The Gabarée Family Chocolate Babka Recipe

Chocolate babka has become a family tradition in our home. Over the years I’ve experimented with several recipes before settling on this version, adapted from Jerusalem by Yotam Ottolenghi and Sami Tamimi. The result is a rich brioche dough filled with a silky chocolate ganache that has become one of our favorite treats to share with family and friends

Prep Time: 2 hours 
Cook Time: 35 minutes 
Chilling time: 12 hours 
Total Time: 14 hours 35 minutes 
Yield: 2 loaves

Ingredients

Tools and Miscellaneous:

Food scale (if available)

Measuring cup

Tablespoon

Teaspoon

Stand mixer with dough hook

Hand mixer

Spatula to scrape down the sides of the bowl when mixing the dough

Olive Oil to coat the bowl for when the dough is proofing

Plastic wrap to cover the dough bowl when proofing

Serrated knife

Two 9×5-inch bread pans

Butter for the sides of the bread pans 

Parchment paper for the bottoms of the bread pans

Offset spatula (preferred) or a regular one if an offset spatula is not available to spread chocolate filling

Brioche: 

4⅜ cups (530 g) all-purpose flour, plus extra for dusting 

½ cup (100 g) granulated sugar 

1 tablespoon (14 g) instant dry yeast 

3 large eggs 

½ cup (118 ml) water 

1 teaspoon (6 g) fine sea salt (do not use if butter is salted)

⅔ cup (150 g) unsalted butter, cut into small slices and softened to room temperature

Olive Oil to coat the bowl for when the dough is proofing

Butter for the bread pans 

Parchment paper for the bread pans

Chocolate Filling (modified chocolate ganache): 

200g (7 oz.) 70% dark chocolate 

½ cup (115 g) salted butter 

½ cup (60 g) powdered sugar 

⅓ cup (80 ml) heavy cream 

⅓ cup (50 g) unsweetened cacao powder 

Sugar Syrup: 

½ cup (118 ml) water 

½ cup (100 g) granulated sugar 

Instructions

Make the Dough:
Using a hand mixer, cream the butter and sugar together. Using the same hand mixer, mix the eggs with the creamed butter and sugar. Heat the water to between 105F and 112F. Mix yeast into the heated water using a fork.

Place flour, sugar, yeast, and salt in a standing mixer fitted with a dough hook and mix on low speed until combined. Add the water/yeast mixture and continue to mix on low speed until incorporated. The dough will be mostly dry and crumbly at this point. Add the creamed butter/sugar/egg mixture and mix on medium speed until the dough comes together, 2-3 minutes. Continue mixing for about 10 minutes on medium speed until the dough is completely smooth, elastic, and shiny. It will look soft and might be sticky – that’s ok. During mixing, you will need to scrape down the sides of the bowl.

With floured hands, transfer dough to a large mixing bowl brushed with olive oil, cover with plastic wrap, and leave in the refrigerator to proof for at least half a day or overnight. The dough may not look like it has risen much, but that's okay. If placed for a long time in the fridge, the dough can become hard; that’s also okay; leave it at room temperature until it’s easy to work with, usually around 30-60 minutes.

Grease two loaf pans (I usually use 9×5-inch pans, but a bit smaller or larger pans would also work), butter the sides of each pan, and line the bottoms with parchment paper for easy release later. Set aside.

Make the Filling:
In a double boiler (or medium saucepan with an aluminum bowl resting over it), bring water to a full boil. Place chocolate, butter, heavy cream, cocoa powder, and sugar into the top bowl. Lower the heat to moderate and melt together the contents of the top bowl, mixing frequently with a spatula. The mixture will have a fudgy look and consistency at this point. Reduce the heat to low and continue to mix until fully melted and completely smooth. Set aside the bowl to cool. It will thicken and become spreadable as it cools. You can also place it in the refrigerator briefly until you get a spreadable consistency.

Roll and Shape the Dough:
Divide the dough in half. Roll out the dough with a rolling pin on a lightly floured surface, and shape it into a rectangle measuring 16×12 inches (40×30 cm) and 0.25 inches (0.64 cm) thick. Fold the dough onto itself until it is about 25% it's original rolled-out size. Roll the dough out again, shaping it into a rectangle measuring 16×12 inches (40×30 cm) and 0.25 inches (0.64 cm) thick. Repeat the folding and rolling process one more time. Now position the dough so that the long side is closest to you. Repeat the above process for the other half of the dough.

