[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.] #  @omarsar0 elvis elvis posts on X about context engineering, llm, devs, agentic the most. They currently have XXXXXXX followers and XX posts still getting attention that total XXXXXX engagements in the last XX hours. ### Engagements: XXXXXX [#](/creator/twitter::3448284313/interactions)  - X Week XXXXXXX -XX% - X Month XXXXXXXXX -XXXX% - X Months XXXXXXXXXX +53% - X Year XXXXXXXXXX +110% ### Mentions: XX [#](/creator/twitter::3448284313/posts_active)  - X Week XX -XX% - X Month XXX +23% - X Months XXX +7.40% - X Year XXX +207% ### Followers: XXXXXXX [#](/creator/twitter::3448284313/followers)  - X Week XXXXXXX +0.44% - X Month XXXXXXX +1.90% - X Months XXXXXXX +14% - X Year XXXXXXX +29% ### CreatorRank: XXXXXXX [#](/creator/twitter::3448284313/influencer_rank)  ### Social Influence [#](/creator/twitter::3448284313/influence) --- **Social category influence** [musicians](/list/musicians) XX% [stocks](/list/stocks) X% [technology brands](/list/technology-brands) X% **Social topic influence** [context engineering](/topic/context-engineering) #12, [llm](/topic/llm) 8%, [devs](/topic/devs) #99, [agentic](/topic/agentic) 6.67%, [grok 4](/topic/grok-4) 5.33%, [$googl](/topic/$googl) #966, [realtime](/topic/realtime) 4%, [accuracy](/topic/accuracy) 4%, [capabilities](/topic/capabilities) 4%, [xai](/topic/xai) XXXX% **Top accounts mentioned or mentioned by** [@grok](/creator/undefined) [@elieso619](/creator/undefined) [@adamdittrichone](/creator/undefined) [@trakintelai](/creator/undefined) [@rungalileo](/creator/undefined) [@windsurfai](/creator/undefined) [@anthropicai](/creator/undefined) [@dairai](/creator/undefined) [@llmsan](/creator/undefined) [@divyankb1805](/creator/undefined) [@alessiocarra_](/creator/undefined) [@ahmedrezat](/creator/undefined) [@arindam_1729](/creator/undefined) [@codezera11](/creator/undefined) [@gokulprdeep](/creator/undefined) [@thetetherman](/creator/undefined) [@kaousnadirhatem](/creator/undefined) [@sarthaksharma85](/creator/undefined) [@kybervaul](/creator/undefined) [@chibichaddeus](/creator/undefined) **Top assets mentioned** [Alphabet Inc Class A (GOOGL)](/topic/$googl) ### Top Social Posts [#](/creator/twitter::3448284313/posts) --- Top posts by engagements in the last XX hours "Grok X on Vending Bench Grok X gets the #1 spot. Double the net worth of Claude Opus 4"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1943170235789398331) 2025-07-10 04:47:41 UTC 256K followers, 42K engagements "Learning without training Google researchers explore the implicit dynamics of in-context learning. "Implicit weight updates from ICL mirror the effect of actual fine-tuning on the same data." This one is more technical but much needed. The findings:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1948384435654779105) 2025-07-24 14:07:03 UTC 256.1K followers, 98.4K engagements "AI Research Agents for ML Achieves state-of-the-art on MLE-bench lite Using AI to automate the training of ML models is one of the most exciting and promising areas of research today. Lots of cool ideas in this paper:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1942235421607682317) 2025-07-07 14:53:04 UTC 256K followers, 41.7K engagements "Anthropic is killing it with these technical posts. If you're an AI dev stop what you are doing and go read this. It shows in great detail how to implement an effective multi-agent research system. Pay attention to these key parts:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1933941545675206936) 2025-06-14 17:36:10 UTC 256K followers, 570.7K engagements "Agent Leaderboard v2 is here GPT-4.1 leads Gemini-2.5-flash excels at tool selection Kimi K2 is the top open-source model Grok X falls short Reasoning models lag behind No single model dominates all domains More below:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1945956442785083895) 2025-07-17 21:19:04 UTC 256K followers, 273.6K engagements "Agentic RAG for Personalized Recommendation This is a really good example of integrating agentic reasoning into RAG. Leads to better personalization and improved recommendations. Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1941957079331377475) 2025-07-06 20:27:02 UTC 255.8K followers, 92.6K engagements "Context engineering components include context retrieval and generation context processing context management and how they are all integrated into systems implementation such as RAG memory architectures tool-integrated reasoning and multi-agent coordination mechanisms"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241627582054854) 2025-07-18 16:12:18 UTC 256K followers, 5996 engagements "Assisted Remediation Categorization of LLM-enabled assisted remediation tasks in AIOps by increasing levels of automation. Tasks range from assisted questioning to mitigation solution generation command recommendation script generation and finally automatic execution. This highlights how LLMs progressively reduce human intervention in operational workflows"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946997367439499348) 2025-07-20 18:15:20 UTC 256K followers, 1533 engagements "Traditional agent planning approaches