André Imbayago

Wild Cards vs High Potential 🤔

How it's supposed to be... 🍏 🔐

@chrisparkX A playground was needed. Hope it's a realistic sandbox to build on.

We’ve made major upgrades to X API: • Pay-Per-Use now GA worldwide • XMCP Server + xurl for agents • Official Python & TypeScript XDKs • API Playground - free realistic simulations New releases coming will be a game changer. Start building → docs.x.com 🚢

@ChiragSama9 @ShishirShelke1 Okay buddy

These images were shot on iPhone 17 Pro Max… WOW 🫪

LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So: Data ingest: I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them. IDE: I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides). Q&A: Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale. Output: Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base. Linting: I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into. Extra tools: I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries. Further explorations: As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows. TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

@MokoenaDee I giggled a bit on that part as well. The new sales pitch should be: Military grade encryption. Military grade disaster recovery. Military designed bunker AZ.

😂😂😂

@Leparagadi_Kego Bro:

Yesterday I heard my mom dissing my little brother's girlfriend 🤣🤣🤣 my dad joint and said 'ga ona leitlho bafana' 🤣😂 boy kept a straight face, walked out and while at the door he said 'yall chose each other, please let me be' 😭😭😭😂😂😂

@MokoenaDee You're right about IT & CyberSecurity contracts. AI contracts have entered the chat. 🤖

Tender mafias have entered IT and cybersecurity. Collecting contracts like infinity stones!! Award after award, yet the infrastructure looks like it’s held together by hope.

@jordan_ross_8F OPENCLAW

The founders who figure out OpenClaw in the next 90 days are going to look like geniuses in 2027. The problem is most agency owners don't have time to figure out the install, the security risks, where to start, or what to actually hand it first. So my team built a 48-page beginner's guide that does it for you. Inside: — The exact prompts to hand it on day one — Plain English setup for Mac and Windows — How to secure it so it doesn't burn your business down — 42 copy-paste workflows across sales, marketing, ops, and finance Your competitors are sleeping on this. Comment OPENCLAW and I'll send it.

@Lorato_Xaba 🍏

Which brand has your permanent loyalty?

@folaoftech Texas Insurance ❌ Texas Instruments ✅

She has no clue what her son is up to… honestly, I don't get it either.

@Mageba_wav 💪🏾🔥

Do you understand, like FULLY understand how huge of a flex this is?

@BellaBaddie__ "Save the cheerleader, save the world."

What was the first series you were completely addicted to? The series that paused everything?

@zwai_ndimba i’m upset knowing this.

Dear Devs, Please remind me on Monday to make a thread about a guy who made me write an entire full stack application for him, citing it was for a client and only to find out it was a KPI project for him at his job... Yhooo! I've never felt stupid like that, after finding out😭

Waking up to private statements about my private life 💔

@NoahKingJr 🥧

3.141592653589793238462643383279502884197169399375105820974944592307816406286 208998628034825342117067982148086513282306647093844609550582231725359408128481 117450284102701938521105559644622948954930381964428810975665933446128475648233 786783165271201909145648566923460348610454326648213393607260249141273724587006 606315588174881520920962829254091715364367892590360011330530548820466521384146 951941511609433057270365759591953092186117381932611793105118548074462379962749 567351885752724891227938183011949129833673362440656643086021394946395224737190 702179860943702770539217176293176752384674818467669405132000568127145263560827 785771342757789609173637178721468440901224953430146549585371050792279689258923 542019956112129021960864034418159813629774771309960518707211349999998372978049 951059731732816096318595024459455346908302642522308253344685035261931188171010 003137838752886587533208381420617177669147303598253490428755468731159562863882 353787593751957781857780532171226806613001927876611195909216420198938095257201 065485863278865936153381827968230301952035301852968995773622599413891249721775 283479131515574857242454150695950829533116861727855889075098381754637464939319 255060400927701671139009848824012858361603563707660104710181942955596198946767 837449448255379774726847104047534646208046684259069491293313677028989152104752 162056966024058038150193511253382430035587640247496473263914199272604269922796 782354781636009341721641219924586315030286182974555706749838505494588586926995 690927210797509302955321165344987202755960236480665499119881834797753566369807 426542527862551818417574672890977772793800081647060016145249192173217214772350 141441973568548161361157352552133475741849468438523323907394143334547762416862 518983569485562099219222184272550254256887671790494601653466804988627232791786 085784383827967976681454100953883786360950680064225125205117392984896084128488 626945604241965285022210661186306744278622039194945047123713786960956364371917 287467764657573962413890865832645995813390478027590099465764078951269468398352 595709825822620522489407726719478268482601476990902640136394437455305068203496 252451749399651431429809190659250937221696461515709858387410597885959772975498 930161753928468138268683868942774155991855925245953959431049972524680845987273 644695848653836736222626099124608051243884390451244136549762780797715691435997 700129616089441694868555848406353422072225828488648158456028506016842739452267202605414665925201497442850732518666002132434088190710486331734649651453905796 268561005508106658796998163574736384052571459102897064140110971206280439039759 515677157700420337869936007230558763176359421873125147120532928191826186125867 321579198414848829164470609575270695722091756711672291098169091528017350671274 858322287183520935396572512108357915136988209144421006751033467110314126711136 990865851639831501970165151168517143765761835155650884909989859982387345528331 635507647918535893226185489632132933089857064204675259070915481416549859461637 180270981994309924488957571282890592323326097299712084433573265489382391193259 746366730583604142813883032038249037589852437441702913276561809377344403070746 921120191302033038019762110110044929321516084244485963766983895228684783123552 658213144957685726243344189303968642624341077322697802807318915441101044682325 271620105265227211166039666557309254711055785376346682065310989

@awsdevelopers Dark Mode

say one nice thing about the AWS console