Faraji

[Faraji @farajidotAI]

@bfeld is awesome #bananalounge

[Y Combinator @ycombinator]

It’s never been easier to design your dream house.

Draw a shape. Define your rooms. Set your constraints.

@DraftedAI generates complete floor plans, elevations, and 3D home designs in seconds.

Over the last month, 120,000 people generated 325,000+ home designs with https://t.co/XqC0LP5n3y.

[Jake @JakehellerAI]

This week in AI for Real Estate was interesting:

1) Fifth Dimension raised $26M Series A led by HV Capital. Their AI agent "Ellie" drafts IC memos, screens deals, and integrates with Yardi, Dealpath, and Argus with no data migration.

2) Coatue Management launched "Next Frontier" - a dedicated venture acquiring land near power sources for AI data centers. (this was a couple weeks ago but really relevant)

3) Crexi expanded its AI suite this week. Crexi Create (auto-generated OMs from financials and rent rolls) goes public shortly...

4) FORE Real launched in early access. Built inside Pegasus ($4B AUM, 400 properties across 37 states). Four AI agents: property tax appeals (going straight at the 25-40% contingency fee industry), insurance compliance, lease abstraction, tenant communications. Owner-operators are starting to build AI with their proprietary data instead of licensing horizontal tools.

5) First American and DealGround surveyed 255 CRE pros: 66% use AI weekly, only 5% trust it for actual deal decisions. 31% report zero meaningful time savings.

6) Leni published head to head benchmark results showing their CRE-vertical AI beat OpenAI, Anthropic, Google, and Perplexity on four tests. First credible vertical-AI win against the foundation models.

7) AI companies now account for ~20% of major US office leases.

And don't forget to register for the Yardi + AI for CRE Collective webinar May 20th if you want to see what happens when you connect Yardi Virtuoso to Claude... Link below!

[Faraji @farajidotAI]

I’m honestly not sure what to do with this. Definitely feels like the straw that will get the peasants out with their pitchforks

[Deedy @deedydas]

The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen.

Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation).

Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there.

Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI.

As a result,
1. The corporate ladder looks like the wrong building to climb.
Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more.

2. There’s a deep malaise about work (and its future).
Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire"

3. The mid to late middle managers feel paralyzed.
Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies.

4. The rich aren’t particularly happy either.
No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money."

I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here.

Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success".

Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.

[Faraji @farajidotAI]

https://t.co/gQgHA6eCzB

[Packy McCormick @packyM]

Mom how did we get so rich?

Back in 2026, your dad read the YC Request for Startups and just built one of the ideas on the list.

[Faraji @farajidotAI]

@ataraxia1557 @coldxman @GlennLoury Shoulda been more respectable, I guess

[Aaron Levie @levie]

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise.

Some quick takeaways:

* Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow.

* Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated.

* Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs).

* Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these.

* Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs.

* Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy.

* Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems.

* Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been.

One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise.

This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

[Aakash Gupta @aakashgupta]

There's a physicist at Stanford named Safi Bahcall who modeled this exact principle and the math is wild.

He calls it "phase transitions in human networks." When you're stationary, your probability of a lucky event is limited to your existing surface area: the people you already know, the places you already go, the ideas you've already been exposed to. Your opportunity window is fixed.

When you move, your collision rate with new nodes in a network increases nonlinearly. Double your movement (new conversations, new cities, new projects) and your probability of a serendipitous encounter doesn't double. It roughly quadruples. Because each new node connects you to their entire network, not just to them.

Richard Wiseman ran a 10-year study at the University of Hertfordshire tracking self-described "lucky" and "unlucky" people. The single biggest differentiator wasn't IQ, education, or family money. Lucky people scored significantly higher on one trait: openness to experience. They talked to strangers more, varied their routines more, and said yes to invitations at nearly twice the rate.

The "unlucky" group followed the same routes, ate at the same restaurants, and talked to the same 5 people. Their networks were closed loops. No new inputs, no new collisions.

Luck isn't random. Luck is surface area. And surface area is a function of movement.

The lobster emoji is doing more work than most people realize. Lobsters grow by shedding their shell when it gets too tight. The growth requires a period of total vulnerability. No protection, no armor, soft body exposed to the ocean.

That's the cost of movement nobody posts about. You have to be uncomfortable first. The new shell only hardens after you've already moved.

[Som Mohapatra @Som_Mohapatra]

https://t.co/Y802dxK1Il

[Martin Austermuhle @maustermuhle]

Of nerdy urbanist interest: Next week the D.C. Council will cast a first vote on @BrianneKNadeau's bill to allow for new D.C. buildings up to six stories tall to have only a single stairwell in them, instead of the current two. Proponents say it creates more residential space.

[Chris Lu @chris__lu]

https://t.co/HbzEpcOaUh

[Faraji @farajidotAI]

@kristoncapps This is literally the first time I’ve ever see this

[Faraji @farajidotAI]

@kristoncapps Also doesn’t have good transit. A mile from either of the closest metro stations. I’d have to agree that it probably sits a while absent massive intervention

[DC Office of Planning @OPinDC]

Tell us what you think! We're hosting two in-person workshops to present the plan and gather feedback. Register today: https://t.co/rPYNZj4i7g
☀️DC 2050 Workshop
🗓️TODAY! March 18 (6-8 pm) or March 21 (11am - 1 pm)
📍MLK Memorial Library (Closest metro: Gallery Pl/Chinatown)

[Nav Toor @heynavtoor]

🚨BREAKING: MIT hooked people up to brain scanners while they used ChatGPT.

What they found should concern every single person reading this.

ChatGPT users showed 55% weaker brain connectivity than people who didn't use it. Not after years. After just four months.

Here's how they tested it. 54 people were split into three groups: one used ChatGPT to write essays, one used Google, and one used nothing but their own brain. They wore EEG monitors that tracked their brain activity in real time across four sessions over four months.

The brain-only group built the strongest, most widespread neural networks. Google users were in the middle. ChatGPT users had the weakest brains in the room. Every time.

Then the memory test hit. Participants were asked to recall what they'd just written minutes earlier. 83% of ChatGPT users couldn't quote a single line from their own essay. They wrote it. They couldn't remember it. The words passed through them like they were never there.

It gets worse. In the final session, ChatGPT users were told to write without AI. Their brains were measurably weaker than people who never used AI at all. 78% still couldn't recall their own writing. The damage didn't go away when the tool was removed.

Meanwhile, brain-only users who tried ChatGPT for the first time? Their brains lit up. They wrote better prompts. They retained more. Their brains were already strong enough to use AI as a tool instead of a crutch.

The researchers also found that every ChatGPT essay on the same topic looked almost identical. More facts, more dates, more names. But less original thinking. Everyone using ChatGPT produced the same generic output while believing it was their own.

MIT gave this a name: cognitive debt. Like financial debt, you borrow convenience now and pay with your thinking ability later. Except there's no way to pay it back.

The question isn't whether ChatGPT is useful. It's whether the price is your ability to think without it.

[Faraji @farajidotAI]

@willahmed @shaig I see how you slipped that careers page in there. Well done.

[Faraji @farajidotAI]

@Yayeezy My thoughts and prayers and all, but I know the food at that household bussin

[Imade. @ImadeIyamu]

If you're in the U.S., GovAI's Summer Fellowship is open

It's a 3-month program in Washington, DC with mentorship from leading experts in AI policy & opportunities to build skills & launch impactful careers in U.S. AI governance

Stipend: $7k/month + travel support

https://t.co/0WtE4yFloq
Deadline: March 1