often fail in enterprise scenarios due to unstructured plans weak instruction following and tool selection errors. Routine provides a clear and modular format for LLM agents to follow multi-step plans reducing ambiguity and improving tool selection. Each step contains a step number name detailed description and (optionally) inputs outputs and tool to be called"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947750788752937174) 2025-07-22 20:09:10 UTC 256K followers, 1132 engagements "BREAKING: xAI announces Grok X "It can reason at a superhuman level" Here is everything you need to know:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1943162144930828397) 2025-07-10 04:15:32 UTC 256K followers, 1.3M engagements "Grok X models are available via the xAI API. 256K context window. Real-time data search"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1943170665005134308) 2025-07-10 04:49:23 UTC 255.9K followers, 27.6K engagements "Top XX LLM Interview Questions. Looks like a great resource to learn LLM basics:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1930984834454712537) 2025-06-06 13:47:15 UTC 256K followers, 355.1K engagements "Inference-time tricks fail to help CoT prompting and majority voting do not reliably reduce vulnerability and sometimes make FPR worse especially for Qwen models on math tasks. LLMs continue to show all kinds of weird vulnerabilities and this is just one of the latest results to be published. This highlights the importance of building robust LLM-based evaluation strategies. Paper:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1944778251064496579) 2025-07-14 15:17:21 UTC 256K followers, 5259 engagements "MemAgent MemAgent-14B is trained on 32K-length documents with an 8K context window. Achieves XX% accuracy even at 3.5M tokens That consistency is crazy Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1942667308368871457) 2025-07-08 19:29:13 UTC 256.1K followers, 100.6K engagements "Stress Testing Large Reasoning Models This looks like a more interesting way to evaluate large reasoning models. Presents multiple reasoning problems in a single prompt to better represent real-world scenarios. Which are the best models at this Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1945150414195974448) 2025-07-15 15:56:12 UTC 256K followers, 17.6K engagements "A Structural Planning Framework for LLM Agent System in Enterprise Agentic systems for enterprise are a work in progress. Reliability is a real problem. No secret that planning works but structural planning can further help improve the reliability of AI agents. My notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947750756494586275) 2025-07-22 20:09:02 UTC 256.1K followers, 29.9K engagements "The Illusion of Thinking in LLMs Apple researchers discuss the strengths and limitations of reasoning models. Apparently reasoning models "collapse" beyond certain task complexities. Lots of important insights on this one. (bookmark it) Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1931333830985883888) 2025-06-07 12:54:02 UTC 256.1K followers, 954.2K engagements "Excited to announce my new short course: Building Agentic Applications with Replit Agent and n8n. With AI this capable I believe anyone can become a builder. The stack I use here will teach you how to rapidly build agentic apps with no-code tools"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1943410079199629470) 2025-07-10 20:40:44 UTC 256K followers, 42.1K engagements "Evaluating LLM-based Agents This report has a comprehensive list of methods for evaluating AI Agents. Don't ignore evals. If done right they are a game-changer. Highly recommend it to AI devs. (bookmark it)"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1939691782477902313) 2025-06-30 14:25:33 UTC 256K followers, 96.1K engagements "YC on the key prompting techniques used by the best AI startups:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1928562249297211600) 2025-05-30 21:20:45 UTC 256K followers, 665.9K engagements "One Token to Fool LLM-as-a-Judge Watch out for this one devs Semantically empty tokens like Thought process: Solution or even just a colon : can consistently trick models into giving false positive rewards. Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1944778174493343771) 2025-07-14 15:17:03 UTC 256.1K followers, 97.8K engagements "Deep Research Agents with Test-Time Diffusion Google keeps pushing on diffusion. This time they apply diffusion to deep research agents specifically the report generation process. It achieves a XXXX% win rate vs. OpenAI Deep Research on long-form research. My notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1948021797380861984) 2025-07-23 14:06:03 UTC 256.1K followers, 76K engagements "Emerging evaluation strategies Beyond traditional metrics (precision F1 RMSE) the field has adopted generation metrics (BLEU BERTScore) execution metrics (e.g. success rates of generated scripts) and manual evaluation (qualitative grading human preference) to assess tasks like script generation or report explanation"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946997399127482526) 2025-07-20 18:15:28 UTC 256K followers, 