#ai

AI will do your work for you but make sure you read everything because it doesn't do it right so you're going to spend twice as much time checking the AI. Don't worry about using tokens because we're going to optimize for tokens and anyway no one got to use it this week because we pushed an update and all the agents crashed.

One thing I guarantee: anyone who's good at software development is working for another company, not wells .

Im wondering if the 4 hours on the clock training we are granted per month and the AI My Agent that was announced are going to be delegated by Cisco on what we study and if we use the Agent or not.

This is getting awful now. More red tape in an AI age
Who is tired of how bad this rollout has gone? Product owners have no clue as well as STS leaders. The engineers suffer

Together with this plus GCC and stuck in PCF nothing can stop the death of the engg culture

Curious: has AI fixed all the problems yet? Or is everything still broken?

Lots of floating discussions on upcoming layoffs.
Regardless few facts to consider even you survive ...

1. You are always on the chopping block just waiting for your time
2. Oracle is always a low-payer and during this transition its going to be worse
3. Promotions are going to be night mare
4. Ratings are also getting bad (Usually in Oracle we don't care ratings much. but now we do)
5. We stick with old technologies (POJO - Plain Old Java Only)
6. AI is driven at each org. but without heads and tails. You prepare an axe to cut yourself.
7. Favoritism and Bureaucracy sits at top.
8. Job hunting takes time even you survive now. So better start now
9. Managers are always not good. They might seem sweet to you now. What happens to your colleague can happen to you tomorrow. You are just a paper cup.
10. People come for signing the confluence papers and running the meetings. But they don't come for sharing your workload and pain.

Been told OAL is too important to have any layoffs. Even if the Codex skills will automate all tasks, we will be safe unlike other teams.

Verizon cozies up to Google Cloud even more with Gemini integration.

https://www.fierce-network.com/wireless/verizon-cozies-google-cloud-even-more-gemini-integration

Unknown date. Conversational AI expansion/ they will be repurposing some roles prior to the RIF

The execs would love to run this place with zero employees, they just can't yet. But that's their goal. Not even India is safe from this. I can't wait for the AI bubble to burst and with it their dreams of bringing the actual workforce to a bare minimum. And it's only a matter of time before it happens.

Old colleagues who have left have told me they're developing AI agents at their new company that can assess inspection reports and output recommendations that are spot on in minutes. A small team of engineers doing the work that took our BTC months, without all the errors.
Anyone else hearing similar things?

I know AI is all the rage, but when I see we're looking for more than $60 billion in debt financing, I can't help but wonder how much risk is piling up. That's a huge amount of money, and if the AI bo-m slows down, I don't want the employees paying for it through more cost-cutting or pressure to hit impossible targets.

Marvell's stock pops 10% on AI chip deal that lets Google buy up to $12.2 billion in shares

• Marvell Technology stock popped on a deal for Google to buy up to $12.2 billion in shares.
• The deal is part of Google and Marvell's partnership on custom chips and includes products that "attach to the TPU ecosystem."
• Google has largely been working with Broadcom on custom chips

https://www.cnbc.com/2026/08/19/marvell-google-ai-chips.html

DE Shaw has accumulated a stake worth more than $1bn in Sysco, adding significant weight to the hedge fund’s long-standing investment in the US food distribution giant as the company seeks to accelerate growth and cut costs through AI, according to a report by Reuters.

https://www.hedgeweek.com/de-shaw-builds-1bn-plus-sysco-position/

Google agreed to pay $10 million for an enormous trove of business data from bankrupt Spirit Airlines—but the carrier’s flight attendant union is raising questions about what happens to privacy after a company goes belly up and AI swoops in.

https://www.forbes.com/sites/suzannerowankelleher/2026/08/18/google-train-ai-spirit-airlines-data/

JE leaving as CIO has me concerned. In all of O&T he seemed to be the one guy who had a vision (that wasn’t 100% AI driven).

The why is what I wanna know. Was he unhappy? Was there a rift with him at KR? Was it because of the ServiceNow disaster? Anyone know

Google AI’s analysis/prediction for Markham lab given recent past and current goings on ..

