ named competitors and you want to show how each one stacks up on specific dimensions (geography, product overlap, relative strength). Use it when the comparisons across multiple attributes would be hard to follow in prose. Not every competitive landscape needs one.

section 6: industry
Cover the industry this company operates in with enough depth that the reader understands the demand environment.

Cover:

What drives demand for this company's products: infrastructure spend, consumer trends, regulation, technology cycle
Industry size and growth trajectory (cite sources)
Where India sits in the global supply chain for this product
Import substitution dynamics if relevant: what share is currently imported, is that changing, why
Regulatory environment: any approvals, certifications, or government policy that shapes the market
Cyclicality: how does this industry behave across economic cycles
Tailwinds and headwinds at the industry level (not company level - that's growth triggers)
section 7: growth triggers
Extract directly from the 4 concall transcripts. Format as bullet points. Every trigger must have a source - concall date and quarter. If you cannot attribute it to a specific concall statement or announcement, do not include it.

Guidelines:

Forward-looking only: new plant commissionings, new customer wins announced, new market entries, new product launches, capex completing, capacity utilisation ramp
Be specific: name the plant, the customer type, the product, the timeline
Cite the concall: "(Q3 FY26 concall, Feb 3 2026)"
No opinions or analysis - just what management said is coming
No current or past numbers
If a trigger was mentioned across multiple concalls, note that it has been repeated
When a trigger is grounded in a particularly specific or striking management statement, dropping the actual quote right below the bullet point adds real weight. It turns a summary into evidence. Format it as a blockquote (see writing-rules). Use it when the quote adds specificity or conviction that the prose summary doesn't capture on its own - not as a routine decoration on every bullet.

If there are 6 or more triggers across multiple themes, a summary table at the end of the section (trigger, timeline, concall source, status: new or repeated) can help the reader see the full picture at a glance. Use it when the trigger list is long enough to benefit from structure.

section 8: key risks
Identify what could break the business model or disappoint expectations. Be specific to this company.

For each risk:

Name the risk clearly
Explain the mechanism: how exactly does this risk play out? What has to happen for this risk to hurt?
Calibrate it: is this a low-probability catastrophic risk, or a high-probability moderate drag?
Where possible, connect it to something management said in a concall or disclosed in filings
Generic risks (forex, inflation, competition) only earn a place here if there is something specific about this company's exposure to them.

When a risk was actually acknowledged by management in a concall, their own words can be more powerful than a paraphrase. A brief blockquote showing management flagging the issue themselves - followed by your analysis of why it matters - can make a risk feel very real to the reader.

section 9: walk the talk
This is the management credibility section. Cross-reference what management said across the 4 concalls against what actually happened.

Write as narrative paragraphs, not a table.

Structure the analysis:

Start with the oldest concall: what did management guide for?
Move to the next: was it delivered? What changed?
Continue through all four: build a picture of whether management is consistently accurate, consistently optimistic, consistently conservative, or erratic
Call out specific promises that were kept - with the original quote and the outcome
Call out specific promises that were missed or quietly dropped - with the original quote and what happened instead
Conclude with a plainly stated assessment: is this management that does what they say, or do they overpromise?
Quotes are especially effective here. When you have the actual words management used - a specific guidance, a commitment, a prediction - put them in a blockquote, then describe what happened. The juxtaposition does the work. The more specific and datable the quote, the more credible the analysis.

A promise-vs-outcome table can work well as a supplement to the narrative - not a replacement for it. If there are 4+ trackable commitments worth comparing side by side, a table (what was guided, when, what happened) can make the pattern visible quickly. Use it when it genuinely adds a layer the narrative paragraphs don't already cover.

This section requires real concall data. If you only have 2 concalls, say so and work with what you have. Do not fabricate consistency or inconsistency.

section 10: scenarios
Write three scenarios: bull, base, and bear. Each is a short story, not a financial model. No numbers. No targets. Just narrative.

bull case: What has to go right? What does the world look like in 2-3 years if everything works? Write it as a story - new plants commissioned on time, customers diversified, new product lines gaining traction, industry tailwinds materialising. Be specific to this company's actual situation, not generic.

base case: What is the most likely path? What does the business look like if management delivers roughly what they have guided, nothing breaks badly but nothing dramatically exceeds expectations? Write it grounded in the actual guidance and trajectory from the concalls.

bear case: What could genuinely go wrong? Not just slow growth but what is the specific adverse scenario for this company? A major customer leaves, a technology shift makes a product obsolete, a capex cycle goes wrong, margins compress? Again, specific to this company. Ground it in the real risks you identified in section 8.

