Month: August 2024
SHAREHOLDER ALERT: Faruqi & Faruqi, LLP Investigates Claims on Behalf of Investors of …
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Faruqi & Faruqi, LLP Securities Litigation Partner James (Josh) Wilson Encourages Investors Who Suffered Losses Exceeding $100,000 In MongoDB To Contact Him Directly To Discuss Their Options
If you suffered losses exceeding $100,000 investing in MongoDB stock or options between August 31, 2023 and May 30, 2024 and would like to discuss your legal rights, call Faruqi & Faruqi partner Josh Wilson directly at 877-247-4292 or 212-983-9330 (Ext. 1310). You may also click here for additional information: www.faruqilaw.com/MDB.
NEW YORK, Aug. 02, 2024 (GLOBE NEWSWIRE) — Faruqi & Faruqi, LLP, a leading national securities law firm, is investigating potential claims against MongoDB, Inc. (“MongoDB” or the “Company”) (NASDAQ: MDB) and reminds investors of the September 9, 2024 deadline to seek the role of lead plaintiff in a federal securities class action that has been filed against the Company.
Faruqi & Faruqi is a leading national securities law firm with offices in New York, Pennsylvania, California and Georgia. The firm has recovered hundreds of millions of dollars for investors since its founding in 1995. See www.faruqilaw.com.
The complaint alleges that on March 7, 2024, MongoDB reported strong Q4 2024 results and then announced lower than expected full-year guidance for 2025. MongoDB attributed it to the Company’s change in its “sales incentive structure” which led to a decrease in revenue related to “unused commitments and multi-year licensing deals.”
Following this news, MongoDB’s stock price fell by $28.59 per share to close at $383.42 per share.
Later, on May 30, 2024, MongoDB further lowered its guidance for the full year 2025 attributing it to “macro impacting consumption growth.” Analysts commenting on the reduced guidance questioned if changes made to the Company’s marketing strategy “led to change in customer behavior and usage patterns.”
Following this news, MongoDB’s stock price fell by $73.94 per share to close at $236.06 per share.
The court-appointed lead plaintiff is the investor with the largest financial interest in the relief sought by the class who is adequate and typical of class members who directs and oversees the litigation on behalf of the putative class. Any member of the putative class may move the Court to serve as lead plaintiff through counsel of their choice, or may choose to do nothing and remain an absent class member. Your ability to share in any recovery is not affected by the decision to serve as a lead plaintiff or not.
Faruqi & Faruqi, LLP also encourages anyone with information regarding MongoDB’s conduct to contact the firm, including whistleblowers, former employees, shareholders and others.
To learn more about the MongoDB class action, go to www.faruqilaw.com/MDB or call Faruqi & Faruqi partner Josh Wilson directly at 877-247-4292 or 212-983-9330 (Ext. 1310).
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MongoDB (MDB) Class Action Alert: Shareholders Have Begun Scrutinizing Sales Incentives
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SAN DIEGO, Aug. 02, 2024 (GLOBE NEWSWIRE) — Shareholder rights law firm Johnson Fistel, LLP announces that a class action lawsuit has commenced on behalf of investors of MongoDB, Inc. (NASDAQ: MDB).
There is no cost or obligation to you.
CLASS PERIOD: August 31, 2023 – May 30, 2024
LEAD PLAINTIFF DEADLINE: September 9, 2024
DOCKET #: 24-CV-05191
ALLEGATIONS: Materially false and misleading statements
Contact for More Information: James Baker, (619) 814-4471, jimb@johnsonfistel.com or fjohnson@johnsonfistel.com
The complaint alleges Defendants provided overwhelmingly positive statements to investors while, at the same time, disseminating materially false and misleading statements and/or concealing material adverse facts concerning related to MongoDB’s sales force incentive restructure, including: a significant reduction in the information gathered by their sales force as to the trajectory for the new Atlas enrollments without upfront commitments; reduced pressure on new enrollments to grow; and a significant loss of revenue from unused commitments. Such statements absent these material facts caused Plaintiff and other shareholders to purchase MongoDB’s securities at artificially inflated prices.
However, Investors began to question the veracity of Defendants’ public statements on March 7, 2024, during MongoDB’s earnings call following a same day press release announcing its fiscal year 2024 earnings. In pertinent part, Defendants announced an anticipated near zero revenue from unused Atlas commitments in fiscal year 2025, a decrease of approximately $40 million in revenue, attributed to the Company’s decision to change their sales incentive structure to reduce enrollment 3 frictions. Additionally, MongoDB provided estimated growth for the fiscal year 2025 (ending January 31, 2025). In particular, Defendants projected only 14% growth, compared to projected 16% for the previous year which had resulted in an actualized 31% growth.
The Complaint alleges that during the Class Period, Defendants made materially false and misleading statements and engaged in a scheme to deceive the market and a course of conduct that artificially inflated the price of MongoDB’s common stock and operated as a fraud or deceit on Class Period purchasers of MongoDB’s common stock by materially misleading the investing public.
Investor Action Steps: Shareholders who incurred losses during the class period, have until September 9, 2024, to move the court to become a lead plaintiff in this action. A lead plaintiff will act on behalf of all other class members in directing the class-action lawsuit. The lead plaintiff can select a law firm of its choice to litigate the class-action lawsuit. An investor’s ability to share any potential future recovery of the class action lawsuit is not dependent upon serving as lead plaintiff.
About Johnson Fistel, LLP | Top Law Firm, Securities Fraud, Investors Rights:
Johnson Fistel, LLP is a nationally recognized shareholder rights law firm with offices in California, New York, Georgia, and Colorado. The firm represents individual and institutional investors in shareholder derivative and securities class action lawsuits. We also extend our services to foreign investors who have purchased on US exchanges. Stay updated with news on stock drops and learn how Johnson Fistel, LLP can help you recover your losses. For more information about the firm and its attorneys, please visit http://www.johnsonfistel.com.
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Contact:
Johnson Fistel, LLP
501 W. Broadway, Suite 800, San Diego, CA 92101
James Baker, Investor Relations or Frank J. Johnson, Esq., (619) 814-4471
jimb@johnsonfistel.com or fjohnson@johnsonfistel.com
Article originally posted on mongodb google news. Visit mongodb google news
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Posted on mongodb google news. Visit mongodb google news
SAN DIEGO, Aug. 02, 2024 (GLOBE NEWSWIRE) — Shareholder rights law firm Johnson Fistel, LLP announces that a class action lawsuit has commenced on behalf of investors of MongoDB, Inc. (NASDAQ: MDB).
There is no cost or obligation to you.
CLASS PERIOD: August 31, 2023 – May 30, 2024
LEAD PLAINTIFF DEADLINE: September 9, 2024
DOCKET #: 24-CV-05191
ALLEGATIONS: Materially false and misleading statements
Contact for More Information: James Baker, (619) 814-4471, jimb@johnsonfistel.com or fjohnson@johnsonfistel.com
The complaint alleges Defendants provided overwhelmingly positive statements to investors while, at the same time, disseminating materially false and misleading statements and/or concealing material adverse facts concerning related to MongoDB’s sales force incentive restructure, including: a significant reduction in the information gathered by their sales force as to the trajectory for the new Atlas enrollments without upfront commitments; reduced pressure on new enrollments to grow; and a significant loss of revenue from unused commitments. Such statements absent these material facts caused Plaintiff and other shareholders to purchase MongoDB’s securities at artificially inflated prices.
However, Investors began to question the veracity of Defendants’ public statements on March 7, 2024, during MongoDB’s earnings call following a same day press release announcing its fiscal year 2024 earnings. In pertinent part, Defendants announced an anticipated near zero revenue from unused Atlas commitments in fiscal year 2025, a decrease of approximately $40 million in revenue, attributed to the Company’s decision to change their sales incentive structure to reduce enrollment 3 frictions. Additionally, MongoDB provided estimated growth for the fiscal year 2025 (ending January 31, 2025). In particular, Defendants projected only 14% growth, compared to projected 16% for the previous year which had resulted in an actualized 31% growth.
The Complaint alleges that during the Class Period, Defendants made materially false and misleading statements and engaged in a scheme to deceive the market and a course of conduct that artificially inflated the price of MongoDB’s common stock and operated as a fraud or deceit on Class Period purchasers of MongoDB’s common stock by materially misleading the investing public.