While the physical facility at Warden Ave is legally consolidated, the internal reality for the teams working there is entirely different. The lab is being aggressively hollowed out through rolling layoffs, PIPs used as exit mechanisms, and massive offshoring to India.If things continue at the current pace, the Markham lab as a major, high-value North American development hub could effectively disappear within 2 to 3 years, functioning instead as a skeleton crew or a regional customer-facing support office.The systemic gutting of the Markham site is driven by a clear operational strategy:📉 Aggressive "Workforce Rebalancing" and Shifting to IndiaResource Actions (RAs): IBM has conducted successive waves of global layoffs across late 2024, 2025, and into 2026. Hundreds of Canadian employees across Markham, Ottawa (Cognos), and Montreal have been quietly handed packages.The Cost Arbitrage Pivot: This is a clear case of "cut here, hire there". Software engineering, development, and cloud architecture roles are being systematically closed down in Markham and backfilled by a massive hiring spree in Bengaluru, Hyderabad, and South India offices. The core driver is cost arbitrage—replacing North American developer salaries with offshore engineering pools.Knowledge Transfer Demands: Multiple internal accounts reveal a strict pattern where impacted North American teams are mandated to document their processes and train their replacements in India during their notice periods to guarantee their severance.🛠️ PIPs We-ponized as Hidden ExitsForced Attrition: Performance Improvement Plans (PIPs) are increasingly being we-ponized as covert exit tools rather than true improvement pathways.The "Workforce Reset": Rather than paying out standard Canadian severance packages under Resource Actions, management is pushing more strict utilization metrics and stack-ranking to push out senior, higher-earning Markham engineers through forced attrition.🔄 The Transition to Junior/AI StaffEliminating Senior Devs: Legacy product teams (including Db2, WebSphere, and security infrastructure) are seeing senior engineering talent eroded.A Different Type of Lab: IBM's stated corporate strategy for North America has shifted away from traditional software engineering. Leadership plans to lean heavily into entry-level, junior hires whose responsibilities focus less on core coding and more on client management and supervising automated AI agents.The physical building won't vanish overnight, but the engineering heart of the Markham lab is being rapidly dismantled.

Specialized industry groups-waste of
Money w AI

Whoever (Roscoe?) is the inside source talking to the press saying a bunch of senior leaders were fired because of AI, we don't even have any good AI tools you d-mb fu-k. What a crock of sh-t.

If Dan really wants to do something good for the company, offer a package to everyone with 25 or more years of service. A lot of them are just biding their time to leave anyway. Then figure out which teams can be combined or work sourced out. It’s inevitable that Verizon will soon be under 50k employees due to AI.

The Board of Directors — Dan’s bosses — wants one thing above everything else: stronger cash flow and a much leaner Verizon. And there are really only two ways to accomplish that at scale: increase revenue and aggressively reduce costs.

That’s where AI, automation, indirect retail, and organizational consolidation come into play.

As much as we joke about AI being terrible today, we’re still in the baby stages of what this technology will eventually become. Think about where AI could be 10+ years from now after years of development, training, and integration into systems like Salesforce, POS, digital sales, customer service, and account management.

The long-term vision, in my opinion, is for significantly more of Verizon’s direct sales and service transactions to happen digitally with fewer employees involved in the process.

And that brings us to retail.

I would not be surprised if we eventually reach a point where the overwhelming majority of Verizon retail locations are operated through indirect partners rather than corporate retail. People ask why Verizon would do that, but look at the economics. Some indirect locations are already producing strong numbers while Verizon doesn't have to carry the same corporate labor and operating structure behind every store.

Why own and operate the entire distribution network if somebody else can sell your product for you?

Then there's Business.

I think a major consolidation between Mid-Market and SMB — B2B, I2B, R2B, etc. — is brewing.

Instead of maintaining all these separate channels, imagine one broader organization called Business Markets, with roles differentiated primarily by account size and customer segment. It could eventually resemble the Government model: SMB and Mid-Market account managers operating within the same broader organization, potentially rolling up through the same leadership structure.

If you're wondering why accountability conversations, performance management and PIPs suddenly seem to be getting more aggressive, I don't think that's happening in a vacuum either.

When a company knows it needs fewer employees in the future, attrition becomes valuable. Every employee who voluntarily leaves — or exits through performance management — is potentially one less severance package or position that has to be eliminated during a future restructuring.

At the same time, the company gets an opportunity to identify and preserve its strongest performers for whatever the next version of the organization looks like.

That's why I think the ultimate goal is a much leaner Verizon — potentially below 50,000 employees over time, with headcount continuing to decline as automation improves.

And here's the uncomfortable part:

Verizon probably knows exactly what it's doing.

