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Nobody cares that you process 2B tokens. That’s not a flex, it’s a bill. Introducing Entelligence AI Agent Insights - Track not just dollars spent but actual ROI We built Agent Insights to map AI spend straight to engineering outcomes: features, fixes, and PRs Manage your budget based on...

70,282 次观看 • 2 个月前 •via X (Twitter)

40 条评论

Orikan 的头像
Orikan2 个月前

@EntelligenceAI Knowing what you spent is useful, but knowing what actually reached production because of that spend is where the real value is.

Wasif 的头像
Wasif2 个月前

@EntelligenceAI My boy @TaradepanR doesn’t have to bother me telling me about his new cool skill anymore. My agents pick up his design skills automatically to keep my frontend edits up to his standard It’s a great time to be lazy

PARSA 的头像
PARSA2 个月前

@EntelligenceAI This is exactly what engineering teams need to justify their AI budgets

Khushi 的头像
Khushi2 个月前

@EntelligenceAI this is how ai should be measured

Sharon Riley 的头像
Sharon Riley2 个月前

@EntelligenceAI That's what we needed

aditya 的头像
aditya2 个月前

@EntelligenceAI seems like it's time to stop tokenmaxxing and start optimizing for outcomes

Aman 的头像
Aman2 个月前

@EntelligenceAI love this finally something that tells you if the spend was worth it

Aiswarya Sankar 的头像
Aiswarya Sankar2 个月前

@EntelligenceAI Exactly you can’t optimize what you can’t measure

Pratham 的头像
Pratham2 个月前

@EntelligenceAI Love the individual spend tracking feature, especially useful for companies that give every employee access under per-seat plans.

Aiswarya Sankar 的头像
Aiswarya Sankar2 个月前

@EntelligenceAI Exactly but what we’re seeing actually is that teams end up wanting to budget for their overall goals and initiatives Currently there’s no good way to do that before this

Usman 的头像
Usman2 个月前

@EntelligenceAI Great

Sanskriti Naruka 的头像
Sanskriti Naruka2 个月前

@EntelligenceAI The accountability layer AI eng needed.

alex 的头像
alex2 个月前

@EntelligenceAI mapping spend directly to features and prs is the metric that’s been missing

Shubham Srivastava 的头像
Shubham Srivastava2 个月前

@EntelligenceAI i've spoken with so many CTOs yearning for something like this. Amazing vision and execution @Aiswarya_Sankar and @EntelligenceAI team!

Rishi 的头像
Rishi2 个月前

@EntelligenceAI AI ROI starts when every dollar can be traced to what actually shipped - not merely how many tokens were consumed. That’s the difference between tracking AI cost and measuring AI value.

Aiswarya Sankar 的头像
Aiswarya Sankar2 个月前

@EntelligenceAI Exactly value not spend

Parul Gautam 的头像
Parul Gautam2 个月前

@EntelligenceAI The metric that matters isn't token usage, it's what actually gets shipped.

Nitin.nn 的头像
Nitin.nn2 个月前

@EntelligenceAI The metric that matters isn't token usage, it's what actually gets shipped.

anne 的头像
anne2 个月前

@EntelligenceAI shifting the question from “how much did we spend” to “what did it build” is the right move

Jaynit Makwana 的头像
Jaynit Makwana2 个月前

@EntelligenceAI Love the shift from token metrics to actual engineering outcomes.

Aiswarya Sankar 的头像
Aiswarya Sankar2 个月前

@EntelligenceAI Otherwise it’s just numbers not outcomes

z 的头像
z2 个月前

@EntelligenceAI finally someone measuring what actually shipped instead of tokens burned

Aaliya 的头像
Aaliya2 个月前

@EntelligenceAI Real results matter more than big numbers.

AI PlanetX 的头像
AI PlanetX2 个月前

@EntelligenceAI Outcomes over token counts, every time.

Aditi 的头像
Aditi2 个月前

@EntelligenceAI Its time to stop token maxing

Krishna Agrawal 的头像
Krishna Agrawal2 个月前

@EntelligenceAI I think we've been measuring the wrong thing. Token count is interesting, but shipped work is what really matters.

Divya Porwal 的头像
Divya Porwal2 个月前

@EntelligenceAI AI spend is easy to track. AI impact? Not so much. The real metric isn’t how many tokens you used. It’s what actually got shipped.

Jade 的头像
Jade2 个月前

@EntelligenceAI token count was never the metric that mattered, this proves it

Rahul 的头像
Rahul2 个月前

@EntelligenceAI im so loving the graphs, data with useful insights

maria 的头像
maria2 个月前

@EntelligenceAI been looking for exactly this to justify our team’s ai spend

Aiswarya Sankar 的头像
Aiswarya Sankar2 个月前

@EntelligenceAI Don’t be an anthropic revenue machine!

Vyom 的头像
Vyom2 个月前

@EntelligenceAI soo I have to stop tokenmaxxing????

Z-Coder 的头像
Z-Coder2 个月前

@EntelligenceAI Stop guessing what your AI spend achieved. Agent Insights ties every invoice directly to the features delivered, issues resolved, and pull requests merged.

Juan 的头像
Juan2 个月前

@EntelligenceAI hey there @Aiswarya_Sankar i have a proposition this video should’ve gone viral and that’s what i specialize in, let me help with your next launch and if it doesn’t perform you don’t pay me a dime just sent over a dm

Akshit Joshi 的头像
Akshit Joshi2 个月前

@EntelligenceAI tokenmaxxing is not value maxxing , it's time to value max

AI_Explorer 的头像
AI_Explorer2 个月前

@EntelligenceAI Tokens burned ≠ value shipped. Agent Insights finally connects the invoice to the actual features, fixes, and PRs it produced.

Dhaval Makwana 的头像
Dhaval Makwana2 个月前

@EntelligenceAI Finally someone is measuring what AI actually delivers instead of how much it was used.

sheer_iran 的头像
sheer_iran1 个月前

And Replying @shedntcare_ : 📢💐☕️💐☕️💐Good Evening 🌹☕️🌹☕️🌹 Hi, I hope you have a good time and good luck in your work Can you follow my account? I will be happy, follow my account I am waiting for you Thank You To You Have a good day God bless you Always be successful 🙏🙏🙏

Launch Archive 的头像
Launch Archive2 个月前

@EntelligenceAI Agent Insights connects AI spending directly to engineering results, helping teams understand their true ROI. Congrats @Aiswarya_Sankar on #3 on Launch Archive today.

Nader Hantour 的头像
Nader Hantour2 个月前

@EntelligenceAI Step one isn't optimization, it's attribution — you can't cut what you can't see. InferenceView maps AI activity to teams and workloads with honest evidence grades:

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