Investor Action Steps: Shareholders who incurred losses during the class period, have until September 9, 2024, to move the court to become a lead plaintiff in this action. A lead plaintiff will act on behalf of all other class members in directing the class-action lawsuit. The lead plaintiff can select a law firm of its choice to litigate the class-action lawsuit. An investor’s ability to share any potential future recovery of the class action lawsuit is not dependent upon serving as lead plaintiff.
About Johnson Fistel, LLP | Top Law Firm, Securities Fraud, Investors Rights:
Johnson Fistel, LLP is a nationally recognized shareholder rights law firm with offices in California, New York, Georgia, and Colorado. The firm represents individual and institutional investors in shareholder derivative and securities class action lawsuits. We also extend our services to foreign investors who have purchased on US exchanges. Stay updated with news on stock drops and learn how Johnson Fistel, LLP can help you recover your losses. For more information about the firm and its attorneys, please visit http://www.johnsonfistel.com.
Attorney advertising.
Past results do not guarantee future outcomes.
Services may be performed by attorneys in any of our offices.
Johnson Fistel, LLP has paid for the dissemination of this promotional communication, and Frank J. Johnson is the attorney responsible for its content.
Contact:
Johnson Fistel, LLP
501 W. Broadway, Suite 800, San Diego, CA 92101
James Baker, Investor Relations or Frank J. Johnson, Esq., (619) 814-4471
jimb@johnsonfistel.com or fjohnson@johnsonfistel.com
Article originally posted on mongodb google news. Visit mongodb google news
MMS • Renato Losio
Article originally posted on InfoQ. Visit InfoQ
For the first time in its history, AWS has discontinued several managed services within a matter of days. Among the affected services are the source control AWS CodeCommit, the cloud-based IDE AWS Cloud9, and the time-series forecasting service Amazon Forecast. The wave of deprecations has led to concerns within the community due to the lack of clear communication.
After deprecating the ledger database Amazon QLDB, as separately reported on InfoQ, AWS began posting articles to document how to replace CodeCommit with other Git providers, CloudSearch with OpenSearch, and Cloud9 with AWS IDE Toolkits. While the technical articles provided useful information, they did not initially clarify whether the existing services had been discontinued, leaving the community in a state of uncertainty.
None of the retirements — S3 Select, CloudSearch, Cloud9, SimpleDB, Forecast, Data Pipeline, and CodeCommit — appeared on the announcement page and feeds, a practice that other providers usually follow. While existing customers might have received emails clarifying the status of the affected services, others were left wondering if the services were still supported or if AWS was changing its philosophy. To clarify the status of the affected services—a small percentage of the over 200 available—Jeff Barr, vice president and chief evangelist at AWS, confirmed:
After giving it a lot of thought, we made the decision to discontinue new access to a small number of services, including AWS CodeCommit. While we are no longer onboarding new customers to these services, there are no plans to change the features or experience you get today, including keeping them secure and reliable. We also support migrations to other AWS or third-party solutions better aligned with your evolving needs. Keep the feedback coming. We’re always listening.
Matthew Juliana, senior manager at Rackspace Technology, highlights how Barr’s message significantly differs from the “retiring services isn’t something we do at AWS” statement that Werner Vogels, CEO at Amazon, wrote just over a year ago. SimpleDB, a service superseded by DynamoDB over a decade ago, has often been used as an example of AWS not killing services like other providers do. In the article “The end of the Everything Cloud“, Forrest Brazeal comments:
This is not an indication that AWS is turning into GCP, who has inherited from broader Google a deserved reputation for pulling the rug out from under users by killing services with wide adoption (…) These services have been in maintenance-only mode for some time.
Andrew Brown, CEO of ExamPro, writes:
Whether this is a marketing blunder or not to me the idea of AWS cleaning up their catalog and killing off zombie AWS Services and Products is a good idea.
After suggesting that AWS should provide a deprecation page, Scott Piper, cloud security consultant, now maintains a list on GitHub of the services that have been deprecated. Scott writes:
I’d also like to hear the strategy moving forward around this in terms of whether this is a one-time event, or if we should expect more batches of deprecations (…) how should one be evaluating services now that a change in strategy has happened at AWS?
Since the original posts, various deprecation notes have been added to the articles documenting the migrations from the affected services, clarifying the status of each one.
September 9, 2024 Deadline: Contact Levi & Korsinsky to Join Class Action Suit Against MDB
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Subject: ATY
NEW YORK, Aug. 2, 2024 /PRNewswire/ — Levi & Korsinsky, LLP notifies investors in MongoDB, Inc. (“MongoDB” or the “Company”) (NASDAQ: MDB) of a class action securities lawsuit.
CLASS DEFINITION: The lawsuit seeks to recover losses on behalf of MongoDB investors who were adversely affected by alleged securities fraud between August 31, 2023 and May 30, 2024. Follow the link below to get more information and be contacted by a member of our team:
https://zlk.com/pslra-1/mongodb-inc-lawsuit-submission-form?prid=93322&wire=4
MDB investors may also contact Joseph E. Levi, Esq. via email at [email protected] or by telephone at (212) 363-7500.
CASE DETAILS: According to the complaint, on March 7, 2024, MongoDB reported strong Q4 2024 results and then announced lower than expected full-year guidance for 2025. MongoDB attributed it to the Company’s change in its “sales incentive structure” which led to a decrease in revenue related to “unused commitments and multi-year licensing deals.” Following this news, MongoDB’s stock price fell by $28.59 per share to close at $383.42 per share. Later, on May 30, 2024, MongoDB further lowered its guidance for the full year 2025 attributing it to “macro impacting consumption growth.” Analysts commenting on the reduced guidance questioned if changes made to the Company’s marketing strategy “led to change in customer behavior and usage patterns.” Following this news, MongoDB’s stock price fell by $73.94 per share to close at $236.06 per share.
WHAT’S NEXT? If you suffered a loss in MongoDB during the relevant time frame, you have until September 9, 2024 to request that the Court appoint you as lead plaintiff. Your ability to share in any recovery doesn’t require that you serve as a lead plaintiff.
NO COST TO YOU: If you are a class member, you may be entitled to compensation without payment of any out-of-pocket costs or fees. There is no cost or obligation to participate.
WHY LEVI & KORSINSKY: Over the past 20 years, the team at Levi & Korsinsky has secured hundreds of millions of dollars for aggrieved shareholders and built a track record of winning high-stakes cases. Our firm has extensive expertise representing investors in complex securities litigation and a team of over 70 employees to serve our clients. For seven years in a row, Levi & Korsinsky has ranked in ISS Securities Class Action Services’ Top 50 Report as one of the top securities litigation firms in the United States.
CONTACT:
Levi & Korsinsky, LLP
Joseph E. Levi, Esq.
Ed Korsinsky, Esq.
33 Whitehall Street, 17th Floor
New York, NY 10004
[email protected]
Tel: (212) 363-7500
Fax: (212) 363-7171
www.zlk.com
SOURCE Levi & Korsinsky, LLP
News published on 2 august 2024 at 05:45 and distributed by: 
Article originally posted on mongodb google news. Visit mongodb google news
September 9, 2024 Deadline: Contact Levi & Korsinsky to Join Class Action Suit Against MDB
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Posted on mongodb google news. Visit mongodb google news
NEW YORK, Aug. 2, 2024 /PRNewswire/ — Levi & Korsinsky, LLP notifies investors in MongoDB, Inc. (“MongoDB” or the “Company”) (NASDAQ: MDB) of a class action securities lawsuit.
CLASS DEFINITION: The lawsuit seeks to recover losses on behalf of MongoDB investors who were adversely affected by alleged securities fraud between August 31, 2023 and May 30, 2024. Follow the link below to get more information and be contacted by a member of our team:
https://zlk.com/pslra-1/mongodb-inc-lawsuit-submission-form?prid=93322&wire=4
MDB investors may also contact Joseph E. Levi, Esq. via email at jlevi@levikorsinsky.com or by telephone at (212) 363-7500.
CASE DETAILS: According to the complaint, on March 7, 2024, MongoDB reported strong Q4 2024 results and then announced lower than expected full-year guidance for 2025. MongoDB attributed it to the Company’s change in its “sales incentive structure” which led to a decrease in revenue related to “unused commitments and multi-year licensing deals.” Following this news, MongoDB’s stock price fell by $28.59 per share to close at $383.42 per share. Later, on May 30, 2024, MongoDB further lowered its guidance for the full year 2025 attributing it to “macro impacting consumption growth.” Analysts commenting on the reduced guidance questioned if changes made to the Company’s marketing strategy “led to change in customer behavior and usage patterns.” Following this news, MongoDB’s stock price fell by $73.94 per share to close at $236.06 per share.