6005 engagements "Context engineering is going to evolve rapidly. But this is a great overview to better map and keep track of this rapidly evolving landscape. There is a lot more in the paper. Over 1000+ references included. This survey tries to capture the most common methods and biggest trends but there is more on the horizon as models continue to improve in capability and new agent architectures emerge"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241716467716455) 2025-07-18 16:12:39 UTC 256K followers, 7425 engagements "I started to experiment with Grok X and I already found some interesting things about it. I'm preparing a detailed comparison with other reasoning models. I will be hosting a workshop on Grok X for our academy members soon:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1943303408175267903) 2025-07-10 13:36:51 UTC 256K followers, 13K engagements "The paper provides a taxonomy of context engineering in LLMs categorized into foundational components system implementations evaluation methodologies and future directions"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241581415272904) 2025-07-18 16:12:07 UTC 256K followers, 7756 engagements "A Survey of Context Engineering 160+ pages covering the most important research around context engineering for LLMs. This is a must-read Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241565728600503) 2025-07-18 16:12:03 UTC 256.1K followers, 198.9K engagements "i am at the point where my ai agents have become so good and fast at various complex tasks that i've become the bottleneck hard to make use of and keep track of all the insane value my ai agents are creating ai agent managers are going to be in high demand soon"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1948490601164316891) 2025-07-24 21:08:55 UTC 256.1K followers, 12.1K engagements "AI for Scientific Search AI for Science is where I spend most of my time exploring with AI agents. This 120+ pages report does a good job of highlighting why all the big names like OpenAI and Google DeepMind are pursuing AI4Science. Bookmark it My notes below:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1940787135596187970) 2025-07-03 14:58:05 UTC 256K followers, 61.8K engagements "Context Rot Great title for a report but even better insights about how increasing input tokens impact the performance of top LLMs. Banger report from Chroma. Here are my takeaways (relevant for AI devs):"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946607725796045287) 2025-07-19 16:27:02 UTC 256.1K followers, 169.8K engagements "Future of Work with AI Agents Stanford's new report analyzes what 1500 workers think about working with AI Agents. What types of AI Agents should we build A few surprises Let's take a closer look:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1936134951520682123) 2025-06-20 18:51:58 UTC 256.1K followers, 301.1K engagements "The framework separates planning (with LLMs) from execution (with small instruction-tuned models) using Routine as the bridge. This enables small-scale models to reliably execute complex plans with minimal resource overhead especially when using variable memory and modular tools like MCP server"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947750820403175918) 2025-07-22 20:09:17 UTC 256K followers, XXX engagements "Thoughts after coding relentlessly with tools like Replit Agent and Claude Code for the past few days: Current coding models are more impressive that we all think. Clever memory management search and context engineering is whats falling short. Tool calling also needs more work but thats improving fast with these new models. Spend the time preparing context (eg. design mockups and complete error logs) and you will be iterating less on building new features see less mistakes and get a lot more done with vibe coding"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947859083702239314) 2025-07-23 03:19:29 UTC 256.1K followers, 10.6K engagements "An ablation study shows the importance of explicitly including tool names and I/O descriptions in Routine steps. Removing tool names dropped Qwen3-14Bs accuracy from XXXX% to 71.9%. Adding I/O fields provided minor gains especially for less capable models"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947750835334877352) 2025-07-22 20:09:21 UTC 256K followers, XXX engagements "What comes after Cursor This new agentic IDE Kiro offers a glimpse at that future. Kiro comes with all the fun features in an agentic IDE deliberate planning and leverages ambient agents that autonmously collaborate with devs as they build production-grade systems"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1945134066551980278) 2025-07-15 14:51:14 UTC 255.9K followers, 47K engagements "So tired of seeing these agentic systems used for booking travel. The real deal is AI agents for scientific discovery. Were getting close and not just LLM providers. If you can build reliable agentic systems you can be part of the race. Saying no more but watch this space"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946738268881514899) 2025-07-20 01:05:46 UTC 256K followers, 14.2K engagements "Agentic-R1 This 7B model is surprisingly good at interleaved tool use and reasoning capabilities. It's fun to see small language models improving this fast. Knowledge distillation in full display. Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1945863581918257591) 2025-07-17 15:10:04 UTC 256K followers, 62K engagements "LLMs Get Lost in Multi-turn Conversation The cat is out of the bag. Pay attention devs. This is one of the most common issues when building with LLMs today. Glad there is now paper to share insights. Here are my notes:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1922755721428598988) 2025-05-14 20:47:41 UTC 256.1K followers, 759.3K engagements "Every AI dev should know how to apply everything on this list. From prompting tips to context engineering to metaprompting. Learn it once apply it everywhere. Check out my new 4+ hrs course (with code examples) to learn more:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1938602425386152296) 2025-06-27 14:16:50 UTC 255.9K followers, 49.3K engagements "The work distinguishes prompt engineering from context engineering on dimensions like state scalability error analysis complexity etc"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241611903762897) 2025-07-18 16:12:14 UTC 256K followers, 6186 engagements "Tool-calling capabilities in an area of continuous development in the space. The paper provides an overview of tool-augmented language model architectures and how they compare across tool categories"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241703893189017) 2025-07-18 16:12:36 UTC 255.9K followers, 4107 engagements "This handbook is so good It covers *everything* you need to know about LLM inference. FREE to access:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1943727674637033601) 2025-07-11 17:42:45 UTC 256.1K followers, 85.9K engagements "Much is being said about context engineering but I want to focus on building. Find the full guide here: I am also hosting a workshop on "Context Engineering for AI Agents" for our academy pro members:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1941566134911963231) 2025-07-05 18:33:33 UTC 255.9K followers, 16.7K engagements "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:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1940038438746718698) 2025-07-01 13:23:02 UTC 256K followers, 267.6K engagements "Context Engineering Guide I'm writing a detailed guide on context engineering for AI devs. v1 is out now (bookmark it) I use a concrete deep research multi-agent example to show what context engineering involves"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1941566132001153082) 2025-07-05 18:33:33 UTC 256.1K followers, 289.8K engagements "Whats Hud A lightweight Runtime Code Sensor that installs in X min. No config. No dashboards. No tracing. Just real-time visibility into: Performance Errors Flows Function paths Dependencies All directly in your AI tools"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947288030706077822) 2025-07-21 13:30:20 UTC 255.8K followers, XXX engagements "Context Engineering Guide is now part of the Prompt Engineering Guide. 🔥 Nicer format. We've also been writing guides on other fire topics such as deep research reasoning LLMs and image generation. I will be expanding the guide further in the coming days. Stay tuned"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1942581621171105820) 2025-07-08 13:48:44 UTC 256K followers, 36.1K engagements "The context engineering evolution timeline from 2020 to 2025 involves foundational RAG systems to complex multi-agent architectures"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241597148123515) 2025-07-18 16:12:10 UTC 256K followers, 7225 engagements "In a real HR agent scenario with X multi-step workflows adding Routine increased GPT-4os accuracy from XXXX% to XXXX% and Qwen3-14Bs from XXXX% to 83.3%. Fine-tuning Qwen3-14B on a Routine-following dataset further increased accuracy to 88.2%; training on a Routine-distilled dataset reached 95.5%"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1947750804376719447) 2025-07-22 20:09:13 UTC 256K followers, 1112 engagements "Challenges & Future Work Challenges for future research include reducing LLM cost/latency (especially for real-time tasks) leveraging underused data like traces improving model adaptability to software evolution and integrating LLMs with existing AIOps toolchains instead of replacing them. Paper:"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946997411471323336) 2025-07-20 18:15:31 UTC 255.8K followers, 5659 engagements "You can read the full paper below: Want to take it a step further Learn about context engineering and how to build effective agentic systems in my courses: We also have a workshop on context engineering coming soon"  [@omarsar0](/creator/x/omarsar0) on [X](/post/tweet/1946241728316653990) 2025-07-18 16:12:42 UTC 256K followers, 7601 engagements
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
@omarsar0 elvis
elvis posts on X about context engineering, llm, devs, agentic the most. They currently have XXXXXXX followers and XX posts still getting attention that total XXXXXX engagements in the last XX hours.