That doesn't mean employees have to like it. It doesn't mean every decision will be executed perfectly. But from a shareholder and cash-flow perspective, there is a clear logic behind the direction.

And this isn't exclusively a Verizon story.

It's happening across corporate America.

Companies are realizing they can automate more, outsource more, consolidate departments, flatten management structures and operate with fewer employees. Meanwhile, a difficult job market gives employers something they haven't had to this degree in years: leverage.

You can quit tomorrow because you disagree with the direction of the company, but there's a large pool of qualified candidates competing for good-paying corporate positions right now. Companies know that.

So when you connect the dots — AI integration, digital sales, indirect expansion, organizational consolidation, increased performance pressure and headcount reduction — these don't necessarily look like a bunch of unrelated decisions.

They look like pieces of the same long-term strategy.

The Verizon of 2035 may still be one of the largest telecommunications companies in America.

It just might require a fraction of the people to operate it & that's just facts. Hate it or love it.

DDAT locking down claude code and cutting off use by business teams that have already been using and have built substantial workflows of value at a fraction of the cost or that DDAT probably previously told them they couldn’t do right now…or they didn’t know how to do it… the AI revolution… it’s beginning…

Apple has reportedly laid off an entire team focused on virtual reality development. This move comes as the company shifts its priorities within its spatial computing division. The restructuring suggests a temporary pause on the VR category, with a new focus on AI and smart glasses. While the VR team has been significantly reduced, work on future iterations of the Vision Pro and smart glasses is expected to continue. This indicates a strategic recalibration rather than a complete abandonment of the VR/AR space.

Cupertino, California

https://appleinsider.com/articles/26/08/20/layoffs-in-apples-vision-products-group-prove-slow-progress-in-spatial-computing

Find this funny and ironic this notification going on for months on the employee IT support slack channel. Looks like Ai agents ate going a great job after getting rid of humans.

Companies in Michigan are increasingly pointing to artificial intelligence as the reason for recent layoffs. However, experts suggest that the reality behind these workforce reductions is more complicated than just AI. While AI plays a role, other factors are also contributing to job cuts across the technology sector. This trend is evident in significant reductions at a Grand Rapids-based firm and a wider national pattern. The true drivers of these layoffs appear to be multifaceted.

Detroit, Michigan

https://www.detroitnews.com/story/business/2026/08/19/companies-cite-ai-for-layoffs-in-michigan-but-its-not-so-simple/91010735007/

The mortgage sector is anticipating more layoffs and reduced hiring due to persistently high interest rates and compressed profit margins. Lenders who expanded their workforce early in the year are now reassessing their staffing levels as refinance hopes have faded. Increased efficiency from AI and complex product mixes also contribute to the need for leaner operations. Analysts suggest that consolidation may become a more common strategy for companies struggling with profitability. This trend follows significant workforce reductions seen since the market's post-pandemic peak.

https://www.housingwire.com/articles/mortgage-layoffs-expected-to-rise-as-rates-remain-high-margins-stay-thin/

why isn't there a 20 minute AI summary? Isn't that what y-all are supposed to be donig now?

Well.. you all are fu---d based on what was just said on thebeat..

Looks like SSNC health is hiring cost center representatives at Mumbai India for the first time they are traitors to their own country. They just sent out a welcome new associates communication and I looked them up and they are in India. It’s bad enough that they are using AI now now they do not hire Americans anymore.

What is the purpose of their job? Track token usage and scold us if we use too much or not enough?

Company will use AI to layoff people based on number of hours worked not factoring furloughs into the equation. The more furloughs you are given the more likely you will be laid off.

I see an uptick in Retirements, mostly 25 to 35 years experience each. Seems like many are being replaced by first or second year BTC staff performing the job remotely.

Dependence on less experienced, less competent persons working remotely, using AI, seems like a recipe for disaster.

What are examples of disasters, or potential disasters, that you see due to this trend?

Customers are not getting answers for weeks and months,
Issues not resolved and accumulating.
They thought Ai will resolve all issues for them and replace staff.
The remaining teams are understaffed.

Anyone feeling that all of this new AI agent deployment basically means it’s going to eventually replace all of us at the ground level? That town meeting today was very uncomfortable & felt like they were dancing around that issue.

For the Cloud program, we hired significantly from JPMorgan Chase and Amazon, largely because members of the leadership team came from those organizations. This contributed to substantial budget consumption.