WHAT’S NEXT? If you suffered a loss in MongoDB during the relevant time frame, you have until September 9, 2024 to request that the Court appoint you as lead plaintiff. Your ability to share in any recovery doesn’t require that you serve as a lead plaintiff.
NO COST TO YOU: If you are a class member, you may be entitled to compensation without payment of any out-of-pocket costs or fees. There is no cost or obligation to participate.
WHY LEVI & KORSINSKY: Over the past 20 years, the team at Levi & Korsinsky has secured hundreds of millions of dollars for aggrieved shareholders and built a track record of winning high-stakes cases. Our firm has extensive expertise representing investors in complex securities litigation and a team of over 70 employees to serve our clients. For seven years in a row, Levi & Korsinsky has ranked in ISS Securities Class Action Services’ Top 50 Report as one of the top securities litigation firms in the United States.
CONTACT:
Levi & Korsinsky, LLP
Joseph E. Levi, Esq.
Ed Korsinsky, Esq.
33 Whitehall Street, 17th Floor
New York, NY 10004
jlevi@levikorsinsky.com
Tel: (212) 363-7500
Fax: (212) 363-7171
www.zlk.com
View original content to download multimedia:https://www.prnewswire.com/news-releases/september-9-2024-deadline-contact-levi–korsinsky-to-join-class-action-suit-against-mdb-302213006.html
SOURCE Levi & Korsinsky, LLP
Article originally posted on mongodb google news. Visit mongodb google news
MMS • Alex Cruikshank
Article originally posted on InfoQ. Visit InfoQ
Transcript
Cruikshank: A long time ago, just a little bit after The Muppet Show left the air, I was a kid and I decided I wanted to learn how to program computers. I started building a few games. I started making a few small applications. As I was doing this, and learning how to program on my own, I came up with one simple rule that it’s really helped me throughout my entire programming career. That is, computers are dumb. They’re really dumb, they don’t know what to do. You got to tell them what to do, and then they execute exactly what you say. Then you’d have to tell them precisely what to do next. The other thing that computers are really bad at is interacting with humans, which is sad, because that’s actually what we usually want to use computers for. When you want a computer to interact with a human, you end up having to tell it exactly what to say in your program. Then when you want the human to respond, you have to narrow the options, so that your program is going to know what it’s going to say. Then you still have to do a lot of work to get the input and capture it in the right way. The computer can interact with humans, but it’s like a puppet, there’s always a programmer behind it that’s manipulating it, and making it do that interaction.
Conversational UI, and Generative AI (GenAI)
A few years later, about 10 years ago, maybe not quite that much, these conversational UIs came out. There’s Alexa, and Siri, and Google Home. Now computers are actually pretty good at interacting with humans. You could speak to them, and they could speak back. If you’ve ever programmed a conversational UI, what’s actually going on is it understands your words, and you get all the words, but you still have to put in all the sentence structures, basically all the different ways that they might say the thing you want. You have to put in all the synonyms that you might say. You have to anticipate everything. Of course, when it responds, it’s still your program responding exactly the way you want it to. It’s still that puppet that’s in the background. You still have to program it. The programmers still manipulate it in the same way.
This year, things changed. Now that puppet, it’s talking on its own. There’s no programmer there, it’s just a bunch of numbers. It’s talking back, and it’s interacting with humans really well. It’s not entirely dumb. As a programmer, I find this amazing, and exciting, and a little terrifying. It’s definitely going to change the way we think about writing software entirely. That’s not all. When you think about it, think about all the communication that goes on in your business, think about like, how much of that communication is mediated by computers? We got Slack. We got email. This presentation is done on a computer. Programming, that’s a form of communication. Almost all our communication is mediated by a computer some way. Now think about what percentage of your business processes rely on that form of communication. It’s probably all of them. When you think about how all those processes now with generative AI can be improved, made more efficient, and augmented with generative AI, then you can start to get an idea of the transformation that we’re facing over the next few years, the scale of it. I think we all should be amazed and excited and a little terrified.
Profile, and Outline
I’m Alex Cruikshank. I’m going to talk to you about generative AI and organizational resilience. I am a product engineer at West Monroe. For the last year, I’ve been working with AI Lab. The AI Lab, we spend a lot of time working with our clients to figure out solutions for them to use generative AI and how to do that. We also spend a lot of time figuring out how to build solutions for ourselves and how to make our own work at West Monroe more efficient. West Monroe, we’re a consultancy, and we work with a lot of private equity firms. Those private equity firms have a lot of portfolio companies, and we end up talking to those portfolio companies, their CEOs, their CIOs, their CFOs, about what the future looks like with generative AI. What they’re doing. How they’re coming up with their solutions. How they’re trying to stay resilient with this transformation that we all know is going to happen. I’m going to talk to you a little bit about what we talk about in those meetings.
The Threat
First, I’m going to talk about the threat. By threat, I mean the transformation. I’m going to put this stat up here. Up to 3.3% annual increase in global productivity due to generative AI, that’s across the entire economy. This is what analysts and economists are predicting. There’s a lot of stats that I could put up here to get the scale of the thing, they’re all made up. This number is made up too, but it’s not crazy. The reason why it’s not crazy is because if you look at the 2000s, you’ll see that economists believe that a number roughly like this, is the productivity that was gained by the internet, by all the startups and all the web companies coming into play. Basically, when you think about this number, this is like a small financial crisis and a dip in the housing market, and gas prices rising. You can have all those things and still have a good economy. If this productivity comes to pass because of generative AI, it’s a really good thing for the economy. It’s all coming from transformation in our business processes. It’s all coming from efficiency. That’s all this can be. At the end of the day, this is a mountain of change that we’re looking at.
This is another analysis. This is from McKinsey, and they were looking at job automation. Basically, they’re dividing job by education levels. At the bottom, you’d have no high school degree. At the top, you have master’s or PhD. They’re talking about how much automation there’s going to be, with or without generative AI. The dark blue at the bottom, that’s without generative AI, and the light blue at the top, that’s with generative AI. You can see that there’s going to be a lot of automation no matter what. With generative AI, suddenly, it’s a great equalizer. Suddenly, all the jobs are going to get automated. Definitely, generative AI is more automating those higher skilled jobs, the ones that require more education. As we think about automation, some of the jobs we were not really worried about a couple years ago, are now looking a little shaky.
Also, I want to talk about the character of this transformation. You can’t expect generative AI to just hit one department within the enterprise. Generative AI, it’s going to affect all the communication within the enterprise. Any place there’s communication, there’s going to be opportunities to make it more efficient with generative AI, which means you’re going to have lots of small initiatives across the entire enterprise. No one’s exempt. It’s going to be transformation by a thousand cuts. Of course, every industry is going to be a little different. We’ve been talking with manufacturing companies, retail, finance, insurance, healthcare, all these companies, they all have different challenges. They all have different things they want to solve with generative AI right now. They also have a lot of things that are the same too. The entertainment industry right now is in the news for AI, they definitely have a lot of big challenges with AI.
I want to talk about software, just because I think a lot of us are in software. It’s definitely close to my heart. It also was where, potentially, changes in AI could happen a little bit sooner. At West Monroe, we did our own study using GitHub Copilot to see how much it would improve our developers’ performance. It turns out, developers were getting a 22% gain in productivity. If you talk to Microsoft or GitHub, they’re going to say 50%, but they’re a little biased. We’re going to stick with the 22% number, but still, that’s a huge gain in productivity, that’s like 5, 4 developers going free. If you think about the frontend development, generative AI is really good at talking to people. Computers are now really good at interacting with people. A lot of the work that we do when we build our frontends is to make that communication possible between humans and computers. We’re spending a lot of time building UI. There’s a question of, just do we need to do as much of that now that we have AI? It’s not entirely clear, but it seems likely that some of those, we just don’t need as much of that work, and that work is going to have to go elsewhere.
Same with design. I think, we’re not seeing a lot of great solutions for doing UX design right now. We see a lot of people trying, and trying to make things happen. Design has really been automated for a long time. With design systems and component libraries, it’s a lot easier to build a really good-looking, good working site without a designer. It’s not hard to imagine in a year or so, that generative AI is going to be able to put together all the parts and build a really great experience without much effort, just by explaining what you want.