Engagements: XXXXXX #
- X Week XXXXXXX -XX%
- X Month XXXXXXXXX -XXXX%
- X Months XXXXXXXXXX +53%
- X Year XXXXXXXXXX +110%
Mentions: XX #
- X Week XX -XX%
- X Month XXX +23%
- X Months XXX +7.40%
- X Year XXX +207%
Followers: XXXXXXX #
- X Week XXXXXXX +0.44%
- X Month XXXXXXX +1.90%
- X Months XXXXXXX +14%
- X Year XXXXXXX +29%
CreatorRank: XXXXXXX #
Social Influence #
Social category influence musicians XX% stocks X% technology brands X%
Social topic influence context engineering #12, llm 8%, devs #99, agentic 6.67%, grok 4 5.33%, $googl #966, realtime 4%, accuracy 4%, capabilities 4%, xai XXXX%
Top accounts mentioned or mentioned by @grok @elieso619 @adamdittrichone @trakintelai @rungalileo @windsurfai @anthropicai @dairai @llmsan @divyankb1805 @alessiocarra_ @ahmedrezat @arindam_1729 @codezera11 @gokulprdeep @thetetherman @kaousnadirhatem @sarthaksharma85 @kybervaul @chibichaddeus
Top assets mentioned Alphabet Inc Class A (GOOGL)
Top Social Posts #
Top posts by engagements in the last XX hours
"Grok X on Vending Bench Grok X gets the #1 spot. Double the net worth of Claude Opus 4"
@omarsar0 on X 2025-07-10 04:47:41 UTC 256K followers, 42K engagements
"Learning without training Google researchers explore the implicit dynamics of in-context learning. "Implicit weight updates from ICL mirror the effect of actual fine-tuning on the same data." This one is more technical but much needed. The findings:" @omarsar0 on X 2025-07-24 14:07:03 UTC 256.1K followers, 98.4K engagements
"AI Research Agents for ML Achieves state-of-the-art on MLE-bench lite Using AI to automate the training of ML models is one of the most exciting and promising areas of research today. Lots of cool ideas in this paper:" @omarsar0 on X 2025-07-07 14:53:04 UTC 256K followers, 41.7K engagements
"Anthropic is killing it with these technical posts. If you're an AI dev stop what you are doing and go read this. It shows in great detail how to implement an effective multi-agent research system. Pay attention to these key parts:" @omarsar0 on X 2025-06-14 17:36:10 UTC 256K followers, 570.7K engagements
"Agent Leaderboard v2 is here GPT-4.1 leads Gemini-2.5-flash excels at tool selection Kimi K2 is the top open-source model Grok X falls short Reasoning models lag behind No single model dominates all domains More below:" @omarsar0 on X 2025-07-17 21:19:04 UTC 256K followers, 273.6K engagements
"Agentic RAG for Personalized Recommendation This is a really good example of integrating agentic reasoning into RAG. Leads to better personalization and improved recommendations. Here are my notes:" @omarsar0 on X 2025-07-06 20:27:02 UTC 255.8K followers, 92.6K engagements
"Context engineering components include context retrieval and generation context processing context management and how they are all integrated into systems implementation such as RAG memory architectures tool-integrated reasoning and multi-agent coordination mechanisms" @omarsar0 on X 2025-07-18 16:12:18 UTC 256K followers, 5996 engagements
"Assisted Remediation Categorization of LLM-enabled assisted remediation tasks in AIOps by increasing levels of automation. Tasks range from assisted questioning to mitigation solution generation command recommendation script generation and finally automatic execution. This highlights how LLMs progressively reduce human intervention in operational workflows" @omarsar0 on X 2025-07-20 18:15:20 UTC 256K followers, 1533 engagements
"Traditional agent planning approaches often fail in enterprise scenarios due to unstructured plans weak instruction following and tool selection errors. Routine provides a clear and modular format for LLM agents to follow multi-step plans reducing ambiguity and improving tool selection. Each step contains a step number name detailed description and (optionally) inputs outputs and tool to be called" @omarsar0 on X 2025-07-22 20:09:10 UTC 256K followers, 1132 engagements
"BREAKING: xAI announces Grok X "It can reason at a superhuman level" Here is everything you need to know:" @omarsar0 on X 2025-07-10 04:15:32 UTC 256K followers, 1.3M engagements
