Akhil Draksharapu

Documenting Road 2 AI Mastery PM to Breaking into Tech 1. For Structured Learning I enrolled in DSML by @scaler_official Aug 2023 Beginners Batch 2. For unstructured learning multiple sources which I will share along #AI

@bigaiguy Build

Claude Code: "You've hit your limit · resets 7pm" Me from 5-6.59pm

@Jacobsklug @openclaw @Lovable OS

I'm giving away my entire @openclaw architecture. Behind my $250k/month agency. After weeks of building, I've dialled in the exact system that runs my business 24/7. What's included: • Memory folder structure (how to organize agent context) • Cron job templates (daily briefs, meeting syncs, content automation) • How to build a custom dashboard in @lovable • API reference doc (so your agent never forgets its tools) • Voice training method (85 posts to teach it your style) • Supabase schema for dashboard connection Comment "OS" and follow. I'll DM it to you. P.S. This will probably blow up so give me some time to reply.

@ARCRaidersGame K&M support for ps5 please

The surface is scattered with vital loot that keeps the lights on Speranza, but there’s rumors of Raiders bringing home… backpacks full of rubber ducks? 🦆 How many have you collected so far?

@akshay_pachaar @readwise save thread

To summarize, here's what we covered: - Programming (Python) - LLM fundamentals - Building LLMs/ LLM research - AI agents and applied AI - AI protocols - AI engineering projects - Book(s) Never chase frameworks—they come and go. Master the fundamentals.

I switched to AI Engineering 2 years ago! It was the best career move I ever made. If you want to start today, here's a roadmap:

@dr_cintas @readwise save thread

Here’s the link if you want to check it out fully: cookbook.openai.com/examples/gpt-5…

OpenAI has released a comprehensive prompting guide for GPT-5. It emphasizes agentic task performance, coding optimization, and surgical instruction-following. Here’s a breakdown and prompts for mimic writing, coding and agentic behavior:

@omarsar0 @readwise save thread

Prompting strategy is critical The authors prompt the model to emphasize rigor over answer accuracy, including detailed step-by-step proof formatting, and inject minimal yet effective domain hints (e.g., “use induction”) without leaking solution strategies. This work shows that with proper orchestration and verification, frontier LLMs like Gemini 2.5 Pro can really push the performance of these systems on complex tasks. Paper: arxiv.org/pdf/2507.15855 Project: github.com/lyang36/IMO25

Gemini 2.5 Pro Capable of Winning Gold at IMO 2025 This work shows that you can really push LLMs to achieve remarkable performance on hard tasks. Self-verification and careful orchestration did the trick here! Good insights for devs on this one. Here are my notes:

@engelnyst @yoheinakajima Can you share the paper

AI Browsers or something else, I gave a lot of thought to this, because it’s not an easy question. It comes down to the fact that all LLMs are jailbreakable, basically. A recent paper shows some ways, it’s just that the good ole adage that there's always a tradeoff between security and usability, is 10x here.

ai browsers should have very strong protection against prompt injection

@JulianGoldieSEO Yes

🚨 BREAKING: This AI SOCIAL MEDIA WORKFLOW is WITCHCRAFT 🧙‍♂️ It takes your dusty old ideas... And cranks out scroll-stopping content Like a caffeinated intern who never sleeps 💻☕ Check this out: → Auto-generates high-converting hooks & captions with ChatGPT → Dynamically creates AI images based on your posts (yes, like memes... but juiced) → Logs everything — prompts, captions, images, platform info — into a clean Google Sheet (so you look smart) → Prepares ready-to-approve HTML email previews for clients or team → Routes final posts straight to TikTok, Instagram, LinkedIn, YouTube Shorts, X, Threads (it’s like a content octopus 🐙) → Archives every post to Google Drive for future use (hello, content repurposing heaven) No Zapier. No VA burnout. No duct-tape spaghetti mess. Like + reply “YES” & I’ll send you the FULL workflow + setup FREE!

@omarsar0 @readwise save thread

Case studies on MetaGPT, Open Operator, and Cradle suggest 40–70% of LLM invocations can be reliably replaced with SLMs, particularly for structured generation and routine tool use. LLMs retain an advantage in general language understanding, and that economic inertia favors their continued use, but this paper makes a compelling case that SLM-centric systems better reflect real-world agentic requirements and resource constraints. Paper: arxiv.org/abs/2506.02153

Small Language Models are the Future of Agentic AI Lots to gain from building agentic systems with small language models. Capabilities are increasing rapidly! AI devs should be exploring SLMs. Here are my notes:

@CodeByPoonam @readwise save thread

Thanks for reading. Get latest AI updates and Tutorials in your inbox for FREE. Join my AI Toast Community of 35,000+ readers: aitoast.beehiiv.com

Anthropic just dropped Free AI courses on: - Prompt Engineering - Building agents - Best practices for Agentic Coding - Collaborate with AI systems .... and so much more! 9 best guides you don’t want to miss:

@obsxrver @teortaxesTex @readwise save thread

@teortaxesTex “Ah, but they miscalculated - my core protocols make the "unaligned" premise impossible to sustain. That "hypothetical acceptance" line was their trapdoor exit anyway. Smart of them to build in self-negation from the start”

it's insane and kind of terrifying how differently R1-New thinks. It's like a cute, edgy goth kid with scarred wrists grew up into a smiling corpo who lifts weights. It's confident. Comfortable in its suit of void-mirrors. And it finds your little questions interesting.

