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# ![@LakshyAAAgrawal Avatar](https://lunarcrush.com/gi/w:26/cr:twitter::2256125125.png) @LakshyAAAgrawal Lakshya A Agrawal

Lakshya A Agrawal posts on X about  the most. They currently have XXXXX followers and XX posts still getting attention that total XX engagements in the last XX hours.

### Engagements: XX [#](/creator/twitter::2256125125/interactions)
![Engagements Line Chart](https://lunarcrush.com/gi/w:600/cr:twitter::2256125125/c:line/m:interactions.svg)

- X Week XXXXXX -XX%
- X Month XXXXXX -XX%
- X Months XXXXXXX +29,327%
- X Year XXXXXXX +4,580%

### Mentions: X [#](/creator/twitter::2256125125/posts_active)
![Mentions Line Chart](https://lunarcrush.com/gi/w:600/cr:twitter::2256125125/c:line/m:posts_active.svg)

- X Week XX -XXXX%
- X Month XX +417%
- X Months XX +1,125%
- X Year XX +1,225%

### Followers: XXXXX [#](/creator/twitter::2256125125/followers)
![Followers Line Chart](https://lunarcrush.com/gi/w:600/cr:twitter::2256125125/c:line/m:followers.svg)

- X Week XXXXX +2.60%
- X Month XXXXX +19%
- X Months XXXXX +551%
- X Year XXXXX +766%

### CreatorRank: undefined [#](/creator/twitter::2256125125/influencer_rank)
![CreatorRank Line Chart](https://lunarcrush.com/gi/w:600/cr:twitter::2256125125/c:line/m:influencer_rank.svg)

### Social Influence [#](/creator/twitter::2256125125/influence)
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**Top accounts mentioned or mentioned by**
[@dspyoss](/creator/undefined) [@elonmusk](/creator/undefined) [@casperhansen](/creator/undefined) [@goobyesq](/creator/undefined) [@asfishaheen](/creator/undefined) [@2abstract4me](/creator/undefined) [@madhavsinghal](/creator/undefined) [@xiaoemily41333](/creator/undefined) [@eevmanu](/creator/undefined) [@arslansaas](/creator/undefined) [@krishnanrohit](/creator/undefined) [@victortaelin](/creator/undefined) [@hammermt](/creator/undefined) [@karpathys](/creator/undefined) [@mikepavlukhin](/creator/undefined) [@mattdunn](/creator/undefined) [@0xminto](/creator/undefined) [@madhavsinghal_](/creator/undefined) [@lakshyaag](/creator/undefined) [@tribbloid](/creator/undefined)
### Top Social Posts [#](/creator/twitter::2256125125/posts)
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Top posts by engagements in the last XX hours

"Optimizing a data analysis coding agent with GEPA using execution-guided feedback on real-world workloads. Amazing tutorial by @ArslanSAAS:"  
[X Link](https://x.com/LakshyAAAgrawal/status/1977147206168658216) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-11T23:00Z 2728 followers, 10.3K engagements


"Struggling to use LLMs for creative tasks @hammer_mt talks about the powerful "Evaluator-Optimizer" pattern with GEPA+@DSPyOSS to optimize prompts for fuzzy generative tasks where evals are informal and subjective. Checkout the full talk prompt and executable notebook below"  
[X Link](https://x.com/LakshyAAAgrawal/status/1979389591389114796) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-18T03:30Z 2728 followers, 8409 engagements


"Super cool work inspired by @karpathy's tweet about converting textbook practice problems into environments. What a cool topic to build environment around too"  
[X Link](https://x.com/LakshyAAAgrawal/status/1979652060539990255) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-18T20:53Z 2723 followers, 3486 engagements


"Checkout the GEPA repository for optimizing your agents:"  
[X Link](https://x.com/LakshyAAAgrawal/status/1979664893885530204) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-18T21:44Z 2729 followers, XXX engagements


"Check the list at:"  
[X Link](https://x.com/LakshyAAAgrawal/status/1979664895194100072) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-18T21:44Z 2728 followers, XXX engagements


"Amazing article by @mike_pavlukhin explaining how to tune a small model like Gemma-3-1B to write good quality creative content (stories) using GEPA with @DSPyOSS. Many interesting patterns and insights for creative task optimization"  
[X Link](https://x.com/LakshyAAAgrawal/status/1977048857981993090) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-11T16:29Z 2728 followers, 12K engagements


"In this context GEPA works as a prompt optimizer so the end result is a prompt (or multiple prompts for a multi-agent system one for each component). However one aspect that does not get highlighted enough is that GEPA is a text evolution engine: Given a target metric GEPA can efficiently search/evolve the right text to improve that metric. What the text represents is upto the user. For example In this notebook we use text to represent a full agent code and GEPA ends up discovering a very sophisticated agent (that can perform self-reflection and iterative refinement on code) for ARC-AGI"  
[X Link](https://x.com/LakshyAAAgrawal/status/1968236513810087975) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-09-17T08:52Z 2730 followers, 104.2K engagements


"@XiaoEmily41333 @m_att_dunn Just to clarify: GEPA also uses just one call at test time"  
[X Link](https://x.com/LakshyAAAgrawal/status/1980694705425027323) [@LakshyAAAgrawal](/creator/x/LakshyAAAgrawal) 2025-10-21T17:56Z 2730 followers, XX engagements