What happens when companies have new releases on deck, and it is clear that the dev team is spread too thin? Teams are always under pressure to deliver, but what if a project calls for overtime across the organization? What happens if those teams are pulled in competing directions? When major projects are at stake, development teams may face a less-than-ideal circumstance: a race to meet deadlines with near-mandatory overtime. Such “crunch time” can mean team members get pulled in different directions with little relief in sight until the project is done. Under such circumstances, CTOs must prioritize where development teams focus, but what happens if other IT resources also need urgent support? New software and apps may need to be delivered, yet existing apps could still need attention. In this episode of the podcast, Ken Ringdahl, CTO of Emburse, and Larissa Schneider, COO and co-founder of Unframe AI, discuss what happens when teams are spread thin and must deliver, and how they can work to avoid future periods of crunch time. They also navigated the “Questionable Ideas ‘R’ Us” tabletop exercises, helping the fictional company address its crunch time issues.

Many organizations have at least explored the use of AI in coding, changing the game for professional developers and citizen developers alike. Not that long ago, the conversation focused on what no-code and low-code platforms meant for in-house development. Citizen developers, staffers with limited or no professional background in coding, could use these platforms to produce somewhat simplified apps. That, in theory, left professional developers more time to focus on more robust, feature-rich software that required their skills. Use of AI to code got off to a rocky start, with some companies accidentally releasing proprietary code into the wild. But now it seems AI is here to stay as a tool developers might use to streamline their work. Vibe coding – letting AI take much of the lead – takes it even further. Where does that leave citizen developers, who may have been hitting their stride, and ecosystems that incorporated no-code/low-code platforms? Krishna Kumar Tiwari, co-founder and CTO of Whilter AI; and Maruf Ahmed, CEO of Dexian, tackled these and other questions about the impact AI has on the citizen developer space.

Allan Leinwand, CTO of Webflow, and Pierre DeBois, founder and CEO of Zimana, discuss how organizations can realign when IT goes awry. Internal or external forces can turn an IT ecosystem upside-down, and how CTOs lead the recovery may shorten or prolong the pain. Whether it is an in-house coding error, hardware failure, third-party software implosion, malicious bad actors, or a force of nature that shakes things up, how does tech leadership restore confidence in the tech resources the organization relies on?

Michael Leland, field CTO for Island, and Diane Ma, US finance strategy and global business services practice leader for Deloitte, discuss delivering on a tech overhaul.

Samya Dassarma, CTO of Iterable, and Margaret Dawson, CMO of Chronosphere, discuss navigating wayward tech implementations.  

Dan Carpenter, Amplitude's CIO, discusses whether enterprises that adopt new technology face inevitable shifts in how they function.

Businesses have been through transformative times, from the Industrial Revolution to the dawn of the Digital Age. As a flurry of AI agents and tools emerges, what should CIOs look for in this next period of transformation? How does this era of change differ from cloud transformation? Saket Srivastava, CIO of Asana, and Pierre DeBois, founder and CEO of Zimana, spoke to these and more questions in the latest InformationWeek podcast.

Harry Folloder, chief digital and technology officer for Alorica; and Brooke Huling, chief product officer for Accruent, break bread on productive ways they tap predictive data.

Building up an AI-enhanced workforce calls for more than telling staffers to use new tools and then hope for the best. Job roles can change, C-suite leadership may need new strategies, and the organization could face a different set of security and oversight concerns. In this episode of the InformationWeek podcast, Michael Fanning, CISO for Splunk; and Andie Dovgan, chief growth officer with Creatio, came together for a Breaking Bread session, tackling the tech and operations aspects of making AI part of the workforce.

Laura Sellers tackles a series of scenarios, discussing how tech and operations can navigate surprises both may face. How well do your software delivery cycles mesh with the logistics and operations of your organization? How do you deal with different rhythms of customer demand and logistics vs. the pace of software development and deployment? Who needs to be part of the conversation to get everything in line, especially when faced with unexpected pressures?

As IT leadership wrangles with data governance and policies, can operations glean useful information without stepping on a few toes? In this Breaking Bread session, Craig Martell, chief AI officer for Cohesity; and Matt McVaney, chief revenue office for BombBomb, discussed finding common ground between operations and tech to make data useful, and better understand the demands on either side of this dilemma. InformationWeek's podcast is evolving. The "Breaking Bread" format brings together one CIO, CTO, or other C-suite tech leader to discuss a challenge with an executive from the operations side of another organization. The intent is to allow them the space to exchange ideas and pain points from their respective vantages, and foster discussions that generate new insights for their organizations as well as the audience.