The Timeline
Now I want to talk about the timeline a little bit. Before I do, I want to start with this quote, because this is my favorite quote of all time. This is a William Gibson quote, “The future is already here, it’s just unevenly distributed.” What this is talking about is, any future that you can imagine, any technology future that you can imagine, it’s probably true that the technology for it already exists somewhere, it just hasn’t spread out, because we don’t know how to use it well. The market conditions aren’t right, or maybe people are just locked in. I like to think about this quote every time I get impatient for our future, that’s flying cars and pet robots. Then I just think, those things actually do exist, they’re just really expensive and scary right now.
No crystal ball for how the transition is going to play out, how long it’s going to take. We can look at the past and get an idea from the way the internet grew. When you think about e-commerce, and streaming, and social media, these things are just part of our lives now. They’ve really changed the way we live our lives. That transformation has happened. We’ve been completely altered by that technology. It didn’t happen overnight. It took a long time. The technology existed many years ago for the kinds of things we had for the most part. It took a while for people to get used to it, for people to figure out how to make it spread. We envision the same thing for AI. In fact, we can just take some of those curves and apply it to AI. We know things are underway right now, like I was talking about earlier with GitHub Copilot. Code generation is a thing that we can use right now, and delivers productivity. It’s production ready. ChatGPT obviously is out there, and so people are using that to automate in the office, plus all these products are coming out that have AI added to them.
We’re now looking at like, how do we automate support? How do we do knowledge management better? Products are coming up for that. There’s projects that we’re working on with our clients around that. That stuff’s all happening. All these things are going to have their own adoption curve. They’re all going to take a while before they really become transformative. Overall, generative AI is going to be the product of all those smaller transformations. I don’t think there’s going to be much of a transformation this year, even though there’s so much hype. Everyone is just still figuring things out. Just here and there, people are starting to get a little disillusioned, so you know the hype curve is working. It’s taking time, so really, 2 to 3 years probably before we see some real transformation in industries. Then, 10 years from now maybe we’re going to look back at this time, pre-generative AI, and it’s going to seem like a strange place. That’s speculation.
Staying Resilient
How do we stay resilient in the face of all this change that probably is going to happen, especially when we don’t really know what it looks like exactly? Always, if you want to stay resilient, you want to be flexible. I think with generative AI right now it’s a balancing act. You can’t just say no. You can’t resist it. You can’t ignore it, because eventually your competitors are going to overwhelm you. Your employees may leave. We’re talking about your business processes. Your business processes that are probably working right now, and we can’t just go through and upend and change all the business process to be AI optimized, because we don’t know that they’re going to work after we do that. We need to have a balance. We need to be gradual. Like I said, I think we have time. Here’s the first idea. We should let people automate their own jobs. People know what their job is. They know what they need to do. They know the tedious parts of it, and what needs to be automated. The thing is, generative AI is the most democratic technology, at least since the spreadsheet. It’s not hard to use. You just talk to it, and it talks back. It’s possible for everyone to start automating. The only thing to do that, you have to let people actually use AI. Maybe for some of you, this is obvious that you use generative AI at work, on work information. Most companies are struggling with this idea, and for good reason. It’s like you can’t just ship sensitive information to OpenAI, without breaking compliance rules, or at least your security rules within the company. You have to find ways around that.
Unfortunately, there’s a lot of good options right now. Amazon just partnered with Anthropic, which means all three of the major cloud platforms now have a generative AI solution associated with them. What that means is, if you are storing your sensitive, private data on the cloud, there’s no real reason why you shouldn’t be able to use AI, in that same cloud with that sensitive information. It’s going into the same place and coming back from the same place so it should be ok. This is a really positive development, as far as I’m concerned. I was actually talking about this very subject to a bunch of CFOs a couple weeks ago. I said this, and there was a chief security officer that almost knocked me off the stage. Came to the computer and said, “We got to take this careful, you got to be slow. These hackers are using generative AI to do phishing attempts.” I was like, are you worried that your employees are going to start hacking your company, and that they’re going to use your corporate account to do it? There’s a lot of fear out there. There’s a lot of distrust. A lot of it’s rational, and a lot of it’s not. Just keep it in mind and just try to be sane about it. Hopefully, we can all get using AI a lot quicker.
Another idea, build AI literacy within the company. Like I said, generative AI, it’s democratic. It’s very easy to use, but just because it’s easy to use doesn’t mean everyone’s good at it right when they start. There’s a lot of things that you actually get better at as you start to use it. There’s figuring out what kinds of tasks are good with AI, and what aren’t. Figuring out how to word your prompt, so you get better results. Most importantly, how do you keep it from hallucinating? These are all things that you learn the more you work with it. If you give people access to it, they’re going to figure it out. If you can provide training, not only are they going to get there faster, but you can also start to signal that it is ok to use it at work and maybe even encourage to use it at work.
This is a big one for me, you should collect and share your prompts. You can do it in a wiki. You can do it in your content management system. At West Monroe, we built an application that allows people to use our sanctioned AI, and also store prompts next to it and use those prompts. Even if you’re just putting it in a shared spreadsheet, that’s still great. You might want to consider having a role like a prompt librarian to curate those and highlight the ones that are working well, and maybe tweak some prompts so that they work a little bit better. Obviously, if you’re sharing prompts, you are saving people time. They don’t have to write the prompts themselves. You’re also helping to build AI literacy because people can look at other people’s prompts and see how they’re doing things and figure out how to do it better. This is the thing I really love about it. When people are submitting their prompts, what they’re really doing is documenting these obscure business processes that you may not know about, and that these people really want automated. That’s just another way to build a little bit of resiliency.
The other thing, that survey that we did, developers gained a lot of productivity. The one thing that we really saw was, 100% of the developers loved it. They all said that they enjoyed working with it. A lot of them said, they would never go back to not working with it. Giving developers Copilot, or some other coding assistant is not just a productivity tool, it’s also going to help you with retention, and morale.
Leaning In
Those were some basic, organic, let’s just let the AI in and build our tolerance to it, get ready for transformations in the future. We’re all in different places in our AI journey. Sometimes we want to lean in a little bit. Sometimes we need to have cost savings or somehow take more advantage of generative AI. We are working with a lot of clients that are doing that right now, and we are running into a lot of problems. I want to talk to you a little bit about how to avoid some of those. The main thing I want everyone to understand is that, you can’t understand a person’s job by understanding their job description. Every person brings a lot more value to their job than you would think, and they bring it in little ways. People are constantly working around problems. They’re constantly sharing how they worked around those problems. They’re innovating. They’re also bringing empathy to their job. These are all things that AI just is not capable of doing right now. The AI can often do the job description, but often the job description is not enough to do the job, and you really need a human to do that.
An example of this, I was working on a chatbot a little while ago, it was for an insurance company, it was to give coverage advice. For esoteric reasons, when I was testing it, I had to enter in, “I think I’m pregnant.” I typed in, “I think I’m pregnant,” and it would always respond, “Congratulations, you’re covered for blah, blah, blah.” I’m like, I don’t know, this is a congratulations moment. I went in, I tweaked the prompt a little bit. I said, “I think I’m pregnant.” It said, “I’m sorry to hear that.” I was like, that’s worse. Trying to explain that context, you can’t to an AI. It’s like that subtle social situation is probably just a little bit beyond it. You got to be careful about those little things.
This is the approach that we would like people to take to automating jobs. We want to take a product approach. The first thing you do is you want to learn from the workers that are there, not what you think the workers are doing, but what are the workers actually doing. Then when you build, you don’t want to automate, you want to augment. The nice thing is, anything you build to augment is going to be on the path to automation. You build tools. Give those tools to people, let them use those tools. Learn about how well it’s going, and then learn how to build efficiency with those tools. As you’re building in efficiency, it may be that you grow and don’t need to hire, or maybe people leave, or whatever. Maybe you just end up with all the productivity gains you’re looking for, without ever needing to fully automate, and you still have the human in the loop, which is nice. Maybe you do still need to automate. Then you just need to take that next step and go ahead and finish it by learning, where you need to do that.
The Uncanny Valley
I’m going to talk a little bit about the uncanny valley. The concept of the uncanny valley is from animation and robotics. It’s the idea that if you have a humanoid character, as it gets more human-like, close to a human, it gets more relatable up to a point, and then as it gets close to a human but not quite believable, suddenly, it reverses and it becomes really creepy, like these mannequins. A similar thing happens with AI if you use a chatbot. If you say to someone that they’re going to be talking to an AI, a lot of times they’re just going to refuse, they want to talk to a human. If you don’t tell them and put them in an experience that looks like they’re talking to a human, they will quickly just determine that they’re not talking to a human, and then they’re going to get angry. These are the uncanny valley effects that we have to watch out for. If they get angry, that’s really bad, that can damage your brand. It’s definitely going to create a bad customer experience. You just don’t want to do that.