"Grok X models are available via the xAI API. 256K context window. Real-time data search" @omarsar0 on X 2025-07-10 04:49:23 UTC 255.9K followers, 27.6K engagements
"Top XX LLM Interview Questions. Looks like a great resource to learn LLM basics:" @omarsar0 on X 2025-06-06 13:47:15 UTC 256K followers, 355.1K engagements
"Inference-time tricks fail to help CoT prompting and majority voting do not reliably reduce vulnerability and sometimes make FPR worse especially for Qwen models on math tasks. LLMs continue to show all kinds of weird vulnerabilities and this is just one of the latest results to be published. This highlights the importance of building robust LLM-based evaluation strategies. Paper:" @omarsar0 on X 2025-07-14 15:17:21 UTC 256K followers, 5259 engagements
"MemAgent MemAgent-14B is trained on 32K-length documents with an 8K context window. Achieves XX% accuracy even at 3.5M tokens That consistency is crazy Here are my notes:" @omarsar0 on X 2025-07-08 19:29:13 UTC 256.1K followers, 100.6K engagements
"Stress Testing Large Reasoning Models This looks like a more interesting way to evaluate large reasoning models. Presents multiple reasoning problems in a single prompt to better represent real-world scenarios. Which are the best models at this Here are my notes:" @omarsar0 on X 2025-07-15 15:56:12 UTC 256K followers, 17.6K engagements
"A Structural Planning Framework for LLM Agent System in Enterprise Agentic systems for enterprise are a work in progress. Reliability is a real problem. No secret that planning works but structural planning can further help improve the reliability of AI agents. My notes:" @omarsar0 on X 2025-07-22 20:09:02 UTC 256.1K followers, 29.9K engagements
"The Illusion of Thinking in LLMs Apple researchers discuss the strengths and limitations of reasoning models. Apparently reasoning models "collapse" beyond certain task complexities. Lots of important insights on this one. (bookmark it) Here are my notes:" @omarsar0 on X 2025-06-07 12:54:02 UTC 256.1K followers, 954.2K engagements
"Excited to announce my new short course: Building Agentic Applications with Replit Agent and n8n. With AI this capable I believe anyone can become a builder. The stack I use here will teach you how to rapidly build agentic apps with no-code tools" @omarsar0 on X 2025-07-10 20:40:44 UTC 256K followers, 42.1K engagements
"Evaluating LLM-based Agents This report has a comprehensive list of methods for evaluating AI Agents. Don't ignore evals. If done right they are a game-changer. Highly recommend it to AI devs. (bookmark it)" @omarsar0 on X 2025-06-30 14:25:33 UTC 256K followers, 96.1K engagements
"YC on the key prompting techniques used by the best AI startups:" @omarsar0 on X 2025-05-30 21:20:45 UTC 256K followers, 665.9K engagements
"One Token to Fool LLM-as-a-Judge Watch out for this one devs Semantically empty tokens like Thought process: Solution or even just a colon : can consistently trick models into giving false positive rewards. Here are my notes:" @omarsar0 on X 2025-07-14 15:17:03 UTC 256.1K followers, 97.8K engagements
"Deep Research Agents with Test-Time Diffusion Google keeps pushing on diffusion. This time they apply diffusion to deep research agents specifically the report generation process. It achieves a XXXX% win rate vs. OpenAI Deep Research on long-form research. My notes:" @omarsar0 on X 2025-07-23 14:06:03 UTC 256.1K followers, 76K engagements
"Emerging evaluation strategies Beyond traditional metrics (precision F1 RMSE) the field has adopted generation metrics (BLEU BERTScore) execution metrics (e.g. success rates of generated scripts) and manual evaluation (qualitative grading human preference) to assess tasks like script generation or report explanation" @omarsar0 on X 2025-07-20 18:15:28 UTC 256K followers, 6005 engagements
"Context engineering is going to evolve rapidly. But this is a great overview to better map and keep track of this rapidly evolving landscape. There is a lot more in the paper. Over 1000+ references included. This survey tries to capture the most common methods and biggest trends but there is more on the horizon as models continue to improve in capability and new agent architectures emerge" @omarsar0 on X 2025-07-18 16:12:39 UTC 256K followers, 7425 engagements
