Phoenix

CRYPTO😺 NFA (NOT financial advice) 🌻
Politically curious Left, Right and Centre 😅

Go Leafs Go✌
$CRCL $SILVER $BTC $ETH $XRP

[Phoenix @kalai_mofta]

❤️

[Phoenix @kalai_mofta]

#montemorencyfalls #quebec2022

[Roberto Nickson @rpnickson]

This is awesome from @modretro

It comes with a blank cartridge, you build games with Codex and then play them on the device.

Great work on this activation @DylanAbruscato

[freeCodeCamp.org @freeCodeCamp]

Algorithmic trading combines market data, strategy logic, and brokerage APIs into one system.

In this course, you'll learn how to build a momentum trading app with Python and Django.

You'll use Massive, SnapTrade, and Alpaca Paper to generate signals and execute paper trades along the way.

https://t.co/aiMSUmZ9Nz

[copperhead @copperheadhq]

huge shoutout to @alexrgstudio for bringing @copperheadhq to life like this.

15 seconds of the actual product flow: prompt → specification → schematic/layout → deterministic verification → manufacturing outputs.

absolutely nailed it!

[cr3ghost @cr3ghost]

If you're learning malware analysis or reverse engineering, bookmark this.

RPISEC released the full materials from its Malware Analysis university course for FREE.

12 lectures + 10 hands-on labs + 4 projects covering:

• Static + dynamic malware analysis
• x86 + IDA
• Windows internals + WinAPI
• Malware behavior + persistence
• Anti-disassembly
• Anti-VM + anti-debugging + anti-AV
• Packing + unpacking
• Windows kernel + drivers
• Rootkit techniques
• Hooking + DKOM
• Anti-forensics + covert channels
• Runtime process manipulation
• APT sample analysis

It was designed for students starting with zero reverse engineering experience and built heavily around Practical Malware Analysis.

https://t.co/9RRL2LcI5q

Huge credit to RPISEC and original authors Branden Clark, Austin Ralls and Aaron Sedlacek for making the course materials publicly available.

#MalwareAnalysis #ReverseEngineering #WindowsInternals

[fred @heyfredds]

TUTORIAL DE 10 MINUTOS PARA CREAR SITIOS WEB 3D CON IA

paso a paso, desde cero

guárdalo antes de que lo necesites 🔖

[Matt Dancho (Business Science) @mdancho84]

Some guy built a free AI university on GitHub.

Not tutorials.
Not theory.
Full real-world AI systems.

Step by step.

Week 1 → Docker, FastAPI, databases
Week 2 → Automated data pipelines
Week 3 → Build your own search engine (BM25)
Week 4 → Hybrid search (semantic + keyword)
Week 5 → Full RAG system
Week 6 → Production-ready (caching + monitoring)
Week 7 → Agentic AI with LangGraph

You don’t just “learn AI”.

You ship it.

GitHub (free): https://t.co/hVeMP1DBPr

🚨 P.S. Want to learn how to build + ship AI and Data Science projects (that businesses actually want in 2026)?

On October 7th, I am hosting a free workshop to help you get started with AI + DS projects in Python.

Register here (500 seats): https://t.co/onpLpRwkzH

[Swaroop Kumar Yadav @S2SmeX]

One of the most underrated Youtube channel on VLSI.
there are a lot of lectures, discussing in depth even for a beginner. This is something worth trying.
https://t.co/g44VHSEZoA

[Naval @naval]

When you look back, you’ll wish you’d just done the long-term version of everything.