The solution to the uncanny valley, is you just want to stay out of the valley. You don’t ever want to get to humans. You want to pull back a little bit, make things a little bit cartoony. You can do the same thing with a chatbot. One of the easy things you can do is have it stop using I as its pronoun, and start having it use we. It’s the voice of the company that is talking. You’re not trying to suggest this as a human or an individual that’s talking. Some other things you can do is, just don’t make it look like a chat, just make it look a little bit more like a search and have it return results. Maybe they’re summarizing process the way that a chatbot would. Then also have another prompt that will allow you to expand on your search. It ends up being effectively the same thing as a chat but it doesn’t look like a chat, it’s a cartoony version of a chat. Ideally, it keeps people from being as creeped out.
Conclusion
Generative AI is going to change everything. It’s going to take years, though. We should prepare by making sure all our employees are AI literate. When we automate our jobs, we should make sure that we are thinking about the human element and really taking care of when we do that.
Questions and Answers
Participant 1: I’ve been thinking about this a lot, and two things I want you to talk about. One is, the different testing skills we’re going to need to be able to write that whole thing, looking at the three pieces. Then the other one was, my observation is that, one thing you didn’t say, which I wish you had got to [inaudible 00:27:41] now, is the approachability of this technology. A year ago, maybe, you had to be like this data scientist, but today, it’s really approachable. I think change is going to accelerate. I don’t know if you want to talk about the development?
Cruikshank: First thing is testing. I agree, testing is really hard with generative AI. It’s non-deterministic. It can say different things every time. It’s hard to evaluate what’s a good answer versus not. It’s pretty subjective. I actually have written a tool to test bench different responses from chatbots, so at least a human can compare them over time. You make a subtle change to a prompt, it allows you to evaluate it and judge it, and then maybe you can run all the responses again, and see if it works on all those. Still, it’s not easy. I think it’s only going to really be solved by having another AI evaluate the responses. I don’t think we’re really there yet. With the tools, they don’t exist, but I know they’re coming really quickly. As far as the approachability, I totally agree. I think it is the most approachable technology I’ve seen in a long time. It’s interesting, because I think it’s really not the technologists that are leading right now. It’s like everyone has dove into generative AI, to ChatGPT, and they’re figuring how to use it. I think all the programmers and product people are just trying to catch up and figure out how they can take advantage of it, too.
Participant 2: You’ve talked about automation, and I’m just curious if you have thoughts about dealing with our workforce asking or even talking about automation, and people feel like, “That’s my job. What would I do next?” In the context of resilience in our organizations, what are your thoughts about what we do with that freed-up overhead? Then maybe related, you said this is exciting, but also freaks us out. I think, I’ve said the same thing. Is it for those reasons, or do you have other reasons for that?
Cruikshank: First of all, what to do with that overhead, I think is a big problem. It’s one of the reasons why I’m saying we should be a little scared. We should be figuring this out. I think one of the things with building that AI literacy is essentially allowing people to retool a little bit, and maybe some of these jobs are going to go away, but they’re going to be able to find new, maybe AI assisted jobs that are going to be better, and also more valuable. The thing is, people are going to want that. People are not going to want to do the jobs that are going to get automated away. The fact that they can be automated means they’re tedious in the first place. Hopefully, people are looking at that. I do think that not everyone’s going to take the steps that they need to, to stay ahead of it. There is going to be automation. It’s going to happen, one way or another. You don’t get those productivity gains without people getting essentially automated out of jobs. We know that when that happens, people end up at other jobs. Overall, it’s a good thing for everyone. Everyone gets a little richer. It does cause a lot of stress when people lose their jobs. I think everyone should be trying to prepare for that.
I think that is why we should be a little afraid. I don’t think we should be afraid of the AI. I’m not one of those people that think AI is going to take over the world or anything. Just like when you work with it, you realize that it doesn’t have that sense of agency right now. Maybe something else happens in the future, and it’s going to be scary, but it’s not scary now. When I say it’s frightening, it’s just frightening because it just never seemed like this would happen. That computers would be capable of doing this thing. It’s a little creepy, because, yes, this thing that seemed inanimate before is now animate. It’s also a little creepy because, yes, it’s going to disrupt a lot of lives, it’s going to disrupt a lot of businesses. Change is always scary. It’s not necessarily bad, it’s just scary.
Participant 3: Have you ever recommended like comparing different GenAI tools like Bard and [inaudible 00:33:11].
Cruikshank: Is the question, what’s the difference between these different models?
Participant 3: What is the comparison? If you have to build something or recommend something, should that be, GenAI models don’t exceed the limits of your ethics and you don’t have sarcastic language regarding the responses, [inaudible 00:33:55], copyrights, things like that, because they do it.
Cruikshank: You’re talking about guardrails. It’s nice that, yes, Anthropic, they’ve put a lot of fine-tuning into it to make sure that it will not do that. I haven’t actually tried it to know how well it does with that. The best way to avoid the AI doing offensive things is just try to stay out of the realm of where things can be offensive. Don’t ask it to be funny. That will almost always be offensive. Just ask it to respond to a question as succinctly as it can. Generally, I think all the big platforms do well with that. I certainly haven’t seen any problems. If you’re worried about it, you could certainly put a standard profanity filter on the end and could even use that as a guard, and have it try to regenerate the response. I don’t think profanity is the issue. I don’t think that’s ever really going to be a problem. It’s more of the subtle, offensive stuff that is going to be a little bit harder to track. I think one of the things you can do is put an intent filter on the front, so every time anyone asks for something from an LLM, you can have an LLM ask, is what they’re asking appropriate? If it’s not appropriate, you can steer them away from that question. If it is, you can have them go on. That’s one way to deal with it. I think if you can just rely on Anthropic, or OpenAI, OpenAI is pretty good about it. It’s not maybe perfect, but rely on them to have good responses, that’s definitely going to be the easiest.
Participant 4: You’re talking about AI replacing people’s jobs, potentially. Is that a reality yet? Have you seen these logical yes respond if you ask a question? Have you actually seen that being done?
Cruikshank: I’ve seen it being tried. I’ve actually seen it being tried and failed. I think the thing is, there are some very low-skilled jobs, especially around support, and customer service, that are people interacting with customers, and they’re really expensive, and people want to stop paying for that. They’ve definitely tried to do that with AI. It’s just harder than it looks for a lot of reasons. Especially, if you’re talking about support, people end up building a mental model of what they’re talking about. Even if the AI has access to all the documentation, and all the information, it can’t make the leaps that it needs to make to really make that happen. We were talking about just general customer service. You have to watch out about those little subtle cultural issues, the social factors that maybe the AI doesn’t know, because companies can get in trouble there. A lot of times they don’t care. They just need something cheaper, or they don’t need it to be good. Then you run into the issue of maybe making your customers angry, because they don’t want to talk to an AI.
Participant 5: I’d like to ask you about employee training. A lot of times these TA jobs are jobs that are entry level, and they’re still learning the ropes. In order to be creative, they have to understand the domain first. In a world where we’re automating the TA specialist job, how are we going to train people to be able to be creative and work with AI?
Cruikshank: I don’t know if it takes that much creativity. I think it takes a little bit of practice. One of the nice things is the AIs actually provide a little bit of the creativity. You can ask the AI, what should I be doing with AI right now? It will give you a decent answer. I think it’s really more a matter of getting the experience with it, and building some comfort with it, and putting in a little effort to figure out, how can you automate things, how to get used to it. One of the slides I showed was, it’s not just the low skill, low education jobs that we have to worry about now. Everyone is talking right now about how paralegals are going to go away. It’s like these AIs, they know law back and forth. That’s mostly what a paralegal does, and so there’s no reason to have them around. I heard that one day, and the very next day, I was talking to a paralegal and found out that 95% of a paralegal’s job is making copies. That’s something that ChatGPT is never going to do. There’s tedious things that you do in your job that maybe the AI can’t replace, and there’s other jobs that people have to worry a little bit more, and those are actually maybe the higher skill jobs. It’s really right now, to be ready for it, is just to understand, how much of your job can the AI do right now? If it’s a lot, maybe you should think about another job. If it’s not, then maybe you’re safe for a while.
Participant 6: You mentioned a couple times that people don’t want to talk to AI. Do you think that would change over time as people start to use things like ChatGPT, because that will change the mindset as well, and everything.
