[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.] #  @neural_avb AVB AVB posts on X about context engineering, llm, agentic, $googl the most. They currently have XXXXX followers and XX posts still getting attention that total XXXXXX engagements in the last XX hours. ### Engagements: XXXXXX [#](/creator/twitter::1754194661084983296/interactions)  - X Week XXXXXX +1,278% - X Month XXXXXX +8,959% - X Year XXXXXXX +43,036% ### Mentions: XX [#](/creator/twitter::1754194661084983296/posts_active)  ### Followers: XXXXX [#](/creator/twitter::1754194661084983296/followers)  - X Week XXXXX +47% - X Month XXXXX +359% ### CreatorRank: XXXXXXX [#](/creator/twitter::1754194661084983296/influencer_rank)  ### Social Influence [#](/creator/twitter::1754194661084983296/influence) --- **Social category influence** [stocks](/list/stocks) XXXX% [technology brands](/list/technology-brands) XXXX% **Social topic influence** [context engineering](/topic/context-engineering) #3, [llm](/topic/llm) 8.89%, [agentic](/topic/agentic) 4.44%, [$googl](/topic/$googl) 2.22%, [gpu](/topic/gpu) 2.22%, [capabilities](/topic/capabilities) 2.22%, [handy](/topic/handy) 2.22%, [applied](/topic/applied) 2.22%, [topics](/topic/topics) 2.22%, [shoutout](/topic/shoutout) XXXX% **Top accounts mentioned or mentioned by** [@jacksonatkinsx](/creator/undefined) [@hesamation](/creator/undefined) [@777bhavya](/creator/undefined) [@eigenron](/creator/undefined) [@kalomaze](/creator/undefined) [@dankornas](/creator/undefined) [@rohanpaulai](/creator/undefined) [@clementdelangue](/creator/undefined) [@prompttunes](/creator/undefined) [@hiteshdotcom](/creator/undefined) [@hostinger](/creator/undefined) [@yuvrajs9886](/creator/undefined) [@mickelliu](/creator/undefined) [@neuralavb](/creator/undefined) [@prathamgrv](/creator/undefined) [@jon_blay](/creator/undefined) [@atreydesai](/creator/undefined) [@hust_niuniu](/creator/undefined) [@fact0id](/creator/undefined) [@yacinelearning](/creator/undefined) **Top assets mentioned** [Alphabet Inc Class A (GOOGL)](/topic/$googl) ### Top Social Posts [#](/creator/twitter::1754194661084983296/posts) --- Top posts by engagements in the last XX hours "@DanKornas I am not worried about this. The wheel keeps turning Data Science is not getting anywhere. You have 10000+ data points to cluster and analyze you call a data scientist. Not a prompt engineer"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1943766118574797194) 2025-07-11 20:15:30 UTC 1756 followers, 6582 engagements "TIL my DSPY tutorial has crossed 40K views on YT. Shows up very high on google search and a top X viewed YT videos on the topic. When i was making this I thought I was making niche content for nerds. Apparently the niche is much bigger than I thought"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1944805488719487116) 2025-07-14 17:05:35 UTC 1821 followers, 7431 engagements "What platform do yall use to spin up a remote GPU server On the market looking for one"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945714656372498731) 2025-07-17 05:18:18 UTC 1833 followers, 1625 engagements "Must have tools for agentic ai: - api key to an llm - dspy.Predict - python if statement - python for loop"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945713926496256217) 2025-07-17 05:15:24 UTC 1774 followers, 2380 engagements "@JacksonAtkinsX Kinda interesting. I feel like LLMs can differ in capabilities so much depending on size provider training data etc - tuning the prompts to just one LLM may not always guarantee good performance on other models"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1946353334857646427) 2025-07-18 23:36:11 UTC 1833 followers, XXX engagements "@Hesamation Mental note/Social Promise: I need to make a proper video on Context Engineering"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945264165641228562) 2025-07-15 23:28:13 UTC 1826 followers, 2628 engagements "I am trying to get a distribution of what sort of ML/AI projects people around me here are working on. Feel free to share below. CV NLP RL Agentic AI classical ML etc - tell me what yall are into"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1944071570760380812) 2025-07-12 16:29:16 UTC 1833 followers, 24.5K engagements "Here are X must-know RL libraries for single-agent and multi-agent environments. I am using most of these right now to make my multi-agent collaborative navigation environment - so it's a great time to post this list"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1944289959126380972) 2025-07-13 06:57:04 UTC 1798 followers, XXX engagements "Today I started ideating a dedicated video on Context Engineering. I'll cover the main approaches some research trends and a walkthrough of the concepts with DSPy. This git repo will be my muse for this one"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945332815337238734) 2025-07-16 04:01:00 UTC 1833 followers, 16.8K engagements "Not really. SIMBA or other DSPy optimizers inputs a dataset and a metric function to update prompts. Refine generates an output from the LM checks reward and sends the LLM additional advice about how to change the output for better reward. Its kinda self reflection with a reward module"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945640845161402461) 2025-07-17 00:25:00 UTC 1833 followers, XXX engagements "I think I am cooking the Context Engineering with DSPy tutorial hard. The blueprint. 