Now, with the new AI budget, we appear to be seeing a similar pattern within Technology—hiring senior leaders from Discover Financial at GL17 and above, while simultaneously increasing pressure on existing U.S Bank employees

Copy architectire from one project put it to ai give specifications for this project, ask it to generate architecture. Architecture ready! that's architect DINOSAURS work in fidelity paid $200k+ shamelessly.

We have all noticed, including people in neighboring departments, that all the fire and fury about AI back in the Spring has disappeared. Also, many national articles about AI buyer’s remorse and people who were laid off being rehired; many errors with AI; AI not reaping any real benefits. Also- I have heard that part 3 of that AI test has been moved back to next year (the one where they want a 6-page thing). AI=dot com bo-m and bust?

Now that AI and Big Tech are officially falling out of favor on Wall Street, how long until Jim pivots and claims his "big bet" on AI was just a victim of bad timing? Place your bets, but historically, he usually clings to a fad for about a year before quietly shuffling away.

What amazes me is how he always gets away with it. How many trends does this guy have to chase just to sit at the cool kids' table on Wall Street? Why doesn't Bill see through this? Sometimes chasing the shiny new thing doesn't pay off, to the tune of $20 billion.

First, it was autonomous vehicles Argo taxis, because every American loves to rent their car. "They'll be here tomorrow!" Then it was subscriptions. "Wait, no, energy, were an auto battery supplier now! Wait no one wants them, how about energy storage, anyone? !" And now? "Data centers and defense! That’s the ticket!" Affordable, sorry guys, that was Mr. Trump, which Jim referred to as the "return of common sense", after cursing him for stripping the EV dream no American wanted.

Does anyone remember the genius of the scooter or the inflatable bike? We're growing they exclaimed, we went from 5 employees to 500, that's progress!

We Must Act Now
Statement on AI’s Transformation of the Economy

AI may become radically more powerful over the next 10 years.
This could drive an unprecedented transformation of our economy, larger than the Industrial Revolution, but unfolding over a vastly shorter time frame. It could bring risks, including large-scale job displacement, as well as opportunities such as major gains in living standards.

Economists, policymakers and technology leaders must act now to understand the economics of transformative AI and to build the incentives, guardrails, and institutions needed to steer AI in a direction that complements humans and benefits society.

