Aishwarya Reganti (Ash)
Founder & CEO, LevelUp Labs. On 1 show, 1 appearance. The Shows tab opens the full record on each.
founderscientistengineeracademic@aish_reganti ↗LinkedIn ↗levelup-labs.ai ↗
Formerly an applied scientist and AI tech lead at Amazon Alexa and AWS's Generative AI Innovation Center, she has advised and deployed dozens of production AI applications for large enterprise clients. She is known for teaching AI engineering courses on Maven and developing operational frameworks like CC/CD for AI products.
1shows
1appearances
22statements
1resolved
0supported
0contradicted
0%fully supported
Everything Aishwarya Reganti (Ash) said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Reganti: Vendors Selling 'One-Click AI Agents' Are Pushing Pure Marketing
“I probably will go as far to say that if someone's selling you one click agents, it's pure marketing.
You don't want to buy into that.”
Reganti: Enterprise AI Workflows Require 4 to 6 Months for Real ROI
“To replace any critical workflow or to build something that can give you significant ROI easily takes four to six months of work, even if you have the best data layer and infrastructure layer.”
Reganti: LLM judges fail in complex AI cases due to emerging patterns
“When you go to complex use cases, it's incredibly hard to build LLM judges because you see a lot of emerging patterns. If you build a judge that would you know, test for verbosity or something like that, it turns out that you're seeing newer patterns that your…”
Reganti: Prompt injection will become a major crisis as AI goes mainstream
“I think that will be a huge problem once systems go mainstream. We're still so busy building AI products that we're not worried about security, but it will be such a huge problem to kind of especially with this non-deterministic API again, right? So you're kin…”
Reganti: Enterprise AI transformation cannot succeed as a bottom-up initiative
“It's almost always impossible for it to be bottom-up. You can't have a bunch of engineers go and get buy-in from the leader if they just don't trust in the technology, or if they have misaligned expectations about the technology, right?”
Reganti: Workflow Automation Always Requires Combining ML Models and Deterministic Code
“Whenever you're trying to automate some part of a workflow, it's never the case that you could use an AI agent and that will kind of solve your problems, right?
It's always, you probably have a machine learning model that's going to do some part of the job.
Yo…”
Reganti: Predefined AI evals only catch anticipated failure patterns
“The issue with just building a bunch of evaluation metrics and then having them in production is evaluation metrics catch only the errors that you're already aware of, but there can be a lot of emerging patterns that you understand. Only after you put things i…”
Reganti: Successful AI products require rethinking workflows, not just adding chat
“A lot of the use cases that I saw last year were more of slap chat on your data, right? And that was, you know calling themselves an AI product. And this year, a ton of companies are really rethinking their user experiences. And their workflows and all of that…”
Reganti: AI development breaks traditional handoffs between PMs and engineers
“The AI lifecycle both Pre-deployment and post-deployment is very different as compared to a traditional software life cycle. And so, so a lot of old contracts and handoffs between traditional roles, like say PMs and engineers and data folks has now been broken…”
Reganti: Granting AI agent autonomy inherently demands sacrificing operational control
“Every time you hand over decision-making capabilities or autonomy to agentic systems, you're kind of relinquishing some amount of control on your end trade, and when you do that, you want to make sure that your agent has Gained your trust, or it is reliable en…”
Reganti: Insurance pre-authorization is a prime use case for AI
“Insurance pre-authorization is a very ripe use case for AI because clinicians spend a lot of time pre-authorizing things like blood tests, MRIs, and things like that, right?”
Reganti: 75% of enterprises cite reliability as main barrier to customer AI
“It said about 74 or 75% of the enterprises that they had spoken to their biggest problem was reliability, and that's also why they weren't comfortable deploying products to their end users and building customer-facing products”
Reganti: Terms Like Evals and Agents Suffer From Semantic Diffusion
“I think Martin Fowler at some point had this term called semantic diffusion back in The 2000 which kind of means that someone comes up with a term, everybody starts butchering it with their own definitions, and then you kind of lose the actual definition of it…”
Reganti: Advance AI autonomy when monitoring yields minimal new surprise
“There's not really a rule book you can follow, but it's all about minimizing surprise, which means let's say you're calibrating every one or two days and you figured out that you're not seeing new data distribution patterns. Your users have been pretty consist…”
Reganti: Cheap AI building makes product design and problem focus far more valuable
“Building is really cheap today. Design is more expensive. Really thinking about your product, what you're going to build. Is it going to really solve a pain point? Is, is what is way more valuable today? And it will only become more true in the near future, ri…”
Reganti: Frontier AI models still cannot parse messy PDFs and handwriting
“There are so many handwritten documents and really messy PDFs that cannot be passed even by the best of the models as of today.”
Reganti: 80% of AI engineering is understanding workflows, not complex models
“80% of so-called AI engineers, AI PMs spend their time actually understanding their workflows very well. They're not building the fanciest and the, you know, most cool models or workflows around it. They're actually in the weeds understanding their customers' …”
Reganti: AI product development involves non-determinism across input, process, and output
“You don't know how the user might behave with your product, and you also don't know how the LLM might respond to that, so you're now working with an input, output, and a process, and you don't understand all the three very well.”
Reganti: AI challenges stem from achieving deterministic outcomes with non-deterministic tech
“You want to make sure that that intent is rightly communicated and the right actions are taken because most of your systems are deterministic, and you want to achieve a deterministic outcome, but with non-deterministic technology, and that's where it gets a li…”
Reganti: Rackspace CEO blocked 4-6 AM daily for AI learning
“I used to work with the CEO of now Rackspace, Gajen, so he would have this block every day in the morning, which would say catching up with AI four to six a.m., And he would not have any meetings or anything like that, and that was just his time to pick up on …”
Reganti: Team shut down their AI support product due to endless hotfixes
“At a time we were building for a customer support. Use case, which is what, which is the example that we give in the newsletter as well, and we had to shut down the product because we were doing so many hot fixes, and there was no way we could count all the em…”
Reganti: AI systems need recalibration as evolving user behavior increases complexity
“Something that might seem very natural to an end user might be very hard to build as a product builder, and you see that user behavior also evolves over time, and that's when you know that you want to go back and recalibrate.”
One line per show, most statements first. The link opens Aishwarya's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 LENNY'S PODCASTLEDGER | Founder & CEO, LevelUp Labs | 1 | 22 | 0% 0/1 | full record on Lenny's Podcast → |