Use Claude they said.
Upload your decks the said.
Unleash all this productivity they said.
But apparently, I first need to start a new chat, delete some of the deck and not exceed the maximum image countโฆjust like my existing brain.
Microsoft just turned an $11 billion startup into a Word feature.
Harvey raised $200M at an $11B valuation in March on the bet that legal AI is its own surface. The numbers held that up. $190M ARR per TechCrunch's December reporting. 100,000 lawyers across 1,300 organizations including the majority of the AmLaw 100. Around $1,200 per lawyer per month per Sacra. Big firms paid because Harvey was the only tool in the category that worked.
Brad just stapled a legal agent directly inside Microsoft Word, shipping in the $30 per seat Copilot subscription every law firm already pays for. Same surface every lawyer drafts in. Same .docx that gets sent and redlined. No second login, no procurement cycle, no migration. The price gap is roughly 40x.
The interesting tell: Microsoft built the agent with legal engineers, many of them from Robin AI, a legal AI startup that recently went under, per Artificial Lawyer's reporting. The talent that knew how to make legal AI work for lawyers landed at Microsoft after their startup couldn't survive standalone. That's the legal AI category in one sentence.
Distribution was always the constraint here. Lawyers don't switch tools. Word is where contracts get drafted, redlined, and tracked. Whichever AI lives inside that .docx wins the default workflow, and Microsoft just walked through the door uncontested.
Harvey's surviving moat is the AmLaw 100 partner workflow. Domain training, agentic litigation prep, deep integrations with iManage and NetDocuments. Real moat for $1,500-an-hour partners running M&A and complex litigation. It does not extend to the millions of lawyers globally drafting NDAs, redlining vendor contracts, and updating templates. That layer is exactly what Word Legal Agent goes after, and Microsoft can ship it as a feature inside a $360-a-year subscription.
The $11B valuation pays out only if legal AI work stays its own surface. Microsoft just absorbed the surface.
most growth marketers use AI to rewrite headlines and call it a day. here's how I actually use Claude on the growth marketing team at @AnthropicAI across chat, Claude Cowork, and Claude Code ๐
ANTHROPIC JUST PROVED MOST PEOPLE HAVE NO IDEA HOW TO PROMPT CLAUDE.
Their applied AI team dropped a 24 minute free workshop.
Not a creator who reverse engineered it.
Not a Reddit thread.
ANTHROPIC.
The people who wrote the weights.
And what they showed is uncomfortable.
There are 6 elements to a properly structured Claude prompt.
Most people are using 1.
Maybe 2.
That is not a skill issue.
That is an information issue.
And it has been quietly costing you every single day.
The outputs that felt slightly off.
The responses you had to rewrite 4 times.
The prompts that worked once and never again.
All of it traces back to the same 6 missing elements.
The people who watch this 24 minute workshop tonight will understand something about Claude that most daily users still do not know exists.
The people who skip it will keep getting 30% of what the tool is actually capable of and wonder why the results never quite land.
I watched it twice.
Then I built a Claude Skill that applies all 6 elements to every prompt automatically.
No more thinking about structure.
No more guessing what Claude needs.
The framework runs in the background every single time.
Full breakdown and skill setup is below.
Bookmark this now.
Watch the workshop first.
Then read the guide.
This is the one that compounds.
Follow @cyrilXBT for the exact prompt architecture, Claude skills, and systems I use to get outputs most people do not believe came from one person working alone.
We spent a lot of time trying to do tokenization and PII protection ourselves. And then decided to turn to existing tools that help with PII. There are a few available, but some of them are pricey. If youโre interested in this approach, try NoPII. Theyโve got a very generous free tier to get you started.
This was the exact problem we faced. The solution lies in tokenization and not a PII scrubber. Imagine redacting everything from a document and AI having to make head or tail of it. Tokenizing PII maintains context. Iโm happy to discuss this further with you if it helps solve your PII challenge.
