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@divaagurlxw
diva
diva8.2K
diva
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@divaagurlxwAI EngineeringAI AgentsSystem Design

maths • engineer • aiml • software

8.2KFollowers
1.5KMedian impr. / post
6.1%Engagement
2
Paid partnerships
In their audience
3+ affiliated with @google follow diva
@craigweiss@petertsatsu@matteomadd3+ affiliated with @meta2+ from @ycombinator2+ from @stanford2+ affiliated with @ao_build2+ affiliated with @oracle
1,500+ verified followers analyzed
@craigweiss@petertsatsu@matteomadd+1497100+ AI engineers82+ AI founders75+ founders66+ engineers61+ media creators40+ creators
25–34 core age group
59.4%
50% of audience in United States
🇺🇸
Last 7 days144 posts analyzed · replies not counted · updates weekly
ImpressionsEngagements
2.2M1.1M0
177K88.5K0
Sep 21Sep 22Sep 23Sep 24Sep 25Sep 26Sep 27
Past collabs
diva@divaagurlxw · Aug 18as an AI engineer this shouldn't be this easy. I opened CrowdReply, talked to the AI Agent, and it: > pulled visibility across ChatGPT / Gemini / Claude > explained why they don't recommend the brand > ranked the gaps > started implementing the fix retrieval, citations, then write + ship. that's not a dashboard. that's an agentic loop. and people are charging $10K/month for the PDF version. watch this.CrowdReplyPaid partnership851 views
diva@divaagurlxw · Aug 10After trying MemoraX Code, I think the future of coding agent memory is less about storage and more about understanding intent. A bug fix, a code review, an architecture decision, and a deployment procedure are completely different types of knowledge. Treating all memories as the same vector database feels too simple. The idea of separating: >Coding Memory >Repo Memory >Procedure Memory >Personal Memory >makes much more sense for real engineering workflows. Memory should help agents make better decisions, not just retrieve more text.MemoraxPaid partnership2.3K views
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