[Monica @monicaa_AI]

50 Sites That Show What Billionaires Buy and Read for Free🤯

1.) https://t.co/mvAFha3UcY → Current portfolios of famous investors
2.) https://t.co/VjOIL5Kj7A → Quarterly fund trades
3.) https://t.co/pyHuR5ONhD → Stock transactions of US politicians
4.) https://t.co/2L2KSsXhOR → Executives' own company stocks
5.) https://t.co/U0eklGHXcn → Making fund filings readable
6.) https://t.co/lrMexKysa4 → Companies' official reports
7.) https://t.co/w1Em8oLpKl → Buffett's letters since 1977
8.) https://t.co/ext9919w8f → Video archive of Buffett meetings
9.) https://t.co/f2BkyzJiGf → Howard Marks' investor memos
10.) https://t.co/Pp3n1W0if7 → Research from Ray Dalio's firm
11.) https://t.co/8L1ngcmpun → Dalio's principles for free
12.) https://t.co/dno7ADFdiF → Jeremy Grantham's market notes
13.) https://t.co/a8rXDzONYd → Quantitative fund research
14.) https://t.co/mAUpmSgjEX → Damodaran's valuation data
15.) https://t.co/KBUGehAISK → Valuation professor's blog
16.) https://t.co/6SMvHvJlsr → Morgan Housel's money writings
17.) https://t.co/NMqdV93mXJ → Mental models for decision-making
18.) https://t.co/px8LaAqr6D → JPMorgan's free market guide
19.) https://t.co/ek9boIMk0V → Innovation-focused fund research
20.) https://t.co/Z0uXDnZMSk → Venture capital essays
21.) https://t.co/GX9jOaFzG6 → Value investing lecture notes
22.) https://t.co/hxvNeFPJ8M → Columbia's value investing archive
23.) https://t.co/BafbVYJP4x → Fed's economic data archive
24.) https://t.co/hKNAg2TfFf → Fed decisions and statements
25.) https://t.co/bNBsCvLcZh → European Central Bank data
26.) https://t.co/DOfFtQZpGy → Reports from the central bank of central banks
27.) https://t.co/BNCg0sGiUT → Countries' economic indicators
28.) https://t.co/pXQ2FkAO7f → Companies' long-term charts
29.) https://t.co/dEgHv3yC3E → Company financials for free
30.) https://t.co/9ixwpGlIHT → Companies' market cap rankings
31.) https://t.co/7MqH62ojVK → Stock screener and heat map
32.) https://t.co/6IdMnRTpi7 → Portfolio backtesting
33.) https://t.co/3CZcOYGdXT → Charts and market analysis
34.) https://t.co/WbRaajTSo7 → Professional market screener
35.) https://t.co/yYXBrk2AHB → Company activity reports archive
36.) https://t.co/NtKuBPtENy → SEC's investor education site
37.) https://t.co/OkbIKghb5c → Passive investing encyclopedia
38.) https://t.co/KOdlzRNGH8 → Financial terms dictionary
39.) https://t.co/t6ETCJ4rWm → Free finance guides
40.) https://t.co/kDj8uBsVIR → CFA research publications
41.) https://t.co/npCqge3hok → Fund and stock evaluations
42.) https://t.co/sJfn3Flo4t → Companies' visual analysis
43.) https://t.co/c1INhDEcGY → Archive of selected investment theses
44.) https://t.co/6usagzjipB → Seeing what's inside funds
45.) https://t.co/WG6x4PmYuA → European fund backtests
46.) https://t.co/tMK10BK7xU → Investment writings with data
47.) https://t.co/dlhu9JPkmM → Market history notes
48.) https://t.co/fmp9hAQK64 → Investor psychology writings
49.) https://t.co/DMaTpZMCB3 → Explaining the economy with charts
50.) ourfiniteworld? → (see note)

The rich don't hoard information. They just don't tell you where it is.

Save it, follow @monicaa_AI you'll need it.
Not investment advice.

[Aakash Gupta @aakashgupta]

PM is now the slowest part of an AI-native team.
Here's how to run it with agents instead:

I've spent months building and testing PM loops in Claude Code. These are the 12 that earned a permanent spot, and the system they add up to.

1) Loops gather every signal

This is where most of your week goes today. Reading tickets. Chasing sales for deal notes.

Six loops take that over:

• Feedback digest: support tickets and interview notes, grouped into themes
• Deal intelligence: what sales won and lost last week, and why
• Competitive brief: what rivals shipped
• Metric anomaly flag: pings you the day a number moves
• Onboarding friction: where new users stall
• Customer call list: who changed behavior, with the outreach drafted

Most B2B PMs hear about deals once a quarter. With the deal loop, you hear on Monday.