Signatories

Erik Brynjolfsson, Stanford University

Ajay Agrawal, University of Toronto

Anton Korinek, University of Virginia and Anthropic

Tom Cunningham, METR

Michael Spence, New York University*

Daron Acemoglu, MIT*

Diane Coyle, University of Cambridge

Chad Jones, Stanford University

David Autor, MIT

Joseph Stiglitz, Columbia University*

Niall Ferguson, Stanford University

Jason Furman, Harvard University

Simon Johnson, MIT*

Christopher A. Pissarides, London School of Economics*

Paul Milgrom, Stanford University*

George Akerlof, Georgetown University and University of California, Berkeley*

Philippe Aghion, INSEAD*

Dan Hendrycks, Center for AI Safety

Eric Schmidt, Former CEO of Google

Peter Howitt, Brown University*

Oliver D. Hart, Harvard University*

Bengt Holmstrom, MIT*

Alvin Roth, Stanford University*

Michael Kremer, University of Chicago*

Roger B. Myerson, University of Chicago*

Paul Krugman, Graduate Center of the City University of New York*

Ben Bernanke, Brookings Institution*

Robert J. Shiller, Yale University*

Pascual Restrepo, Yale University

Jaan Tallinn, University of Cambridge

Daniel Susskind, Gresham College

Yoshua Bengio, Université de Montréal, LawZero and Mila

Gillian Hadfield, Johns Hopkins University

Raffaella Sadun, Harvard Business School

Tyler Cowen, George Mason University

Reid Hoffman, Greylock

Wojciech Zaremba, OpenAI Foundation

David J. Deming, Harvard University

Jack Clark, Anthropic

Ronnie Chatterji, OpenAI

Dean Ball, OpenAI

Jeff Dean, Google

Joshua Gans, University of Toronto

Abhishek Nagaraj, University of California, Berkeley

Jeffrey Sachs, Columbia University

Peter McCrory, Anthropic

Alex Imas, University of Chicago

Stephanie Bell, Partnership on AI

Rebecca Finlay, Partnership on AI

Gina Raimondo, RAISE US

Yann LeCun, Advanced Machine Intelligence Labs

John McHale, University of Galway

Oskar Nordström Skans, Uppsala University

Ebehi Iyoha, Harvard Business School

Kevin Bryan, University of Toronto

Judy Chevalier, Yale University

Shannon Liu, University of Toronto

Shai Bernstein, Harvard Business School

Alexander Oettl, Emory University

Benjamin Jones, Northwestern University

Scott Stern, MIT

Hong Luo, University of Toronto

Amir Sariri, Purdue University

John List, University of Chicago

Rebecca Henderson, Harvard Business School

Ben Weidmann, University College London

Kristina McElheran, University of Toronto

Basil Halperin, University of Virginia

Christian Catalini, MIT

Rembrand Koning, Harvard Business School

Lee Lockwood, University of Virginia

Daniel Trefler, University of Toronto

Annie Liang, Northwestern University

Anders Humlum, University of Chicago

Jonathan Colmer, University of Virginia

Maria del Rio-Chanona, University College London

Janice Stein, University of Toronto

David Yanagizawa-Drott, University of Zurich

Frank Neffke, Complexity Science Hub

Eva Vivalt, University of Toronto

Doh-Shin Jeon, Toulouse School of Economics

Adam Posen, Peterson Institute for International Economics

Jakub Growiec, SGH Warsaw School of Economics

David Hémous, University of Zurich

Elliott Ash, ETH Zurich

Klaus Prettner, Vienna University of Economics and Business

Donghyun Suh, Bank of Korea

Benjamin Moll, London School of Economics

Philipp Schmidt-Dengler, University of Vienna

Olivier Blanchard, Peterson Institute for International Economics

Emilio Calvano, LUISS University of Rome

John Van Reenen, London School of Economics

Maryam Farboodi, Cornell University

Sholto Douglas, Anthropic

John Schulman, Thinking Machines

Martin Beraja, University of California, Berkeley

John Fernald, INSEAD

Boaz Barak, Harvard University and OpenAI

Arnaud Costinot, MIT

Noam Brown, OpenAI

Anna Salomons, Tilburg University and Utrecht University

Olivier Jeanne, Johns Hopkins University

Neil Thompson, MIT

Simone Daniotti, Utrecht University

Jerry Yang, AME Cloud Ventures

Leonardo Gambacorta, Centre for Economic Policy Research

Daniel Kokotajlo, AI Futures Project

Michiel Bakker, MIT and Google DeepMind

Manuel Trajtenberg, Tel Aviv University

Giacomo Calzolari, European University Institute

Jeff Wilke, Re:Build Manufacturing

Jacques Crémer, Toulouse School of Economics

Danny Yagan, University of California, Berkeley

Beatrice Weder di Mauro, Centre for Economic Policy Research

Max Tegmark, MIT

Vinod Khosla, Khosla Ventures

Benjamin Shiller, Brandeis University

Oren Etzioni, University of Washington

Martin Ford

Oded Galor, Brown University

Sarah Friar, OpenAI

Marc L. Busch, Georgetown University

Walid Hejazi, University of Toronto

Dilip Soman, University of Toronto

John Danaher, University of Galway

Thomas Astebro, HEC Paris

Alex Tabarrok, George Mason University

Alberto Galasso, University of Toronto

Alfonso Gambardella, Bocconi University

Reza Satchu, Harvard Business School

Alex Whalley, University of Calgary

Tom Davidson, Forethought Center for AI Strategy

Laurina Zhang, Boston University

Andrew Scott, University of Oxford