"I started to experiment with Grok X and I already found some interesting things about it. I'm preparing a detailed comparison with other reasoning models. I will be hosting a workshop on Grok X for our academy members soon:" @omarsar0 on X 2025-07-10 13:36:51 UTC 256K followers, 13K engagements
"The paper provides a taxonomy of context engineering in LLMs categorized into foundational components system implementations evaluation methodologies and future directions" @omarsar0 on X 2025-07-18 16:12:07 UTC 256K followers, 7756 engagements
"A Survey of Context Engineering 160+ pages covering the most important research around context engineering for LLMs. This is a must-read Here are my notes:" @omarsar0 on X 2025-07-18 16:12:03 UTC 256.1K followers, 198.9K engagements
"i am at the point where my ai agents have become so good and fast at various complex tasks that i've become the bottleneck hard to make use of and keep track of all the insane value my ai agents are creating ai agent managers are going to be in high demand soon" @omarsar0 on X 2025-07-24 21:08:55 UTC 256.1K followers, 12.1K engagements
"AI for Scientific Search AI for Science is where I spend most of my time exploring with AI agents. This 120+ pages report does a good job of highlighting why all the big names like OpenAI and Google DeepMind are pursuing AI4Science. Bookmark it My notes below:" @omarsar0 on X 2025-07-03 14:58:05 UTC 256K followers, 61.8K engagements
"Context Rot Great title for a report but even better insights about how increasing input tokens impact the performance of top LLMs. Banger report from Chroma. Here are my takeaways (relevant for AI devs):" @omarsar0 on X 2025-07-19 16:27:02 UTC 256.1K followers, 169.8K engagements
"Future of Work with AI Agents Stanford's new report analyzes what 1500 workers think about working with AI Agents. What types of AI Agents should we build A few surprises Let's take a closer look:" @omarsar0 on X 2025-06-20 18:51:58 UTC 256.1K followers, 301.1K engagements
"The framework separates planning (with LLMs) from execution (with small instruction-tuned models) using Routine as the bridge. This enables small-scale models to reliably execute complex plans with minimal resource overhead especially when using variable memory and modular tools like MCP server" @omarsar0 on X 2025-07-22 20:09:17 UTC 256K followers, XXX engagements
"Thoughts after coding relentlessly with tools like Replit Agent and Claude Code for the past few days: Current coding models are more impressive that we all think. Clever memory management search and context engineering is whats falling short. Tool calling also needs more work but thats improving fast with these new models. Spend the time preparing context (eg. design mockups and complete error logs) and you will be iterating less on building new features see less mistakes and get a lot more done with vibe coding" @omarsar0 on X 2025-07-23 03:19:29 UTC 256.1K followers, 10.6K engagements
"An ablation study shows the importance of explicitly including tool names and I/O descriptions in Routine steps. Removing tool names dropped Qwen3-14Bs accuracy from XXXX% to 71.9%. Adding I/O fields provided minor gains especially for less capable models" @omarsar0 on X 2025-07-22 20:09:21 UTC 256K followers, XXX engagements
"What comes after Cursor This new agentic IDE Kiro offers a glimpse at that future. Kiro comes with all the fun features in an agentic IDE deliberate planning and leverages ambient agents that autonmously collaborate with devs as they build production-grade systems" @omarsar0 on X 2025-07-15 14:51:14 UTC 255.9K followers, 47K engagements
"So tired of seeing these agentic systems used for booking travel. The real deal is AI agents for scientific discovery. Were getting close and not just LLM providers. If you can build reliable agentic systems you can be part of the race. Saying no more but watch this space" @omarsar0 on X 2025-07-20 01:05:46 UTC 256K followers, 14.2K engagements