Add the Filling and Shape the Babka:
Using an offset spatula, spread half of the chocolate mixture over the rectangle. It is ok to have some ganache left over. Spread just enough to cover the dough, between 0.15 (0.38 cm) and 0.25 inches (0.64 cm). Too much ganache will make the babka soggy and taste off-balance.

Use both hands to roll up the rectangle like a roulade, starting from the long side closest to you and ending at the other long end. Press to seal the dampened end onto the roulade, then use both hands to even out the roll into a perfect, thick cigar. Rest the cigar on its seam.

Using a serrated knife, gently cut the roll in half lengthwise, starting at the top and finishing at the seam, essentially dividing the log into two long, even halves, with the layers of dough and filling visible along the length of both halves. With the cut sides facing up, gently press together one end of each half, then lift the right half over the left half. Repeat this process, but this time, lift the left half over the right to create a simple two-pronged plait. Gently squeeze together the other ends so you are left with the two halves intertwined, showing the filling on top.

Carefully lift the cake into a loaf pan. Don’t worry if there are gaps in the pan since the cake will rise and will eventually look fine, even if it looks messy at this point. Cover the pan loosely with plastic wrap and leave to rise at room temperature for 1 to 1½ hours until almost doubled in size. Repeat to make the second babka.

Bake the Chocolate Babka:
Preheat oven to 350°F/175°C, allowing plenty of time to heat fully before the uncooked babkas have finished rising. Remove the plastic wrap and place the cakes on the middle rack of the oven. Bake for 30-35 minutes, until golden brown on top. If you have a thermometer, you are looking for an internal temperature of about 200ºF/93ºC degrees.

Make and Apply the Syrup:
While the cakes are in the oven, make the syrup. In a small saucepan over medium heat, bring water and sugar to a boil. As soon as the sugar dissolves, remove from heat and set aside to cool. As soon as the cakes come out of the oven, brush the syrup over them. Use all of the syrup, even if it looks like you used a lot. Let cakes cool until they are warm, then remove from pans and let cool completely before serving.

Serve:
Serve by itself warm or at room temperature. It also pairs nicely with ice cream and coffee.

This Chocolate Babka will stay fresh for 24 hours in an airtight container at room temperature, but will also be just fine for around five days in a plastic bread bag with a twist tie.

Where AI Creates Real Value in Finance

Artificial intelligence is not replacing finance.

It will change what finance professionals spend their time doing.

For decades, finance organizations have focused on collecting data, reconciling transactions, producing reports, and explaining what happened. Those responsibilities remain essential, but AI is changing how much time is required to complete them.

The real opportunity is not simply automating existing work. It is allowing finance teams to spend more time helping the business make better decisions.

AI Is an Accelerator, Not a Strategy

Organizations often begin their AI journey by asking:

“What tasks can we automate?”

A better question is:

“What decisions could we improve if our people had more time, better information, and stronger analytical tools?”

Finance has always been responsible for turning information into decisions. AI simply expands its ability to do that work faster and at greater scale.

Moving Beyond Reporting

Most finance organizations already possess large amounts of data.

Financial statements.

Forecasts.

Vendor spending.

Capital projects.

Procurement.

Contract performance.

Cash flow.

Operational metrics.

Historically, much of the finance team’s effort has been devoted to collecting, validating, and presenting that information.

AI allows those activities to become increasingly automated.

That creates capacity for work that generates greater organizational value:

• evaluating investment alternatives
• modeling strategic scenarios
• identifying operational inefficiencies
• improving forecasting accuracy
• strengthening vendor oversight
• supporting capital allocation decisions

The objective is not fewer finance professionals.

It is better use of financial expertise.

Better Decisions Require Better Data

Artificial intelligence amplifies the quality of the information it receives.

Organizations with fragmented systems, inconsistent data definitions, or poor governance should expect AI to expose those weaknesses rather than solve them.

Successful AI adoption depends on disciplined data management, clear ownership, consistent definitions, and governance that ensures information can be trusted.

Technology cannot compensate for poor data quality.

Finance and Technology Must Lead Together

AI adoption should never be viewed as an isolated technology initiative.

Finance understands business value.

Technology understands platforms, integration, cybersecurity, and implementation.

Together, they create solutions that are technically feasible, financially responsible, and operationally sustainable.

The strongest AI programs emerge when CFOs and CIOs work as partners rather than customers and service providers.