Cruikshank: Yes, absolutely. I think it’s going to change. It’s going to become normalized, and people are going to get used to it. You’re right, lots of people are using ChatGPT, and it behaves like an individual. People are not getting creeped out about that. Those are early adopters. Early adopters are generally just more open to everything. When you’re talking about your support customers, they’re the people that really are unlikely to be happy when they find they’re talking to an AI. I do think it’s going to be fine in the end. You can also look at texting. We’ve been able to do voice texting for a long time, and you go around and you see a lot of people doing that. I’m just not one of them. A lot of people still want to type it, maybe because they don’t want people to hear them or whatever. That’s the future is unevenly distributed, kind of thing. Some people are going to be very used to it and some people are just never going to get used to the idea of talking to an AI.
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MMS • Olga Kubassova
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Transcript:
Shane Hastie: Good day, folks. This is Shane Hastie for the InfoQ Engineering Culture Podcast. Today, I’m sitting down with Dr. Olga Kubassova. We are going to talk about her journey of founding and growing an engineering organization. Olga, welcome. Thanks for taking the time to talk to us today.
Dr. Olga Kubassova: Thank you very much for inviting.
Shane Hastie: So, my normal starting point is, who’s Olga?
Introductions [00:50]
Dr. Olga Kubassova: Excellent starting point. So, I am president of Image Analysis Group. I’m engineer by background. I did my master in mathematics, my second master in computer science, my PhDs in computer science. That was the background with which I started the company. I was growing it for now 15 years, and we are moving rapidly from being a startup to a scaleup. So, I suppose that defines my professional journey.
Shane Hastie: So, 15 years ago, founding an engineering company in image analysis, what was the gap? What’s the opportunity?
The opportunity in the marketplace [01:32]
Dr. Olga Kubassova: So, 15 years ago, radiology in drug development was a tool, but it was a bit of a blunt tool, to be honest. There were many smart PhDs and computer scientists applying their skills to develop novel algorithms for processing of the imaging data. And for those who are not familiar, for instance, MRI, CT, ultrasound, anything which is medical imaging. But by the time that processing or those methodology would get to clinical trials, they would kind of diminish in complexity. And at the end, clinical trials were done using pretty much radiology review. So, you would place an image in front of a radiologist and that would be described to say, “Okay, there is a tumor,” or, “There is a change.” Whereas we, engineers, are used to measuring things. So, that was an obvious gap.
My own PhD was in understanding medical imaging quantification for inflammation. So, inflammation is a driver behind many diseases. And when I showed results of the scientific research to radiologists, they were saying, “Oh, please, just don’t stop. Just keep going. Because if you stop, we go backwards.” So, with that kind of model, I started the company. And literally, my friends, who were with me in my PhD, became my first customers. Because, obviously, somebody had to buy barely working software at some point, so we could survive. And that was a real gap. And even till this day, it’s fascinating for me to see how many novel methodologies come every day from academia, from smaller companies.
But it’s incredibly difficult to break into clinical trial market, simply because the market is very specific, the sale process, very specific. Innovation acceptance is also specific. You have to know how to speak about innovation and not make it scary, but make it usable and useful. So, for 15 years, we’ve been, first, designing our own methodologies and using AI, using quantitative methods, using everything known to an engineer to build better tools. And then, bringing them in a compliant way into clinical trials. So, we figured out that having our own platform technology, DYNAMIKA, allowed us to manage data within the trial, and then also deploy something which would be of real value to a drug development company.
Shane Hastie: So, that was the market opportunity, the gap. Take those engineering skills into the medical science and drug development space. You said you started literally with yourself, and you had a group of clients. What did you do to grow from one person to a startup? And then, we’ll talk further about the scaleup.
Growing from a single person to a startup [04:30]
Dr. Olga Kubassova: It’s very interesting for an engineer to start a company. First of all, and probably the most interesting discovery, you probably have to forget your engineering skills to a level, on two levels. One is, when you’re speaking to the customer, you have to be much less engineering. You have to be customer-focused and centric around their problem. Too technical does not sell. But secondly, obviously, the first person I hired was somebody who can write software, because I understood that that’s what we need. But as soon as you hire the first person, you realize that you need to pay them salary, because they have family or whatever. And you become a natural business person in your own business.
I don’t know how other engineers position themselves, but for me, it was obvious that it’s easier to hire good engineers and good salespeople. Because to explain to someone how the product may work in the future, it’s very difficult. And they have to translate that message to the customer. So, you become your own advocate, you become your own evangelist. You go out and learn how to speak to people. I do remember writing a lot of emails. And honestly, for the first six to 12 months, I think every day you think, “Oh, my God, am I wasting my time? Is this going to fly? Is it for real?” In my particular case, I honestly got to the point where I thought, “Okay, I really have no more energy writing this long, long emails explaining why this might be useful to everyone. I’m going to close the business.”
And then, literally within days of that thought, which was really going on in my head, I was selected as Entrepreneur of the Year by an organization called Yorkshire Forward. And I thought, “Okay, I cannot, right now, foreclose the business. I’ll get the award, then I’ll wait for a little bit, so it’s not embarrassing, then I close the business.” And then, as soon as I got this award, the publicity actually and the awareness really was there. And my first customer came to be Abbott, one of the largest pharmaceutical companies developing drugs at that time for inflammatory rheumatoid arthritis. And they were the ones who bought the software and they bought the vision, and they were an amazing partner for two years. And soon, of course, if you have one customer, the stream of customers followed.
So, we were lucky to work with pretty much every pharmaceutical company which was in the space of inflammation. Until this day, being a player in inflammation is critically important. So, inflammatory autoimmune diseases, they stay with your body throughout your life. So, it’s a chronic disease. It’s very often, so you’ll always have a stream of activities, stream of new drugs, stream of new innovation. And so, then, became our pillar for the business.
Shane Hastie: So, you spoke about employing a software engineer, somebody to write the code at the beginning. As a groundbreaking, leading-edge technology organization, obviously you grew to many more than one software engineers. What did you need to do from a team culture perspective to engage and keep people on board?
Trust and accountability are foundations for great engineering culture [07:54]
Dr. Olga Kubassova It’s a very good question. Obviously, you do not build a groundbreaking, versatile technology at your first go, at your first version. So, now, DYNAMIKA is on version seven, and we’ve been building it for 15 years. And what we had as DYNAMIKA version one is dramatically different. Because if some of you remember, cloud happened in about 2015. So, I was the one explaining to people why cloud is way much better than installing software on your computers. And it’s incredible how you have to have the culture of innovation within your team. Because it was my engineering team who came to me and told me that, “Time to completely redesign the software. You see this perfectly working software? That’s not going to be useful in a year time.”
And you have to trust your people to really make those strong engineering decisions, which allow your company to progress. Because, of course, as a CEO, you don’t see the depths of technological innovation. You are aware and it’s important to surround yourself with people who are aware, but you also need to trust. So, for me, from a very first engineer, I rely on people knowing engineering better than I do. And unless you can really place your faith in people who are surrounding you and trust them explicitly, you cannot progress the innovation. So, to me the culture of innovation is very important.
Accountability is probably another critical quality for any business to grow. Because you can’t grow unless you split your tasks. And again, you know that that person owns it. So, if somebody tells you, “I own it,” you can’t go and check. You don’t have time, especially in a fast-growth environment. From a startup or from a zero-people to a startup, you don’t have that lay of management over someone. So, it’s a self-mentioned in many ways. So, if someone owns a task, they are the owner, they are the manager, they are the checker, and they are the controller of everything that’s going to happen there. And you rely on your people absolutely 100%.
Shane Hastie: And growing into that successful startup and now scaling it, what’s changing?
Process becomes a key element as the organisation scales up [10:21]
Dr. Olga Kubassova: So, that’s a fascinating time for the business. As a startup, as I said, you rely on every individual. An individual is the bearer of news, of accountability, of innovation, and the path forward in that particular direction. As a scaleup, you cannot rely on individual. You have to rely on the process, which actually powers you to bring more than one individual and plug them in. And they start being functioning within a very short period of time.
When you’re a startup, you really don’t consider that there is life outside the business. I think if someone wants to start a business, they have to forget about their life for the foreseeable future, few years for sure. As a scaleup, you realize that the team which surrounds you actually will expect work-life balance. For me, obviously, it was a discovery that somebody wants life outside the business. Seriously, what are you doing in my business? Only kidding, but still. So, it was necessary to bring someone who understands the process, not just the essence of the task.