Jean-Etienne de Bettignies, Queen's University

Sam Manning, GovAI

Joel Blit, University of Waterloo

Sampsa Samila, IESE Business School

Roshni Raveendhran, University of Virginia

Liz Lyons, University of California, San Diego

Ramana Nanda, Imperial College London

Marianne Bertrand, University of Chicago

Arnaldo Camuffo, Bocconi University

Maxim Massenkoff, Anthropic

Petra Moser, New York University

Shivaji Sondhi, University of Oxford and Princeton University

Danny Buerkli, Windfall Trust

Carles Boix, Princeton University

Anna Yelizarova, Windfall Trust

Ken Ono, Axiom Math and University of Virginia

Isaiah Andrews, MIT

Anders Sandberg, University of Oxford

Martin Chorzempa, Peterson Institute for International Economics

Gita Gopinath, Harvard University

Zoë Hitzig, Anthropic

Lawrence Katz, Harvard University

Nathan Wilmers, Anthropic

Sebastian Becker, HEC Paris

Markus K. Brunnermeier, Princeton University

Sebastian Mallaby, Council on Foreign Relations

Adrian Brown, Windfall Trust

Sonia Sennik, Creative Destruction Lab

Ioana Marinescu, University of Pennsylvania

Nicholas Bloom, Stanford University

Johannes Hermle, Anthropic

Ashesh Rambachan, MIT

Brian Jabarian, Carnegie Mellon University

Lukas Althoff, Stanford University

Soumitra Shukla, Harvard Business School

Andrey Fradkin, Boston University

Andrew Koh, Columbia University

Prasanna Tambe, University of Pennsylvania

Cheryl Wu, Yale University

Albert Wenger, Union Square Ventures

Gigi Danziger, Eutopia

Chris Tonetti, Stanford University

Justin Bullock, Americans for Responsible Innovation

Bryan Seegmiller, Northwestern University

Betsey Stevenson, University of Michigan

Stefanie Stantcheva, Harvard University

Justin Wolfers, University of Michigan

Eva Lyubich, Anthropic

Chrishan Thuraisingham

Szymon Sacher, Anthropic

Thomas Houlden, Columbia University

Ben Golub, Northwestern University

Carlos J. Serrano, HEC Paris

Heski Bar-Isaac, University of Toronto

William Strange, University of Toronto

Jen Baggs, University of Victoria

Victor Aguirregabiria, University of Toronto

Melissa Lynne Dell, Harvard University

Jasmine Sun

Rob Reich, Stanford University

James Landay, Stanford University

Anousheh Ansari, XPRIZE Foundation

Fiona Chen, Harvard University

Michael Nayak, XPRIZE Foundation

George Williamson, The Alan Turing Institute

Michael Chui, McKinsey

Gabriel Unger, Stanford University

Katya Klinova

Parker Whitfill, METR

Arvind Karunakaran, Stanford University

Georgios Petropoulos, University of Southern California Marshall School of Business

José Ramón Enríquez, Stanford University

Christos Makridis, Arizona State University

Luca Vendraminelli, Stanford University

Alvin Wang Graylin, Stanford University

Sophia Kazinnik, Stanford University

Christina Langer, Stanford University

Riitta Katila, Stanford University

Lynn Wu, University of Pennsylvania

Matt Beane, University of California, Santa Barbara

David Nguyen, Stanford University

Avinash Collis, Carnegie Mellon University

Pamela Mishkin, Stanford University

Andy Haupt, Stanford University

Neale Mahoney, Stanford University

Robb Willer, Stanford University

Sinan Aral, MIT

Thomas W. Malone, MIT

Wajeeha Ahmad, Stanford University

Diyi Yang, Stanford University

Mary MacLennan

Wang Jin, Chapman University

Arjun Ramani, MIT

Glen Weyl, Microsoft Research

J. Frank Li, University of British Columbia

Jeremy Howard, fast.ai

Matt Gentzkow, Stanford University

Bharat Chandar, Stanford University

Jiaxin Pei, Stanford University

Sarah Bana, Chapman University

Ramiz Razzak

Molly Kinder, Breakwater Initiative

Arvind Narayanan, Princeton University

Laura Tyson, University of California, Berkeley

Tristan Harris, Center for Humane Technology

Christie Ko, Stanford University

Susan Young, Stanford University

• Nobel laureate

This could give Vz a huge leg up in PA.
AI/data center gets built ...needs connectivity ... Verizon sells connectivity ... Verizon has to build/maintain the network ...employees do the work.

For Verizon, potential work includes:

Fiber construction — new fiber routes into data centers.
Dark-fiber connections — lighting existing unused fiber or leasing strands.
Optical transport — installing/maintaining DWDM, ROADM and high-capacity equipment.
Central-office work — installing racks, shelves, power equipment, fiber panels and transport equipment.
Circuit provisioning — turning up high-capacity connections.
Testing — OTDR testing, fiber certification and optical testing.
Maintenance — troubleshooting fiber, optics, power and transmission equipment.
Network upgrades — increasing capacity as data-center traffic grows.
Data-center interconnects — connecting one data center to another over Verizon's network.
Enterprise services — businesses located at or around those facilities need dedicated connectivity.
Verizon has a lot of existing dark fiber in Pennsylvania, that's potentially a huge advantage. Verizon also has existing facilities .