Governance Determines Long-Term Success

As AI becomes embedded within forecasting, financial planning, reporting, procurement, and decision support, governance becomes increasingly important.

Organizations should establish clear expectations for:

• data quality
• model transparency
• regulatory compliance
• human review of significant decisions
• security and privacy
• accountability for AI-generated outputs

Trust is built through governance, not automation.

AI Should Augment Human Judgment

The greatest contribution AI can make to finance is not replacing analysis.

It is creating more time for it.

Finance professionals are uniquely positioned to evaluate tradeoffs, challenge assumptions, assess risk, and allocate capital. Those responsibilities require judgment, experience, and business context that AI cannot provide independently.

Organizations that use AI successfully will automate routine work while elevating the strategic role of their finance teams.

That is where the greatest value will be created.

AI is changing finance, but its greatest contribution will not be producing reports faster. It will be giving finance leaders more capacity to guide better decisions across the enterprise.

What Total Football Teaches Us About Adaptive Organizations

One of the most influential business articles I’ve ever read wasn’t really about manufacturing.

It was about adaptability.

While reading Making Mass Customization Work by B. Joseph Pine II, Bart Victor, and Andrew C. Boynton, I was reminded of an entirely different discipline: Total Football.

Originally developed and popularized by Ajax and the Dutch national team, Total Football challenged one of the fundamental assumptions of team sports. Instead of rigid positional responsibilities, every player understood the broader system. As one player advanced, another instinctively filled the space. The team remained balanced because everyone understood both their own role and how their role fit within the larger objective.

The lesson extends far beyond football.

Adaptability Creates Competitive Advantage

Organizations often define people by job titles.

Engineers engineer.

Project managers manage projects.

Security teams secure systems.

Operations teams operate infrastructure.

Specialization is important, but organizations become fragile when work depends too heavily on rigid organizational boundaries.

The most resilient organizations develop people who understand how the entire system works, not just their individual responsibilities.

When priorities change, customer needs evolve, or unexpected problems emerge, those organizations adapt far more effectively because people know how to collaborate beyond functional silos.

Every Team Needs Positional Flexibility

Positional flexibility does not mean everyone performs every job.

It means individuals understand enough about adjacent functions to contribute when circumstances require it.

I’ve consistently found that organizations perform better when engineers understand customer impact, project managers appreciate technical constraints, security teams participate early in architecture discussions, and infrastructure teams understand business priorities.

People remain specialists.

But they stop becoming isolated specialists.

Shared Awareness Is More Valuable Than Perfect Processes

Many organizations attempt to solve complexity by adding process.

Process certainly has value, but process alone rarely creates adaptability.

Shared awareness does.

Teams that communicate continuously, understand organizational priorities, and trust one another make better decisions even when situations change unexpectedly.

That principle explains why high-performing organizations often respond to disruption more effectively than organizations with more documentation or more rigid governance.

The difference is not process maturity.

It is collective understanding.

Leadership Creates the Conditions

Adaptive organizations do not emerge by accident.

Leaders create environments where collaboration is rewarded, information moves freely, and expertise is valued regardless of organizational boundaries.

That often requires cross-functional projects, rotational assignments, shared objectives, and deliberate investment in developing broader business understanding—not simply deeper technical specialization.

People become more valuable when they understand how their work enables everyone else’s success.

Technology Organizations Need This More Than Ever

Artificial intelligence, cloud platforms, cybersecurity, data engineering, enterprise architecture, and software delivery have become deeply interconnected.

No single discipline can solve today’s enterprise challenges independently.

Technology organizations increasingly succeed through coordinated expertise rather than isolated excellence.

The leaders who build adaptive organizations recognize that the goal is not to eliminate specialization. It is to create enough shared understanding that teams continue moving forward when priorities shift.

The Best Teams Think Like Systems

Total Football demonstrated that extraordinary teams are built on flexibility, trust, communication, and shared purpose.

The same is true for modern organizations.

Competitive advantage increasingly belongs to organizations that can learn faster, adapt sooner, and coordinate more effectively than their competitors.

That begins with leaders who build systems where people understand more than their own position—and recognize that the success of the organization depends on how well those positions work together.

Who Carries the Risk? Lessons from Technology Contracting

One of the most important questions in any technology contract is not the price.

It's: Who carries the risk when conditions change?

Technology projects rarely unfold exactly as expected. Supply chain disruptions, cybersecurity requirements, inflation, changing business priorities, labor shortages, and evolving technical standards all affect cost, schedule, and delivery. Well-structured contracts recognize those realities by clearly allocating risk between the customer and the service provider.

Understanding those tradeoffs is an important leadership responsibility.

Fixed Price Does Not Mean Fixed Risk

Many organizations assume a fixed-price contract transfers all financial risk to the contractor. In practice, risk is shared, even when pricing is fixed.

If specialized hardware becomes unavailable, labor costs rise unexpectedly, or regulatory requirements change during execution, someone ultimately absorbs those additional costs. The question is whether the contract anticipated those possibilities and assigned responsibility appropriately.

In federal contracting, that balance is particularly important. Government agencies seek cost certainty and responsible stewardship of taxpayer resources. Contractors, meanwhile, must manage delivery risk while maintaining financial viability. Successful partnerships recognize that long-term performance depends on both objectives being achieved.

Innovation Changes the Equation

Risk allocation also works in the opposite direction.

As organizations improve delivery methods, automate repetitive work, standardize platforms, or streamline operations, the cost of delivering services often declines. Those efficiencies create opportunities for contractors to improve margins while remaining more competitive in future procurements.

In competitive markets, many of those operational improvements are ultimately reflected in lower bid prices or greater value delivered to customers. Organizations that continually improve how they work often compete more successfully than those relying solely on lower labor rates.

Contracts Should Encourage Better Outcomes

The strongest technology contracts are not designed simply to control cost. They encourage behaviors that improve long-term outcomes.

When incentives are aligned, organizations invest in automation, standardization, cybersecurity, quality, and continuous improvement because those investments benefit both parties. When incentives are poorly aligned, organizations may optimize for short-term contract performance at the expense of long-term operational success.

Technology leaders should evaluate contracts not only for commercial terms but also for how effectively they distribute risk, encourage innovation, and support sustainable performance.

Leadership Beyond the Contract

Technology contracting is ultimately an exercise in governance.

Leaders must understand where risk resides, how changing market conditions affect delivery, and whether contractual incentives continue to support the organization’s strategic objectives.

The goal is not simply to negotiate the lowest price. It is to create partnerships that remain resilient as technology, markets, and organizational priorities evolve.

The organizations that consistently achieve the best outcomes understand that effective contracting is less about transferring risk than managing it intelligently.

Technology Investment Requires Economic Judgment

One of the biggest misconceptions about technology leadership is that technology decisions are primarily technical decisions. They are not.

The best technology investments are business decisions grounded in economics.

Throughout my career leading infrastructure and operations teams, we regularly evaluated competing priorities: modernizing aging infrastructure, introducing new capabilities, improving cybersecurity, reducing operational risk, and maintaining reliable service. Technical feasibility was rarely the difficult part. The challenge was determining where finite resources would create the greatest long-term value.

That requires more than data.

Data Doesn’t Make Decisions

Technology organizations collect enormous amounts of data.

Asset inventories. Incident counts. Mean time to recovery. System utilization. Cloud costs. Vendor performance. Security events. Project budgets.

Those metrics are valuable, but by themselves they rarely answer the most important leadership questions.

Should we replace the platform this year?

Should we modernize now or extend the lifecycle another eighteen months?

Should cybersecurity funding increase ahead of application modernization?

Should we standardize globally or maintain local flexibility?

Those are economic decisions informed by technology—not technology decisions informed solely by data.

Looking Beyond Initial Cost

Organizations often focus on acquisition cost because it is easy to measure. The more meaningful question is total organizational impact.

A less expensive solution may require higher operating costs, greater administrative effort, increased cybersecurity exposure, or additional downtime over its lifetime. Conversely, a larger upfront investment may reduce operating expense, simplify support, improve resilience, and provide flexibility for future growth.

Technology leaders should evaluate investments across the full lifecycle rather than focusing on purchase price alone.

Cybersecurity Is an Economic Decision

Cybersecurity provides one of the clearest examples.

A Zero Trust initiative is often viewed as a security investment. In reality, it is also an economic investment.

Reducing the likelihood of a successful attack protects far more than technology assets. It reduces operational disruption, protects organizational reputation, strengthens regulatory compliance, lowers recovery costs, and preserves leadership’s ability to execute strategic priorities.

The return on investment is measured not only in avoided incidents, but in organizational resilience.

