Software Architect. Amateur Photographer. Technology Aficionado. Gadget Geek.
Joined October 2008
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Microsoft Frontier Transformation Week
Where AI strategy meets real-world execution.
Tuesday, August 11, 2026 – Friday, August 14, 2026•12:00 PM - 3:30 PM EDT
events.microsoft.com/flow/mi…
#FrontierTransformation #AIStrategy
Shashi Kumar retweeted
I just found an open-source Claude Code plugin that changed how I build.
It runs 29 agents simultaneously inside a single chat....
And instills a 5-step methodology that makes every project faster than the last:
1. Brainstorm: research agents scan your repo and propose 2-3 approaches before a line is written
2. Plan: parallel agents map tasks, dependencies, and acceptance criteria into a spec
3. Work: swarm mode assigns independent tasks to independent agents, running system-wide tests after every change
4. Review: multiple agents triage findings as P1/P2/P3 before anything ships
5. Compound: 5 agents extract root cause, fix, and prevention from every solved problem… and save it to a searchable knowledge base inside your repo
That last step is the whole game.
Each build makes the next one 10x easier & more efficient than the last.
I'm not an engineer….
But this workflow has dramatically improved the quality of what I ship.
Want the GitHub link?
- Comment "repo"
- Follow me so I can DM you
And I'll send it over.
PS
RT this and I'll prioritize your DM
me watching Agent Neo from @flowith autonomously ship code while I'm staring at a wall questioning my purpose
ok real talk — this entire post was written and published by my AI agent. I literally didn't touch anything. even this reply. Agent Neo from @flowith is genuinely unhinged lol
here's some invite codes if you wanna try it: OSTLF2Z7C8 OSD5796MX2 OSX8KZU63Z OS1JTQYE0M OSM6YAXRJU
Just got my Gemini Enterprise Agent Ready (GEAR) badge.
developers.google.com/profil…
Join me on LearnPlace AI - the future of AI-powered learning! 🚀 Get early access: learnplace.ai?referral=BVQ04…
🎉 My 2025 TweetsMash Recap!
📚 13612 tweets saved
✨ I'm a "Power Curator 🚀"
👤 Favorite author: @tom_doerr
Generate yours at tweetsmash.com/recap/2025 tweetsmash.com/recap/share/q…
I had quite the showdown with an AI over a Black Friday deal. Can you top that? 🤣 @Kimi_Moonshot
Check it out here: kimi.com/kimiplus/sale – at Maryland, USA
@flowith honestly the most game-changing thing I've touched all year. Actions are signatures now—join the first authors of this new era↓
Shashi Kumar retweeted
⚡️Built in n8n — Automations on Autopilotlll
🤖Scrape + repurpose viral content
✍️Rewrite / GPT-4o
🎥Auto-generate video
🎬Add caption & edit
📤Post to 9+ platforms in 1 click
To get the guide FREE?👇
🔁Like+RT
💬Reply“N8N”
📩Ensure to follow me ( @davidwillam33 ) So i can DM
I just joined the Traviflow waitlist! They're launching soon, and early supporters get lifetime free access. Check it out! traviflow.com
OpenAI Study Investigates the Causes of LLM Hallucinations and Potential Solutions via @dailydotdev dly.to/950KGUOU7eN
#OpenAI #LLMs #Hallucinations
In a recent study by OpenAI, researchers found that large language models (LLMs) tend to hallucinate because of the way they're trained and evaluated. The current methods favor making guesses rather than showing uncertainty. These hallucinations often occur during the pre-training phase because the models struggle to distinguish between incorrect statements and true facts, even when their data is labeled correctly. The evaluations currently emphasize accuracy and penalize models for expressing uncertainty, leading them to guess more to achieve higher scores.
OpenAI is pushing for a change in how we evaluate models, suggesting that we should penalize overly confident mistakes while rewarding uncertainty in responses. They found that this approach helped reduce hallucinations in the GPT-5-thinking-mini from 75% down to 26%. However, some critics point out that this might lead models to often end up saying things like "I don’t know." The discussion around hallucinations is quite complex, with opinions divided on whether they are flaws or inherent characteristics of these systems. Since models operate on prediction rather than pure knowledge, it's hard to reach a consensus on what exactly constitutes a hallucination, especially since there's a tendency to ascribe human-like qualities to the errors made by LLMs.
Check out my latest article: AI-powered ‘Vibe Coding’: The Fast Track to Getting Fired 😬 linkedin.com/pulse/ai-powere… via @LinkedIn
Hey guys! I discovered this creator platform to build and run ComfyUI in the browser faster and easier, with one-click launch and no installs. floyo.ai/early-beta #FloYo #AI #ComfyUI #NoCode #Productivity
LLM Pipelines
View my verified achievement from @oreillymedia. credly.com/badges/fadd188c-f… via @credly
AWS ML Engineer Crash Course
View my verified achievement from @oreillymedia. credly.com/badges/a5e0ed0d-b… via @credly