2) One agent ranks, a second checks

A single agent ranking your backlog will confidently rank the wrong thing. So split the job. The maker ranks. The checker grades that ranking against your strategy doc. If it fails, it reruns before you ever see it.

3) Loops build the options

Tyler Folkman runs product, design and engineering at JobNimbus. His team runs a loop that builds divergent prototypes from their real component library. A synthetic customer, trained on call transcripts, reviews them first. By the time a human looks, the weak ones are gone.

4) A human picks one

Keep this out of the loop. Roadmap bets and stakeholder reads stay with you, because your head holds more context about the business than any AI setup.

What a loop can do is argue with you. A thinking-partner loop reads your doc and asks the annoying questions. Did you talk to customers? What breaks if you're wrong?

5) Loops build and measure

Your spec drift check pings eng's agent the moment the spec changes. Their nightly evals catch regressions. And your quality watchdog matters more every month: ship twice as fast at the same defect rate and your users see twice the bugs.

Every loop above has the same 6 pieces. A trigger, a skill file, a maker, a checker, a gate, a state file. Most people build the first three and then wonder why the output never gets better.

Two rules keep them alive:

• Never correct a loop in chat. Write the fix into the skill file, where it compounds.
• Retire any loop whose output you've stopped editing. Nobody is checking it anymore.

Start with the feedback digest. You'll feel it by Friday.

[Miles Deutscher @milesdeutscher]

Paste this prompt into Claude Code.

It will build you an Opus 5.5 + Jev trading bot.

It will probably make you a lot of money...

[Aakash Gupta @aakashgupta]

All PM candidates have resumes. Only 24% have a GitHub.

When I interviewed 10+ AI PM leaders at top companies, the hiring managers told me the same thing: if there's a GitHub linked, they will check it.

Shubham Saboo went from Dev Rel to senior AI PM at Google in 3 months. Google reached out because of his GitHub, and because of the way he shared his work on X.

You don't need one his size. PMs I placed at OpenAI, Anthropic and Meta AI all had GitHubs. None of them had 76K-star repos.

Build one small thing a week. A new prompt in your prompt library counts.

How to build yours:
https://t.co/U5X8U3Pqbs

[Polygon @0xPolygon]

Introducing stablecoin payments at checkout, now live in Polygon OMS.

Add ‘pay with crypto’ to the checkout you already run. Customers can pay across wallets, tokens, and chains without leaving your store to swap, bridge, or cash out.

[Jake Fitzgerald @earthtojake]

hacked together a CAD plugin extension for codex this afternoon

CAD + astra + plugin extensions are an insanely powerful combo, i've been waiting for the ability to extend codex's desktop app for a while

[Simplifying AI @simplifyinAI]

a full humanoid robot used to cost more than a car. berkeley just made one for under $5k.

berkeley humanoid lite changes everything:

> modular, 3d-printed gearboxes
> off-the-shelf hobby parts
> cad, firmware, and the full rl training stack included

a five-figure parts order becomes a weekend of printing.

that’s the difference between reading about humanoid robots and having one on your bench.

100% open-source.

[Founder Thoughts & Strategies @mogulinfluence]

This masterclass literally shows entrepreneurs how to use game theory to maximize success with minimum effort:

[How To Prompt @HowToPrompt__]

a dad in Nashville open-sourced a full home security system that runs 100% locally.

it's called Frigate, a AI-powered NVR that runs on your own hardware and does real-time object detection on any IP camera.

→ detects people, cars, animals, packages
→ 100+ detections per second
→ native home assistant integration

100% open source & free

[Steve @day25]

Still needs a little more work, but from a floorplan to being able to walk through the house in under 30 seconds is pretty magical.

[DevenSeenath @DevenSeenath]

this is boring, but it made me hella rich as a kid in my 20's

https://t.co/n6i5N8pQy5

[bodila @51bodila]

damn, send this 24/7 AI trading agent prompt to GPT 6.1 Sol

it will likely make you a lot of money...

Enjoy: