ON DEMAND • Podcast Episode

Rethinking Corporate Innovation By Scaling Agentic AI Products

A candid conversation with Taylor Black from Microsoft’s Office of the CTO on internal incubation, rapid experimentation, Agentic AI, product-market fit, engineering productivity, and how AI-first product development is changing the way companies build and scale new products.

FEATURED GUEST

Taylor Black

Our featured guest

Taylor Black

Office of the CTO, Microsoft

Taylor Black works in Microsoft’s Office of the CTO, where he has helped lead early-stage ideation, incubation, and internal venture-style innovation.
In this episode, he shares how Microsoft sources, validates, funds, and scales internal ideas, and how AI has shifted innovation from long-range bets to faster experimentation across product groups.

He also covers:

  • How Microsoft approaches internal incubation and corporate innovation
  • Why Horizon 3 innovation needs different expectations, funding, and timeframes
  • How AI is accelerating product experimentation across teams
  • Why Agentic AI is changing the full technology stack
  • What startups and product teams should focus on beyond generic AI

Why this conversation matters now

AI is changing how companies test ideas, build products, and organize innovation. The challenge is no longer just whether to invest in AI, but how to create the right operating model for experimentation, validation, and scale.

01.

How should large companies structure internal innovation?

02.

When should an idea become an incubation?

03.

How do teams avoid overfunding products before product-market fit?

04.

How does AI change engineering resources and rapid prototyping?

05.

What does Agentic AI mean for product strategy?

06.

What user experience models will replace the basic chat interface?

What you'll learn in this episode

After unlocking the full podcast, you’ll get expert insights on corporate innovation, Agentic AI, product strategy, and AI-first software development.
01.

How internal incubation can work inside a large technology company

02.

Why corporate innovation needs portfolio thinking and stage-gated validation

03.

How Microsoft evaluates ideas that may not fit immediate product priorities

04.

Why small teams should test hypotheses before scaling engineering resources

05.

How AI is speeding up product experimentation and reducing iteration cycles

06.

Why Agentic AI is affecting infrastructure, models, frameworks, and applications

07.

Why future AI innovation may depend on new user experience and business model patterns

Who this episode is for

CEOs and business leaders CTOs and technology leaders Product and innovation leaders Startup founders Engineering leaders Teams building AI-enabled products Growing businesses exploring AI innovation

Our host

uj

Umair Javed

CEO & Founder

Umair Javed is an AI transformation leader with extensive experience helping organizations adopt and scale AI, including Generative AI and Agentic AI. As CEO of tkxel, he has worked with Fortune 500s, SMBs, and startups worldwide, guiding them through AI-driven transformation, digital modernization, and long-term business growth.

A preview of the key takeaways

01.

Corporate innovation needs portfolio thinking

Taylor explains that not every idea should receive the same level of investment. Internal incubators need to balance risky long-range bets with opportunities that can create nearer-term value.

02.

Product-market fit should come before scaling resources

Before assigning large engineering teams, Microsoft’s incubation model focuses on testing hypotheses, reducing risk, and proving there is something worth building.

03.

AI is compressing innovation timelines

AI has changed the pace of experimentation. Ideas that once sat in long-range innovation cycles may now need to be tested across product groups much faster.

04.

Agentic AI reaches across the full stack

While most visible AI innovation happens at the application layer, Agentic AI also affects infrastructure, model selection, frameworks, orchestration, and developer workflows.

05.

The next AI opportunity may be user experience

Taylor highlights two open questions: what replaces the chat-box interface, and what business model will support Agentic AI as it becomes more widely adopted.

Why tkxel is sharing this conversation 

 At tkxel, we work with growing businesses navigating AI adoption, product engineering, software modernization, cloud strategy, and workflow transformation.

This episode is especially relevant for leaders trying to build faster, smarter, and more disciplined innovation systems. It is not just a conversation about Microsoft or AI incubation. It is a business conversation about experimentation, product-market fit, Agentic AI, and the operating models companies need to turn ideas into scalable outcomes.

WHERE TKXEL BRINGS CONTEXT

1 AI product strategy and implementation 2 Product engineering and software modernization 3 Cloud architecture and scalable delivery 4 Workflow transformation and AI adoption

RECOGNIZED BY

Key concepts covered in this podcast

1

Corporate innovation

Explains how larger organizations can structure, fund, validate, and scale new product ideas.

2

Internal incubation

Covers how ideas move from concept to prototype to potential business through staged validation.

3

Product-market fit

Shows why teams should prove user need and business value before scaling resources.

4

Agentic AI

Explores how AI agents may change applications, infrastructure, workflows, and product strategy.

5

AI-first product development

Looks at how AI is speeding up experimentation, prototyping, and product iteration.

6

Engineering productivity

Covers how software teams may shift from writing every detail to orchestrating higher-level problem solving.

7

Future user experiences

Explains why the next wave of AI products may require new interfaces beyond chat-based interactions.

Frequently Asked Questions (FAQs)

Is this episode only for large companies? Expand FAQ Collapse FAQ
No. While the conversation includes Microsoft’s internal innovation model, the lessons apply to startups, mid-market companies, product teams, and any organization trying to build AI-enabled products.
What do I get after accessing the podcast? Expand FAQ Collapse FAQ
You get access to the full podcast episode and transcript.
What is the core focus of the episode? Expand FAQ Collapse FAQ
The core focus is corporate innovation, internal incubation, Agentic AI, product-market fit, software engineering, and the future of AI-powered product development.
Why is the podcast gated? Expand FAQ Collapse FAQ
It is positioned as a premium resource for leaders actively researching AI innovation, product strategy, corporate incubation, and emerging technology adoption.
Can this help teams building AI products now? Expand FAQ Collapse FAQ
Yes. The episode is useful for teams thinking about how to validate ideas, allocate resources, use AI in product development, and rethink user experience beyond chat-based interfaces.
privacy-icon

We value your privacy

Tkxel uses essential cookies to ensure the proper functioning of our website. With your consent, we also use optional cookies for analytics, advertising, and third-party services.

By clicking “Accept all”, you consent to the use of all cookies. You can manage or withdraw consent for optional cookies at any time by clicking “Customize”. Please note that some website features may not function properly if optional cookies are disabled.

For more information, please read our Privacy Policy.

Customize
Accept All

Control Your Privacy

Websites may store or retrieve information on your browser, mostly in the form of cookies. This information is used to personalize your experience and is not usually linked to your identity. You can choose not to allow certain types of cookies, but it may affect your website experience. Learn more and change settings by clicking on the different categories.

Strictly Necessary

Strictly necessary cookies enable website functionality and cannot be turned off. They are typically set in response to actions you take, like setting privacy preferences, logging in, or filling in forms. You can block or receive alerts about these cookies, but some website features may not work. These cookies do not store personal information.

Performance

Performance cookies track site visits and traffic sources to measure and improve site performance. They provide information on popular pages and visitor behavior. The information collected is anonymous. If you do not allow these cookies, we will not know when you have visited the site and cannot monitor its performance.

Targeting

Targeting cookies are cookies that our advertising partners may set on our site. They use them to create a profile of your interests and show relevant ads on other sites. They do not store personal information, but use your browser and internet device's unique ID. Without these cookies, you will see less targeted ads.

Functional

Functional cookies improve your website experience through enhanced functionality and personalization. They are set by us or third-party providers. Without them, some or all of these services may not work properly.

Confirm My Choices
Accept All

Upcoming Webinar

Cybersecurity for Business Impact: Protecting Operations from AI-Powered Threats

June 29, 2026 10:00 am EST

Register Now
Watch Now
00 Days
00 Hours
00 Minutes
00 Seconds
Register Now