👇🏽"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945532666926846333) 2025-07-16 17:15:08 UTC 1832 followers, 12.7K engagements "Halfway through the Context Engineering w DSPy tutorial. I quite like where it's going. I am taking the simple but classic "write a joke" prompt and creating a full 35-ish minute journey out of it - going through each concept one by one"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1946083498684457430) 2025-07-18 05:43:57 UTC 1833 followers, 1072 engagements "Today I looked deeper into dspy.Refine (& BestOfN). Its insane just how much heavy lifting these modules can do. Define a reward function for any dspy module and Refine will generate responses optimized for to maximize the reward. The way it does so is very interesting. (thread)"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945616221648339295) 2025-07-16 22:47:09 UTC 1833 followers, 15.1K engagements "This taxonomy for Context Engineering is sooo handy. I'm making a comprehensive video tutorial on this using DSPy and my goal is to incorporate atleast one major algorithm from all the blocks"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1946288694882685317) 2025-07-18 19:19:19 UTC 1833 followers, 20.4K engagements "@mickel_liu Gotta love how classic RL paradigms are now being directly applied to LLM training. Cool poster"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1946101360354570657) 2025-07-18 06:54:55 UTC 1824 followers, XX engagements "Dear algorithm show this only to people interested in Reinforcement Learning"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1944784369425805625) 2025-07-14 15:41:40 UTC 1833 followers, 47.4K engagements "@kalomaze Do you mean it coz it decreases compute requirements ie no value net no reward net"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945244023435759916) 2025-07-15 22:08:10 UTC 1770 followers, XXX engagements "Here is a curriculum-ordered list of topics to read for Language Modelling / NLP - going from foundational topics to modern methods. (This is a pure deep learning list covering only-text models) Early foundational stuff - Tokenization - word level BPE n-grams - Word2Vec Word Embeddings - RNNs GRUs LSTMS - Teacher forcing Scheduled sampling Beam search decoding Nucleus sampling - Seq2Seq / Encoder-Decoder Networks - Bahnadau Attention Transformers/Attention: - Attention is All You Need / Transformer architectures - GPT - BERT - Relative Position Embeddings ROPE - T5 XL-Net - Interesting"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1944437978585063840) 2025-07-13 16:45:14 UTC 1796 followers, 16K engagements "So the field of memory management for context engineering goes way deeper than I thought. I'll cover the greatest hits in my upcoming tutorial but this literally needs a whole week of research to do justice"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1946289886773870691) 2025-07-18 19:24:03 UTC 1833 followers, XXX engagements "Repo: Shoutout to @Hesamation for posting it"  [@neural_avb](/creator/x/neural_avb) on [X](/post/tweet/1945340294662078766) 2025-07-16 04:30:43 UTC 1811 followers, XXX 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.]
@neural_avb AVB
AVB posts on X about context engineering, llm, agentic, $googl the most. They currently have XXXXX followers and XX posts still getting attention that total XXXXXX engagements in the last XX hours.
Engagements: XXXXXX #
- X Week XXXXXX +1,278%
- X Month XXXXXX +8,959%
- X Year XXXXXXX +43,036%
Mentions: XX #
Followers: XXXXX #
- X Week XXXXX +47%
- X Month XXXXX +359%
CreatorRank: XXXXXXX #
Social Influence #
Social category influence stocks XXXX% technology brands XXXX%
Social topic influence context engineering #3, llm 8.89%, agentic 4.44%, $googl 2.22%, gpu 2.22%, capabilities 2.22%, handy 2.22%, applied 2.22%, topics 2.22%, shoutout XXXX%
Top accounts mentioned or mentioned by @jacksonatkinsx @hesamation @777bhavya @eigenron @kalomaze @dankornas @rohanpaulai @clementdelangue @prompttunes @hiteshdotcom @hostinger @yuvrajs9886 @mickelliu @neuralavb @prathamgrv @jon_blay @atreydesai @hust_niuniu @fact0id @yacinelearning
Top assets mentioned Alphabet Inc Class A (GOOGL)
Top Social Posts #
Top posts by engagements in the last XX hours
"@DanKornas I am not worried about this. The wheel keeps turning Data Science is not getting anywhere. You have 10000+ data points to cluster and analyze you call a data scientist. Not a prompt engineer"
@neural_avb on X 2025-07-11 20:15:30 UTC 1756 followers, 6582 engagements