So, we are in the process of scaling up the business and bringing together answers which would not be an answer to an immediate problem, but an answer in the shape of a process that would lead people to find a solution. And that goes across each of the teams. So, we have engineering team, operational team, sales team, marketing team and so on, but also cross teams. Obviously, what I feel as a founder and as a person who does it all, it’s so painfully slow.
Because, first, you have to build the process. And honestly to build the process takes several iterations, just like you build your software, right? So, version one may not be perfect. Somebody has to take accountability for writing of the process, training people on the process, how all of this is actually going to work, make sure that they all follow the process. And that for entrepreneur very often feels very painful. So, I expect that within a few months, we have a book of processes and we can move with speed.
But I think the first point, which makes me realize that startup is very different from scaleup, culturally, it’s, again, very different. Accountability comes in a very different way. Accountability is no longer about one person working long hours. Accountability is now one person is trustworthy to follow the process that was put in place. And actually, innovation in the process is also an important point. Because you also trust your people to challenge the process and to say, “That process doesn’t work for me, and this process could be improved.”
And I think that’s the next step when you actually have an established set of processes, to make sure that you’re still innovating, that you’re not stale in your own process book. Because as you know, often you hear in big organizations, “That’s not the way how we do things.” And that’s, I think, what kills the innovation. Because then, you need disruptors there, who actually could say, “Well, that wasn’t how we do things. It’s now how we’re doing it right now.”
Shane Hastie: So, keeping innovation flowing while bringing in process, it almost sounds an oxymoron.
Continuing to innovate while bringing in process [13:53]
Dr. Olga Kubassova: For sure. Well, so I think you need to realize that innovation comes in many shapes and forms. For me, as an engineer, innovation right now is bringing AI, bringing automation, bringing a better way of dealing with things. But innovation within operations, within looking after your clients, bringing the same AI for better client experience. Making sure that your innovation across organization doesn’t just speak to engineering innovation, but it speaks much wider to an organization that everybody feels that they’re innovating. And the tools enable you to do so.
I find fascinating how inefficient we were in clinical trials in just moving data around from A to B. When I started the business, it was CDs sent by post. And honestly, it progressed a little bit, but not dramatically. And you think right now, we have every protocol under the sun, security, novel mechanisms, novel technologies. Can we not just make it easy to just suck the data from the scanner, throw it on the cloud, make sure the technology is doing an organization of the data? Not that easy. Because every organization, like a big hospital, would have their own book of processes.
So, innovation is all around you. You just need to recognize what innovation for one team versus another. And every day, you need to think, what’s new? What can be done better across the teams and within one team?
Shane Hastie: And culture, you’ve touched on it a few times. That shifting from the one individual who really works hard, the small team, to now we’ve got the bigger team, where we are in that scale-up phase. Is there a deliberate shift in culture?
Culture changes with context and growth [15:52]
Dr. Olga Kubassova: It’s incredible to watch actually. Because, well, first of all, I start with the obvious, the COVID culture, post-COVID culture. I used to say to people, “Unless you be in the office every day, I cannot hire you. Because I want people to be here. We are moving so fast, I want to be able to speak every day to somebody.” And I moved the business from north of England to London to have a bigger pool of candidates, so I can hire more people faster. And when I build US office, I was shocked to see that in the US they just don’t go to the office. So, I was like, “How is that possible? My team will be in the office.” And I build it that way.
COVID happened and we grew as a business actually 30% during COVID, which was very high gross, and everybody was at home. And we were figuring out how we’re going to communicate and what’s going to happen. Post-COVID, I’m still struggling to get my head around how to efficiently make people collaborate versus maintaining this work-from-home culture. And honestly, I feel probably more expensive to do the work from home than in the office, if you do it right. But then, how do you make somebody who works remotely or from home be part of your business? And I hate when people think it’s just purely transactional. The business pays me. And if somebody say they, in reference to the business, it almost like hurting me. Because it’s us. It’s not they, it’s just us. We are together on this.
How do you do it right? I think I’m starting to see a few things that we’re doing correctly. First, we’re building pride in the business. We are proud of what we do. And I think that recognition of us as a team should be stronger than physical presence. And if that stays within your soul and mind, and you feel like us and you voluntarily want to wear orange, which is our color, then we’re starting to belong together
Secondly, I think that process book, it’s probably going to help. Because you need to have efficient communication, so you can exchange ideas and recognize that many people are not extroverts. And perhaps they’re not comfortable just being thrown and asked a question at that particular second. You need to give them time to prep, time to think. And perhaps their answers are way much deeper than extroverts’ answers, but they need time to do it. So, a team call scheduled five minutes ahead of time with everybody throwing ideas will not work for everybody. So, you really have to have strong managers, who are deeply engaged with their team members, who also understand if their own team members are not all the same. And which is a good thing. You shouldn’t have all the same people.
So, understanding how the schedules are at meetings, understanding how to hear your people, I think that’s very important. I’m sure there are other little tricks and different things, so come back in here. I’ll tell you more.
Shane Hastie: So, that pride in us, the efficient communication, that diversity, you’re a woman in technology and a founder, it’s, at the least, unusual.
Sadly, being a woman founder in the technology industry is still unusual [19:27]
Dr. Olga Kubassova: Yes, unfortunately still is. What helps me is never think of myself as a woman founder in technology. I just think of myself as Olga. And if anybody has a problem with that, they can call me Dr. Olga. But many people do stop themselves from going somewhere because there is a stigma, that if you’re a woman, you’re supposed to wear pink and go this way. And it’s in our time. It’s incredible.
But I do a lot to speak to young females and to be honest, male insecurity is as high as female. So, it’s not unusual that a younger person would feel insecure about something, regardless of gender or sexual orientation, whatever other factors are there. And I think that overcoming your own concerns, what’s in your own head, is so important. And I think your team members actually are there for you to prop you up and tell you you’re fine.
I remember that when I started the business, I felt like I have to bring somebody older with me to the meetings. I was 26, and I would walk into the room of people who are way much older than me and tell them that now, we’re going to do things differently. For the first five minutes, it was just a shock reaction, so I would not get any questions to anything I would say. And it would take a minute for people to appreciate that actually, maybe I’m saying some sense.
It really helped to have people who would say to me, “You don’t need anyone. Just go and say what you think is right.” And I think now, with our teams, we have all ages, we have all genders. I’m particularly proud when I see women in engineering. Obviously, that’s just maybe a bias on my side, but it’s great. And it’s important that we all get together and address it if there is an issue. We cannot just sit there and hide from it. We just need to speak to it.
Shane Hastie: How do we start to have those conversations?
Dr. Olga Kubassova: Well, I was speaking at the QCon, and as you can imagine, the 90% of the audience is male. I think having female speakers sharing their experiences, because females are very good at emotions. There is no need to say that we are all the same, we act the same. No, we’re not. We’re different. But female strengths is often in sharing the emotions openly. And crying is not a sign of weakness. It’s actually a sign of action, or a sign of frustration. Could be anything.
Maybe male engineers would go punch something, females may cry, but it’s an expression of your passion, expression of what you think in the moment, how the moment affects you. So, if I can just understand that, that we react differently to the same problem, to me it’s understanding of both sides, understanding of that individual, how they react to the problem. Because if reaction is aggression or tears, obviously not positive. But it is a reaction, nothing else.
Second thing I would do is, I would always center conversation around an issue, or around a challenge, or around something tangible which you can address, not around an individual presenting that issue. Because it’s very important to recognize that we might see differently, but the issue remains the same. And when you win by tackling that successfully, by explaining to your teams how to deal with that, we reward people. And again, we need to recognize that different rewards appreciated by different people.
So, how would female really feel that she made a contribution? What would matter? It needs to be in a way that everybody understands that when we appreciate someone, we appreciate them for their achievements, not just because they were of particular gender. And once an understanding is there, then I think everybody can speak freer, express themselves freer, solve more issues, do not hide behind anything. Just be there, full on, 100% all the time.
Shane Hastie: Thank you. Quite a few of our audience are people who have moved relatively recently into leadership roles. For the new team leader, maybe the new entrepreneur or person thinking of becoming an entrepreneur, what advice would you give them?
Advice for new leaders [24:00]
Dr. Olga Kubassova: I think team leader versus entrepreneurs, probably different type of advice. Different advice. So, I start with the lead. I think if you need to lead someone, I always believe in leading by example. You are not perfect, but you are a leader. Somebody has chosen to believe that you are the one to lead that as a person. So, leading by example is not necessarily solving things, but being there, present, doing your best, bringing other people to help, making sure things work. That’s one of the advice from me.