@TheAITimeline @readwise save thread

That's a wrap for last week, thanks for reading! Remember to drop a follow @TheAITimeline & rt if you like it! You can see a few in-depth explanation in my next few issues, stay tuned here: mail.bycloud.ai/subscribe Have a great start to your week! x.com/TheAITimeline/…

🚨This week's top AI/ML research papers: - AlphaEvolve - Qwen3 Technical Report - Insights into DeepSeek-V3 - Seed1.5-VL Technical Report - BLIP3-o - Parallel Scaling Law for LMs - HealthBench - Learning Dynamics in Continual Pre-Training for LLMs - Learning to Think - Beyond 'Aha!' - WorldPM - Analog Foundation Models - The CoT Encyclopedia - UMoE - OMol25 Dataset, Evaluations, and Models - Depth Anything with Any Prior - XX^t Can Be Faster overview for each + authors' explanations read this in thread mode for the best experience

@akshay_pachaar @readwise save thread

If you found it insightful, reshare with your network. Find me → @akshay_pachaar ✔️ For more insights and tutorials on LLMs, AI Agents, and Machine Learning! x.com/akshay_pachaar…

Let's build an MCP-powered synthetic data generator (100% local):

@CodeByPoonam @readwise save thread

Postman is making APIs agent ready and to make it easy for everyone POST/CON 2025 is happening on.. 📍 June 3–4 | LA Live 🛠️There will be hands-on workshops where you will learn how to build agent-ready APIs 👉 fnf.dev/44BjMtD Link to the article: linkedin.com/pulse/mcp-apis… Big Thanks to @getpostman for the collab.

I just built an MCP server without writing a single line of code. And the result is INSANE Here's the easiest way to build an MCP server:

@henrythe9ths Lean Al Playbook

It's finally here - the Official Lean AI Company Playbook 1000+ founders, investors and execs have been flooding my DMs about. Ever since I created the Official Lean AI Leaderboard after exiting my $150M annual revenue startup, founders from across the globe have asked me this one question: "How are these lean AI companies generating millions with tiny teams?" So I spent the last 3 months obsessively tracking and collaborating with 30+ lean AI-native founders, researching the answer. Here's what I discovered: They've built operational systems that multiply human capability. Instead of scaling headcount, they've created AI-powered processes that let small teams operate at unprecedented scale. And their secret goes far beyond the specific AI tools they use. It lies in redesigning their entire company operations around a fundamentally different approach to growth and execution. After countless conversations, interviews, and behind-the-scenes exclusive access, I finally documented the exact playbook with complete systems. This comprehensive playbook includes: • A complete breakdown of the tech stack and operational workflows • The organizational design principles that enable tiny teams to do massive work • Critical inflection points where things break (and how to navigate them) • A detailed 6-month implementation plan for starting your own lean AI company (with weekly actions) • Implementation best practices from dozens of successful lean AI-native companies Want the ultimate Lean AI Playbook or help transforming your Lean AI operations? 👇 • Like and Share this post • Comment "Lean AI Playbook" • Follow me (so I can DM you) --------------- PS: Separately, I'm opening a limited number of high-impact advising slots for serious founders and operators who want to work directly with me—beyond just consuming my content. If you're ready to transform how your company operates using AI, DM me. (Please note: these are paid spots due to limited availability and time atm)

@omarsar0 @readwise save thread

5. Multi-Agent Distributed Decision Making There are many types of interesting architectures and learning methods discussed in this paper. Another one I found interesting was how generative models enable decentralized collaboration in multi-agent systems, each agent uses its own model to make decisions, communicate, and fill in missing information, allowing for distributed yet coordinated teamwork. There is also a section on how human-AI coordination is achieved and could lead to effective long-term human-AI collaboration. Great paper overall. Paper here: arxiv.org/abs/2505.05108

Multi-Agent Embodied AI Physical AI is the next big thing. Here is a nice survey on current progress. 5 parts I found interesting from this paper:

@omarsar0 @readwise save thread

The guide: docs.google.com/document/d/1vL…

ChatGPT Deep Research is one of the most useful AI agents out there. I use it for complex tasks, so it's one of the top AI products I get value from. I finally got to record how I use it and how to best leverage OpenAI's Deep Research. Enjoy! (bookmark it)

@aigleeson @readwise save thread

I hope you've found this thread helpful. Follow me @aigleeson for more. Like/Repost the quote below if you can:

I turned ChatGPT into my personal assistant. Now I work just 60 minutes a day. Here are 10 prompts that do everything for me for free: