Brian Mwangi

Your Location Intelligence Partner

[Brian Mwangi @itsbrian_mwangi]

The early March 2026 flash floods in Nairobi County were among the most severe in recent years. Using Sentinel-1 radar and Sentinel-2 optical imagery, I mapped approximately 21.4 km² of inundated areas.
#GEOINT2026 #NairobiFloods #ClimateChange #UrbanPlanning #GIS

[Brian Mwangi @itsbrian_mwangi]

@amerix The less educated need the litter to change their lives.

[a16z @a16z]

"Most people aren't looking to save time, they're looking for ways to spend their time."

9 of 15 consumer internet categories have zero AI products in the Top 100. These built some of the biggest companies of the last two eras:

- Streaming
- Social
- Dating
- Gaming
- Travel
- Retail
- Finance
- Real estate
- Jobs

More charts in our Top 100 Consumer AI Apps breakdown: https://t.co/J9edFBQvCN

[Nelly IRL @CatalystMindHQ]

Consistency is 🔑

[Osiris Trader @osiris_trader]

Screener for Binance, Bybit, OKX & Bitget

[Camille Roux @CamilleRoux]

Combien de temps pour aller de chez toi à n'importe quel endroit de ta ville en tram ou en métro ?

Cette carte te le montre d'un coup : pose ton départ, tout se colore selon le temps de trajet.

20 villes (Lyon, Marseille, ...) 👇

👉 https://t.co/B8IH6ZK2Tr

[Ryan Sael @RyanSael]

3D simulation for flood risk
https://t.co/agCDzJAbIw

The idea was to run a simulation to make it easier to understand why Pedreiras floods first and why Trizidela do Vale suffers more damage.

@WenzelNicacio, who is currently completing his master’s degree in Risk and Natural Disaster Management in the Amazon, reached out after seeing my previous post and wanted to visualize this in 3D.

I told him to give me as much context as possible, ideally in a PDF.

He compiled everything into one PDF, which I then gave to Opus 5.5.

Here’s the result:

[Tim @leerawllings]

When you win again 📟

[MBA Girly @MBAGirly]

What I am reading / watching this WEEKEND:

1) Yale: Value Creation in Search Fund Projects
2) Howard Marks: Shall We Repeal the Laws of Economics – Part III
3) Bloomberg: RedBird's Cardinale on Paramount & Investing
4) Diary of a CEO: WeWork Founder

[Rahul Kumar @RahulTechX]

One friend of mine makes $1.2 million a year as an Anthropic engineer.

I asked him how he learned prompting so well. He sent me a video that was never supposed to get out. Their core team's prompting playbook.

You won’t find anything better about prompting than this 30 minutes video.

I watched it last night. Halfway through, I realized I've been using Claude completely wrong for two years.

Watch it, then read the article below.

[Kyrox @kyr0stack]

Anthropic just dropped the best 1-hour workshop on Loop engineering: from one prompt to a loop that improves itself

5:31 - loop memory
11:02 - check, build, commit
13:06 - one feature per loop
33:03 - MVP in one hour

free, and the best thing on loop engineering I have seen

Prompts → Agents → Loops → Graphs

most people build the loop and stop there, because it works

the part almost nobody builds is what carries an accepted result into the next run

same model, same tokens, completely different week

watch it today

the step-by-step guide is below, save it while it is still early ↓

[Eric @amerix]

Learn to be strict with yourself.

Your time.

Your resources.

Your business.

Your discipline.

The moment you become mediocre, others will take advantage of you and mess you up.

It is better to be called a bully because being afraid to say NO will cost you a lot.

[Paradis @ParadisLabs]

Recommended reading for the weekend:

1. @a16z — State of Markets II
2. @GoldmanSachs — AI Is Becoming a Stock Picker’s Market
3. @FundaAI — Optics: FCC Transceiver Rules Might Be Better Than Feared, and Better for Top Chinese Players Than You'd Think
4. @abcampbell — There Are Bonds in the Singularity
5. @federalreserve — An Update on AI and the Economy

Have a great weekend everyone!

[shobhanai @HeyShobhan]

Andrej Karpathy spent 8 years at OpenAI and Tesla

Last week, he condensed everything he knows into one free 2-hour lecture

Agents → Loops → Harness → Self-Improving Systems

People pay $14K for bootcamps that teach less than this

This lecture beats most paid AI engineering courses

You probably don't have 2 hours right now

Don't let this disappear from your feed

Watch it

Then read the article below

[shobhanai @HeyShobhan]

SpaceXAI Chief Engineer (former Cursor employee):

"99% of people are still typing into chat windows, while only 1% have already hired an Agent team.

I run 6 bots—my chief assistant wakes me up at 5 a.m. with my entire day's schedule, and my travel bot delegates to my flight bot and hotel bot while I'm asleep."

In 27 minutes, he detailed how to build that team from scratch:

Chat → Copilot → GrokBot → Bot Teams → Self-Improving Systems

Prompts are already an outdated workflow—hiring an Agent team is the next one.

This talk's value surpasses most $700 Agent courses.

Save it now and watch today.

[Employee Tears @EmployeeTears]

I can’t call someone a dumb fuck at work, so instead I say, “walk me through your thought process”

[a16z @a16z]

Where does money invested into the AI buildout actually go?

For every $100 flowing into the supply chain:
- $50 to chips
- $20 to power
- $15 to networking
- $15 to cooling, buildings, and land

More charts in State of Markets II: https://t.co/MTaxKUxa2w

[David George @DavidGeorge83]

Introducing our State of Markets pt 2, along with a companion podcast where we unpack the data and discuss what comes next.

Tech is the everything cycle.

Supply: putting the buildout in context, just passed railroads as % of GDP. The wisdom of Elon is real: the factory (or the datacenter!) is the product.

Demand: diffusion is so, so early. Median AI vendor spending in the top 1% of companies is 8x that of the top 10%. Only about 30% of S&P 500 companies report a quantified AI impact, which means there’s a substantial opportunity in connecting models to a company's data and workflows. Diffusion into companies is one of the main themes of the next 5 years.

We’re entering the agent work period. Only a few million users today, but applicable to billions of internet users with massive surplus created. META/GOOG monetize US users at $200+ per year today. Agent opportunity is much higher.

Mega-trends the next 5 years: Consumer agents, Robotics, Autonomy, AI x bio, Personal health, Diffusion into enterprise, New era of American Dynamism.

Much more in our SoM report here - https://t.co/K4vOy4x3J6

@a16z @sarahdingwang @aleximm @santiago__rdz

[Brian Mwangi @itsbrian_mwangi]

Very informative for S&P

[a16z @a16z]

Where does money invested into the AI buildout actually go?

For every $100 flowing into the supply chain:
- $50 to chips
- $20 to power
- $15 to networking
- $15 to cooling, buildings, and land

More charts in State of Markets II: https://t.co/MTaxKUxa2w

[Tre_vor @Trev_gig]

Good morning the countdown continues

[Keiryosha | まちの計量舎 @machi_measure]

世界の標高・地形を動的な塗り分けで表示するサイトを発見したけど、地図体験としてかなりユニーク。制作者はBert Spaan氏。表示している範囲に応じて標高のカラースケールが動的に変わり、世界全体ではヒマラヤなどの大地形が、ズームしていけば微地形が見えるようになる。

データ基盤には Mapterhornを使用。Mapterhorn は複数のオープンなDEMを統合して配信しているプロジェクトで、世界全体は約30m解像度、国によっては1m以下のDEMまで入っている。

ウェブサイト：https://t.co/kkYn9W2CpA
制作者のlinkedin：https://t.co/3ufzh3wqz5