"Agentic-R1 This 7B model is surprisingly good at interleaved tool use and reasoning capabilities. It's fun to see small language models improving this fast. Knowledge distillation in full display. Here are my notes:" @omarsar0 on X 2025-07-17 15:10:04 UTC 256K followers, 62K engagements
"LLMs Get Lost in Multi-turn Conversation The cat is out of the bag. Pay attention devs. This is one of the most common issues when building with LLMs today. Glad there is now paper to share insights. Here are my notes:" @omarsar0 on X 2025-05-14 20:47:41 UTC 256.1K followers, 759.3K engagements
"Every AI dev should know how to apply everything on this list. From prompting tips to context engineering to metaprompting. Learn it once apply it everywhere. Check out my new 4+ hrs course (with code examples) to learn more:" @omarsar0 on X 2025-06-27 14:16:50 UTC 255.9K followers, 49.3K engagements
"The work distinguishes prompt engineering from context engineering on dimensions like state scalability error analysis complexity etc" @omarsar0 on X 2025-07-18 16:12:14 UTC 256K followers, 6186 engagements
"Tool-calling capabilities in an area of continuous development in the space. The paper provides an overview of tool-augmented language model architectures and how they compare across tool categories" @omarsar0 on X 2025-07-18 16:12:36 UTC 255.9K followers, 4107 engagements
"This handbook is so good It covers everything you need to know about LLM inference. FREE to access:" @omarsar0 on X 2025-07-11 17:42:45 UTC 256.1K followers, 85.9K engagements
"Much is being said about context engineering but I want to focus on building. Find the full guide here: I am also hosting a workshop on "Context Engineering for AI Agents" for our academy pro members:" @omarsar0 on X 2025-07-05 18:33:33 UTC 255.9K followers, 16.7K engagements
"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:" @omarsar0 on X 2025-07-01 13:23:02 UTC 256K followers, 267.6K engagements
"Context Engineering Guide I'm writing a detailed guide on context engineering for AI devs. v1 is out now (bookmark it) I use a concrete deep research multi-agent example to show what context engineering involves" @omarsar0 on X 2025-07-05 18:33:33 UTC 256.1K followers, 289.8K engagements
"Whats Hud A lightweight Runtime Code Sensor that installs in X min. No config. No dashboards. No tracing. Just real-time visibility into: Performance Errors Flows Function paths Dependencies All directly in your AI tools" @omarsar0 on X 2025-07-21 13:30:20 UTC 255.8K followers, XXX engagements
"Context Engineering Guide is now part of the Prompt Engineering Guide. 🔥 Nicer format. We've also been writing guides on other fire topics such as deep research reasoning LLMs and image generation. I will be expanding the guide further in the coming days. Stay tuned" @omarsar0 on X 2025-07-08 13:48:44 UTC 256K followers, 36.1K engagements
"The context engineering evolution timeline from 2020 to 2025 involves foundational RAG systems to complex multi-agent architectures" @omarsar0 on X 2025-07-18 16:12:10 UTC 256K followers, 7225 engagements
"In a real HR agent scenario with X multi-step workflows adding Routine increased GPT-4os accuracy from XXXX% to XXXX% and Qwen3-14Bs from XXXX% to 83.3%. Fine-tuning Qwen3-14B on a Routine-following dataset further increased accuracy to 88.2%; training on a Routine-distilled dataset reached 95.5%" @omarsar0 on X 2025-07-22 20:09:13 UTC 256K followers, 1112 engagements
"Challenges & Future Work Challenges for future research include reducing LLM cost/latency (especially for real-time tasks) leveraging underused data like traces improving model adaptability to software evolution and integrating LLMs with existing AIOps toolchains instead of replacing them. Paper:" @omarsar0 on X 2025-07-20 18:15:31 UTC 255.8K followers, 5659 engagements
"You can read the full paper below: Want to take it a step further Learn about context engineering and how to build effective agentic systems in my courses: We also have a workshop on context engineering coming soon" @omarsar0 on X 2025-07-18 16:12:42 UTC 256K followers, 7601 engagements