I automated my content engine and 2 hrs/day dropped to 10 min
[ whatโs new in v2 ]:
- 9 platforms scraped while I sleep โ 2,000+ topics/day
- a 5-signal scoring brain that filters down to the 10 that matter
- voice DNA writer.. same tone, different structure every time
- a self-learning loop that remembers every approve and decline
- profile DNA โ knows exactly what goes viral on MY account
v1 was a brain with no body
v2 has eyes, a filter, and memory + fully automated
Hereโs how to build it step-by-step โ
[ The architecture]:
/content-engine
โโโ scrapers/ (9 platform scrapers)
โโโ extension/ (chrome ext for X, linkedin, reddit)
โโโ ai/
โ โโโ https://t.co/JLmuw236QH (5-signal scoring brain)
โ โโโ content_writer.py (voice DNA + structures)
โ โโโ profile_analyzer.py (your positioning DNA)
โ โโโ sentiment_analyzer.py
โโโ publisher/ (export + time slot scheduling)
โโโ gui/dashboard.py (streamlit command center)
โโโ ingest_server.py (local server on localhost)
โโโ data/content_engine.db (everything stored locally)
let me walk you through each layer โ
LAYER 1: Research engine
9 sources scanned 24/7 (X, reddit, YT, HN, github, trends + chrome ext for reddit and linkedin)
every post you scroll past gets tagged and stored locally
LAYER 2: Scoring brain
every topic scored on 5 signals:
- freshness (0.20)
- velocity (0.25)
- virality (0.25)
- relevance (0.20)
- uniqueness (0.10)
velocity 8+ โ forced min score of 7. catches late bloomers that suddenly explode
2,000 topics โ top 10 ranked
LAYER 3: Voice DNA writer
not one structure every time. system picks the format:
- short take
- tactical playbook
- QT contrast
- contrarian
- resource drop
- proof post
a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words
LAYER 4: Dashboard Streamlit
dark theme. 5 tabs
review queue = tinder for content. swipe approve, swipe decline
LAYER 5: Publishing
no auto-posting. zero account risk
approve โ pick a slot (8am / 12pm / 5pm) โ exports a .txt โ copy / paste / post
also auto-drafts a linkedin version of every approved tweet
LAYER 6: Self-learning loop
every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain
month 1: you approve 30%
month 3: 70% pre-filtered
month 6: 10 min/day
LAYER 7: Profile DNA
analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account
the scoring brain uses it to prioritize what already works for you
daily run: open dashboard โ 10 min reviewing โ post 3x โ close
total cost: ~$15/month
everything else: local, sqlite, no cloud, no subscription
unfortunately I couldnโt paste in long-form format initial description which was made before
but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code
reply "ENGINE" + RT and I'll DM you access to test it (follow me first so I can write)
save this so you don't lose it
5 reasons your offer isn't converting:
1) Targeting poor people
2) Not enough Proof
3) Too little friction
4) Big outcome not fast enough
5) "Sounds like work"
My new paper on "AI Consciousness".
I argue that to talk about that we need to have *validated* theories of human consciousness (and we're very far from that)
Accepted at AAAI Symposium 2026 on Machine Consciousness.
Feedback and discussion welcome.
The three terms every SaaS founder needs in 2026:
SEO โ rank on Google
AEO โ be the answer AI gives
GEO โ be the source AI recommends
You've been optimizing for one.
Your competitors are about to optimize for all three.
Dear expat techbros of Bangalore.
That Y Combinator gig is not where you will get your next investment. Neither is it that 9000 rupee run event or that pure veg thindi walk in Gandhi Bazaar/Malleswaram.
The really big funding deals happen in Century Club, Bowring Institute, the Karnataka Golf Association, Bangalore Club and Karnataka State Cricket Association, over beers and baby corn Manchurian. If you are not a member of these clubs, find a co-founder who is.
These guys have not studied in your nouveau riche Greenwood or DPS or Narayana or Brigade type schools. Nor are they former IIT aspirants from dummy schools in Kota or Vizag. They don't subscribe to Finance with Sharan.
Their dads wear safari suits and are board members in nondescript co-operative banks, which they treat as their private piggy banks. They have land in Devanahalli and Maddur. Bathroom fittings showroom in Kumara Park.
Your co-founder needs to be from Mallya Aditi, Valley School, Bishop Cottons, Baldwins, Frank Antony or St. Josephs (European). Management quota seat in RV or PESIT, or BCom from Surana College.
Old money. Political connections. ICSE English. No Fear Sticker.
Basically get a Danish Sait as your co-founder.
AI wonโt make most human skills obsolete, but it will change how theyโre used.
Negotiation, problem solving, and leadership will matter more than ever as people work alongside agents and robots.
Our new Skill Change Index shows which skills will be most, and least, exposed to automation in the next five years: https://t.co/fRXfHF1k56