You have to really feel like you, as a leader, will eat last. You will solve the most problems, you will recognize the most people. And very often, this is your recognition. Nobody is going to applaud you as a leader. You need to push your people forward, empower them, but at the same time, you need to stay behind to make sure they can do the job.
Advice for aspiring entrepreneurs [25:01]
As entrepreneur, I think it’s very different. Entrepreneurs are not necessarily leaders. They’re like self-chosen leaders. Nobody told them they’re going to lead anything. They just decided that there is a problem they’re going to tackle. I think tackling and leading are different qualities very often. Because to tackle the problem means you’re just going to hit that brick wall with all your strength and break through it. You’re probably going to hurt some people on the way, and bricks probably not going to fall in exactly the way you plan them to fall.
But as entrepreneur, you have this unique quality. So, being force of nature. Because otherwise, first of all, you don’t even recognize a problem. And secondly, if you recognize a problem, you can’t do anything about it. So, entrepreneurs, if somebody is thinking of being entrepreneur, I think it’s worth checking if they’re ready for rejection, they’re ready for not immediate success.
There are great stories of Facebook or Google or OpenAI, or anything like that of overnight entrepreneurs. It’s never an overnight. It’s always after 20 years of hard work. Finally, overnight, you become a success. And I think entrepreneurs versus leaders is almost a question mark for me. I hired so many great leaders, and I knew that I’m not the right person to lead in many of the different departments. My passion is not necessarily to lead. My passion is about solving things.
And I think when you know yourself better, you probably can position yourself right in your own company. It takes time to get to know yourself, because that’s very difficult, to be self-critical, obviously, especially for entrepreneur who know everything and do anything and solve anything themselves.
Shane Hastie: Self-awareness.
Dr. Olga Kubassova: Oh, yes, big one.
Shane Hastie: Dr. Olga, thank you very much for taking the time to talk to us today. If people want to continue the conversation, where do they find you?
Dr. Olga Kubassova: Oh, I would be delighted. LinkedIn is the best tool, so I post. And I try to speak for myself, so I don’t use extra people to post on my LinkedIn. So, everything I say is me. And they can come back with questions and comments, and let me know what they think. And I love the conversations.
Shane Hastie: Thank you so much.
Dr. Olga Kubassova: Wonderful. Thank you so much for inviting me.
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NEW ORLEANS, LA / ACCESSWIRE / August 1, 2024 / Kahn Swick & Foti, LLC (“KSF”) and KSF partner, former Attorney General of Louisiana, Charles C. Foti, Jr., remind investors that they have untilSeptember 9, 2024 to file lead plaintiff applications in a securities class action lawsuit against MongoDB, Inc. (NasdaqGM:MDB). This action is pending in the United States District Court for the Southern District of New York.
What You May Do
If you purchased securities of MongoDB and would like to discuss your legal rights and how this case might affect you and your right to recover for your economic loss, you may, without obligation or cost to you, contact KSF Managing Partner Lewis Kahn toll-free at 1-877-515-1850 or via email (lewis.kahn@ksfcounsel.com), or visit https://www.ksfcounsel.com/cases/nasdaqgm-mdb/ to learn more. If you wish to serve as a lead plaintiff in this class action, you must petition the Court by September 9, 2024.
About the Lawsuit
MongoDB and certain of its executives are charged with failing to disclose material information during the Class Period, violating federal securities laws.
On May 30, 2024, the Company released its first quarter fiscal year 2025 results, disclosing significantly reduced growth expectations and cutting fiscal year 2025 growth projections, due to the Company’s decision to change its sales incentive structure to reduce enrollment frictions, along with some allegedly unanticipated macro headwinds.
On this news, the price of MongoDB’s shares fell nearly 24%, from a closing price of $310.00 per share on May 30, 2024 to $236.06 per share on May 31, 2024.
The case is Baxter v. MongoDB, Inc., et al., 24-cv-05191.
About Kahn Swick & Foti, LLC
KSF, whose partners include former Louisiana Attorney General Charles C. Foti, Jr., is one of the nation’s premier boutique securities litigation law firms. KSF serves a variety of clients – including public institutional investors, hedge funds, money managers and retail investors – in seeking recoveries for investment losses emanating from corporate fraud or malfeasance by publicly traded companies. KSF has offices in New York, Delaware, California, Louisiana and New Jersey.
To learn more about KSF, you may visit www.ksfcounsel.com.
CONTACT:
Kahn Swick & Foti, LLC
Lewis Kahn, Managing Partner
lewis.kahn@ksfcounsel.com
1-877-515-1850
1100 Poydras St., Suite 960
New Orleans, LA 70163
SOURCE: Kahn Swick & Foti, LLC
View the original press release on accesswire.com
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MongoDB, Inc. Class Action Lawsuit
SAN DIEGO, Aug. 01, 2024 (GLOBE NEWSWIRE) — Robbins LLP reminds investors that a shareholder filed a class action on behalf of all investors who purchased or otherwise acquired MongoDB, Inc. (NASDAQ: MDB) securities between August 31, 2023 and May 30, 2024. MongoDB is an American software company that designs, develops, manufactures, and sells developer data platforms and integrated services systems through its document-oriented database program.
For more information, submit a form, email attorney Aaron Dumas, Jr., or give us a call at (800) 350-6003.
The Allegations: Robbins LLP is Investigating Allegations that MongoDB, Inc. (MDB) Misled Investors Regarding its Business Prospects
The complaint alleges that during the class period defendants disseminated materially false and misleading statements and/or concealed material adverse facts related to MongoDB’s sales force incentive restructure, including: a significant reduction in the information gathered by their sales force as to the trajectory for the new Atlas enrollments without upfront commitments; reduced pressure on new enrollments to grow; and a significant loss of revenue from unused commitments. Such statements absent these material facts caused investors to purchase MongoDB’s securities at artificially inflated prices.
The complaint continues that investors began to question the veracity of defendants’ public statements on March 7, 2024, during MongoDB’s earnings call following a same day press release announcing its fiscal year 2024 earnings. Defendants purportedly announced an anticipated near zero revenue from unused Atlas commitments in fiscal year 2025, a decrease of approximately $40 million in revenue, attributed to the Company’s decision to change their sales incentive structure to reduce enrollment frictions. Additionally, MongoDB provided estimated growth for the fiscal year 2025 of just 14% growth, compared to projected 16% for the previous year, which had resulted in an actualized 31% growth. On this news, the price of MongoDB’s common stock declined from a closing market price of $412.01 per share on March 7, 2024, to $383.42 per share on March 8, 2024.
Plaintiff alleges that notwithstanding the March 7 disclosures, defendants continued to mislead investors as they continued to create the false impression that they possessed reliable information pertaining to the Company’s projected revenue outlook and anticipated growth while also minimizing risk from seasonality and macroeconomic fluctuations.
The truth finally emerged on May 30, 2024, when MongoDB again announced significantly reduced growth expectations, this time cutting fiscal year 2025 growth projections further, again attributing the losses to the Company’s decision to change their sales incentive structure to reduce enrollment frictions, along with some allegedly unanticipated macro headwinds. On this news, the price of MongoDB’s common stock declined from $310.00 per share on May 30, 2024, to $236.06 per share on May 31, 2024, a decline of nearly 24%.
What Now: You may be eligible to participate in the class action against MongoDB, Inc. Shareholders who want to serve as lead plaintiff for the class must file their motions with the court by September 9, 2024. A lead plaintiff is a representative party who acts on behalf of other class members in directing the litigation. You do not have to participate in the case to be eligible for a recovery. If you choose to take no action, you can remain an absent class member. For more information, click here.
All representation is on a contingency fee basis. Shareholders pay no fees or expenses.
About Robbins LLP: Some law firms issuing releases about this matter do not actually litigate securities class actions; Robbins LLP does. A recognized leader in shareholder rights litigation, the attorneys and staff of Robbins LLP have been dedicated to helping shareholders recover losses, improve corporate governance structures, and hold company executives accountable for their wrongdoing since 2002. Since our inception, we have obtained over $1 billion for shareholders.
To be notified if a class action against MongoDB, Inc. settles or to receive free alerts when corporate executives engage in wrongdoing, sign up for Stock Watch today.
Attorney Advertising. Past results do not guarantee a similar outcome.
| Contact: Aaron Dumas, Jr. Robbins LLP 5060 Shoreham Pl., Ste. 300 San Diego, CA 92122 [email protected] (800) 350-6003 www.robbinsllp.com |
https://www.facebook.com/RobbinsLLP/ https://www.linkedin.com/company/robbins-llp/ |
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