What happens of an organization feels the need to move to new tech that will require significant investment and other internal changes? How do the operational and tech sides of the enterprise assess their needs and concerns, then share those perspectives over the fence? Josh Mason, CTO of RecordPoint, and Katie Klein, vice president of marketing for Comcast Business, discuss paths forward for introducing new tech to legacy ops.

Jeff Reihl, CTO for the legal and professional side of LexisNexis, discusses how the introduction of AI changed their project plans.

The duties of C-suite tech leadership at enterprises are changing rapidly of late. AI shook up strategies at many companies and can lead to new demands on CIOs, CTOs, and others responsible for technology plans and use. The core principles that guide CIOs and CTOs can be essential for navigating such times, especially when organizations look to them for direction. In this episode, Matt Lyteson, CIO of IBM, and Phillip Goericke, CTO of NMI, share some key principles that define their respective roles at their organizations. They also discuss where they picked up some of the lessons that shaped those principles, how their jobs have changed since they got their starts, and who they look to for inspiration as leaders -- as well as what they wish they knew when they got started.

With more AI models emerging, how do CIOs and CISOs at enterprises go about establishing security guardrails to reduce risks as the technology gets deployed? In the early months of the AI craze, the business world saw incidents where proprietary code got into the wild after being fed to AI. There have also been concerns about AI being tapped to launch cyberattacks, as well as AI used within organizations creating unintended access opportunities bad actors might leverage. What top risks, internal and external, are CIOs and CISO worried about when it comes to AI? What concerns do CIOs have about bringing a new, third-party AI model inhouse, especially as more models emerge? Carl Froggett, CIO for Deep Instinct; Rob Lee, chief of research and head of faculty at SANS Institute; and Mike Levin, CISO and general counsel with Solera Health, tackled these and other questions in this episode.

Will the development of these resources proceed in tandem at enterprises, or must CIOs evolve these technologies with separate strategies? Luiz Domingos, CTO for Mitel; Jon Kuhn, senior vice president of product for Delinea; Anshu Jain, co-Founder and CTO with Outmarket AI; and Steve Williams, CISO, NTT DATA tackled that and other questions in this episode.

Is putting a data center under the ocean or in orbit just a novelty or a future-forward idea? Data centers have been installed put undersea and now in space -- do these exotic locations seem more like a novelty than a benefit to enterprise operations? One benefit is access to natural sources of cooling for data centers, either in the freezing temperatures in space or cold waters of the sea. Dmitry Zakharchenko, chief software officer for Blaize; and Alvin Nguyen, senior analyst with Forrester, discussed these topics with Shane Snider, senior writer with InformationWeek joining in.

As stakeholders in the cloud try their hands at developing quantum compute chips and related resources, is there a symbiotic evolution of tech in the making? This episode brought together James Kaplan, partner with McKinsey; Rich Salz, principal architect at Akamai; Matthew Keesan, vice president and general manager of quantum computing and platform with IonQ; and Daniella Pontes, quantum ambassador. They discussed that question as well as should enterprises make an effort to be quantum-ready, AI-ready, as well as cloud-ready -- or does this become a point of confusion for CIOs?

There may be a new era of DeFi in the offing if regulation eases up, and stakeholders in this sector see new potential understandings with watchdogs. This episode of DOS Won’t Hunt brought together Wenny C., partner with SynFutures; Martin de Rijke, head of growth for Maple Finance; Alan Orwick, co-founder of Quai; and Gerald Gallagher, general counsel at Sei Labs.

This episode brought together Tatum Tummins, senior product manager with Kion; Edward Walsh, senior managing consultant for IBM’s global cloud advisory practice; Jason Hardy, vice president and CTO of AI at Hitachi Vantara; Joe Jacir, cloud architect for enVista; Stephen Manley, CTO with Druva; and Dave Driggers, CTO and founder of Cirrascale. They discussed whether AI might devour the critical capacity needed at data centers that makes the cloud worthwhile. They dove into other questions such as whether there is a tipping point where cloud loses its viability if AI gobbles up capacity at data centers.