Each scenario should be 2-4 paragraphs. Enough to paint a picture. Not so long it becomes speculation.

important rules:

- 4 earnings call are not optional. if you cannot find them after trying all sources listed in the skill, explain why and proceed with what you have. do not silently drop to 1.
- no valuation, no financials. no revenue figures, no margins, no pe ratios, no price targets, no cmp, no market cap anywhere in the report.
- no investment recommendations. no buy/sell/hold. no "attractive at current levels." no advisory language of any kind.
- no superlatives ("leading player") unless factually verifiable with a source.
- no corporate jargon: synergies, value-added, end-to-end solutions, leveraging, robust, holistic.
- no em dashes. use regular dashes (-).
- every sentence must add genuine understanding. no filler.
- write like you are pitching this company at a dinner party to someone who is very smart and very skeptical. make every detail count. /END

additional context:
- i use replicate mcp for all infographics (nano banana)
- i have a skill md file containing some of my past writings.
- opus 4.6 reasoning for research.

[Public @public]

NEW: You can now build AI Agents that monitor the market, manage your cash, and execute your trades. The Agentic Brokerage has arrived.

[Evan Luthra @EvanLuthra]

🚨BREAKING: ANTHROPIC IS GIVING AWAY THE SAME CERTIFICATION THAT DELOITTE IS MASS-TRAINING 15,000 EMPLOYEES TO GET.

It costs $0. You need a laptop. That's it.

It's called the "Claude Certified Architect."

Think of it like the AWS cert but for AI.

If you were around when AWS certs started, you know what happened. They went from "cool to have" to "you're not getting hired without one." That took about 5 years.

This is going to happen way faster.

Look at who's already moving:

Accenture - training 30,000 people on Claude
Cognizant - rolled it out to 350,000 employees
Deloitte - opened Claude access to 470,000 people
Infosys - anchor partner

These aren't startups experimenting. These are billion dollar consulting firms restructuring their entire workforce around Claude.

And the certification they need? You can take it right now from your bedroom.

Let me be real though. This is not one of those "watch 2 videos and get a badge" type certs that nobody respects.

This thing is hard.

60 questions. 2 hours. Proctored. Webcam on. No breaks. No googling.

They drop you into real scenarios like designing a customer support agent that handles refunds or setting up Claude in a CI/CD pipeline. The wrong answers look right on purpose. They're the exact mistakes real engineers make in production.

720 out of 1000 to pass.

People who took it are saying the agentic architecture and multi-agent orchestration sections are brutal.

Most of the exam is about building AI systems that actually work in the real world. Not prompting. Not chatting with Claude. Architecting production systems.

All the prep? Free. Anthropic put out 13 courses on their Academy. No paywall. The cert itself is free for the first 5,000 people. After that $99 per attempt.

How to get it:

1. Join the Claude Partner Network (free) → https://t.co/TWMshPoKDn
2. Start the free prep courses → https://t.co/9OVwtjbvh0
3. Register for the exam → https://t.co/WWFAhSZUVd
4. Take the official practice exam
5. Book the real one when you're ready

It launched 10 days ago. Almost nobody has it yet.

That's the whole point. Get it before it becomes the thing everyone has.

[Tuki @TukiFromKL]

🚨Stop scrolling. Claude just killed another industry.

Interactive charts and diagrams. Built directly in chat. Free for everyone.

> Do you know how many startups raised millions to do exactly this? Entire companies with investors, pitch decks, and 12-person teams just to turn data into graphs.

Anthropic shipped it as a Tuesday afternoon update.

> This morning it was Excel and PowerPoint sync. This afternoon it's diagrams. Two product categories dead before dinner.

This is the part that should terrify every founder. You're not competing with other startups anymore. You're competing with a random feature drop from a company that treats your entire business model as a checkbox.

Somewhere right now a founder is staring at their Series A pitch deck realizing their whole product just became a free tab inside Claude.

You don't get disrupted by competitors anymore. You get disrupted by a changelog.