"TIL my DSPY tutorial has crossed 40K views on YT. Shows up very high on google search and a top X viewed YT videos on the topic. When i was making this I thought I was making niche content for nerds. Apparently the niche is much bigger than I thought" @neural_avb on X 2025-07-14 17:05:35 UTC 1821 followers, 7431 engagements
"What platform do yall use to spin up a remote GPU server On the market looking for one" @neural_avb on X 2025-07-17 05:18:18 UTC 1833 followers, 1625 engagements
"Must have tools for agentic ai: - api key to an llm - dspy.Predict - python if statement - python for loop" @neural_avb on X 2025-07-17 05:15:24 UTC 1774 followers, 2380 engagements
"@JacksonAtkinsX Kinda interesting. I feel like LLMs can differ in capabilities so much depending on size provider training data etc - tuning the prompts to just one LLM may not always guarantee good performance on other models" @neural_avb on X 2025-07-18 23:36:11 UTC 1833 followers, XXX engagements
"@Hesamation Mental note/Social Promise: I need to make a proper video on Context Engineering" @neural_avb on X 2025-07-15 23:28:13 UTC 1826 followers, 2628 engagements
"I am trying to get a distribution of what sort of ML/AI projects people around me here are working on. Feel free to share below. CV NLP RL Agentic AI classical ML etc - tell me what yall are into" @neural_avb on X 2025-07-12 16:29:16 UTC 1833 followers, 24.5K engagements
"Here are X must-know RL libraries for single-agent and multi-agent environments. I am using most of these right now to make my multi-agent collaborative navigation environment - so it's a great time to post this list" @neural_avb on X 2025-07-13 06:57:04 UTC 1798 followers, XXX engagements
"Today I started ideating a dedicated video on Context Engineering. I'll cover the main approaches some research trends and a walkthrough of the concepts with DSPy. This git repo will be my muse for this one" @neural_avb on X 2025-07-16 04:01:00 UTC 1833 followers, 16.8K engagements
"Not really. SIMBA or other DSPy optimizers inputs a dataset and a metric function to update prompts. Refine generates an output from the LM checks reward and sends the LLM additional advice about how to change the output for better reward. Its kinda self reflection with a reward module" @neural_avb on X 2025-07-17 00:25:00 UTC 1833 followers, XXX engagements
"I think I am cooking the Context Engineering with DSPy tutorial hard. The blueprint. 👇🏽" @neural_avb on X 2025-07-16 17:15:08 UTC 1832 followers, 12.7K engagements
"Halfway through the Context Engineering w DSPy tutorial. I quite like where it's going. I am taking the simple but classic "write a joke" prompt and creating a full 35-ish minute journey out of it - going through each concept one by one" @neural_avb on X 2025-07-18 05:43:57 UTC 1833 followers, 1072 engagements
"Today I looked deeper into dspy.Refine (& BestOfN). Its insane just how much heavy lifting these modules can do. Define a reward function for any dspy module and Refine will generate responses optimized for to maximize the reward. The way it does so is very interesting. (thread)" @neural_avb on X 2025-07-16 22:47:09 UTC 1833 followers, 15.1K engagements
"This taxonomy for Context Engineering is sooo handy. I'm making a comprehensive video tutorial on this using DSPy and my goal is to incorporate atleast one major algorithm from all the blocks" @neural_avb on X 2025-07-18 19:19:19 UTC 1833 followers, 20.4K engagements
"@mickel_liu Gotta love how classic RL paradigms are now being directly applied to LLM training. Cool poster" @neural_avb on X 2025-07-18 06:54:55 UTC 1824 followers, XX engagements
"Dear algorithm show this only to people interested in Reinforcement Learning" @neural_avb on X 2025-07-14 15:41:40 UTC 1833 followers, 47.4K engagements
"@kalomaze Do you mean it coz it decreases compute requirements ie no value net no reward net" @neural_avb on X 2025-07-15 22:08:10 UTC 1770 followers, XXX engagements
"Here is a curriculum-ordered list of topics to read for Language Modelling / NLP - going from foundational topics to modern methods. (This is a pure deep learning list covering only-text models) Early foundational stuff - Tokenization - word level BPE n-grams - Word2Vec Word Embeddings - RNNs GRUs LSTMS - Teacher forcing Scheduled sampling Beam search decoding Nucleus sampling - Seq2Seq / Encoder-Decoder Networks - Bahnadau Attention Transformers/Attention: - Attention is All You Need / Transformer architectures - GPT - BERT - Relative Position Embeddings ROPE - T5 XL-Net - Interesting" @neural_avb on X 2025-07-13 16:45:14 UTC 1796 followers, 16K engagements
"So the field of memory management for context engineering goes way deeper than I thought. I'll cover the greatest hits in my upcoming tutorial but this literally needs a whole week of research to do justice" @neural_avb on X 2025-07-18 19:24:03 UTC 1833 followers, XXX engagements
"Repo: Shoutout to @Hesamation for posting it" @neural_avb on X 2025-07-16 04:30:43 UTC 1811 followers, XXX engagements