Modernization Should Be Continuous

I have also found that infrastructure modernization benefits from an economic perspective rather than a purely technical one.

Many organizations historically replaced major portions of their infrastructure on fixed multi-year cycles. While straightforward administratively, this often concentrated cost, increased operational disruption, and allowed technology to age significantly before replacement.

A rolling modernization strategy frequently produces better outcomes. Incremental upgrades distribute capital requirements more evenly, reduce operational risk, incorporate technological improvements more quickly, and avoid large-scale end-of-life events that strain both budgets and engineering teams.

The objective is not simply newer technology. It is better capital allocation.

Turning Information into Better Decisions

Technology organizations generate abundant data.

Leadership creates value by transforming that data into information that supports better decisions.

That requires understanding organizational priorities, financial constraints, operational risk, customer impact, regulatory obligations, and long-term strategy—not simply interpreting dashboards.

The most effective technology leaders do not ask, “Can we implement this?”

They ask, “Will this create lasting value for the organization?”

That distinction is where technology leadership becomes business leadership.

Leadership and Accountability in Healthcare Technology

Technology has become inseparable from patient care. Electronic health records, clinical systems, medical devices, cybersecurity, data analytics, and digital workflows all influence how safely and effectively care is delivered. As healthcare organizations become increasingly dependent on technology, leadership within IT becomes more than an operational responsibility—it becomes a responsibility to patients.

Successful healthcare technology organizations are built on three principles: accountability, trust, and continuous improvement.

Leadership Creates the Environment

Healthcare technology leaders operate in an environment where change is constant. New clinical applications, cybersecurity threats, regulatory requirements, interoperability standards, and evolving patient expectations require organizations to adapt without disrupting care.

That adaptation begins with leadership.

Leaders establish the vision, set priorities, remove barriers, and create an environment where teams are encouraged to solve problems rather than simply maintain systems. Innovation is important, but innovation must always support safer, more reliable patient care. New technology should improve outcomes, simplify workflows, and reduce risk—not create additional complexity.

Just as important, leaders must build confidence across the organization. Technology initiatives succeed when clinicians, administrators, and operational leaders understand why change is occurring and believe the organization can execute it successfully.

Accountability Builds Trust

Healthcare depends on trust, and technology organizations earn that trust through accountability.

Patient information must remain secure. Clinical systems must remain available. Infrastructure must perform reliably. When technology supports life-critical operations, accountability cannot be delegated—it must be embedded throughout the organization.

Leaders establish clear expectations, define ownership, measure performance, and create transparency around results. More importantly, they foster an environment where issues are identified early rather than hidden until they become crises.

The strongest technology organizations are not those that never experience problems. They are the organizations that identify issues quickly, respond effectively, learn from failures, and continuously improve.

Serving the Organization

Leadership is not measured by authority alone. It is measured by how effectively leaders enable others to succeed.

Technology professionals perform at their best when they understand the organization’s mission, have the resources they need, and know their expertise is valued. Leaders who invest in developing people, encourage collaboration across departments, and remove unnecessary obstacles create teams capable of solving increasingly complex challenges.

That culture extends beyond the IT department. Healthcare technology is inherently collaborative. Clinical staff, finance, compliance, operations, cybersecurity, and technology teams must work together to achieve shared outcomes. Leadership creates the conditions that make those partnerships successful.

Continuous Improvement

Healthcare organizations cannot afford to become comfortable with yesterday’s solutions.

Continuous improvement means evaluating systems, processes, governance, security, and workflows with the expectation that they can always become more effective. It also requires listening—to clinicians, patients, technology professionals, and business leaders—to understand where improvements will have the greatest impact.

Technology should never be implemented simply because it is new. It should be adopted because it demonstrably improves care delivery, strengthens resilience, reduces risk, or enables the organization to fulfill its mission more effectively.

Leadership in Service of Patient Care

Technology is now fundamental to nearly every aspect of modern healthcare. The responsibility of healthcare technology leaders extends well beyond infrastructure, applications, or cybersecurity. Their work influences clinical outcomes, operational performance, regulatory compliance, and the trust patients place in the organizations that care for them.

Organizations that combine clear accountability, collaborative leadership, and a commitment to continuous improvement are better positioned to navigate change while maintaining the reliability, security, and resilience that modern healthcare demands. Ultimately, effective healthcare technology leadership is not measured by the systems it deploys, but by the confidence it creates and the care it enables.