How 80,000 companies build with AI: products as organisms, the death of org charts, and why agents will outnumber employees by 2026 | Asha Sharma (CVP of AI Platform at Microsoft) · Lenny's Podcast: Product | Career | Growth summary

Key takeaways

The transition from 'product as artifact' to 'product as organism' allows for dynamic product learning and adaptation.
Microsoft's 'seasons' framework enables agile planning in a rapidly changing AI landscape.
The evolution from traditional org charts to task-oriented 'work charts' showcases the future role of AI agents.
Companies are increasingly investing in post-training to fine-tune AI models for specific use cases.
Optimism in leadership, as exemplified by Satya Nadella, is critical for fostering a culture of innovation.
The future will see deeper collaboration between humans and AI, enhancing productivity and expanding skills.

Summary

The Transition from Product as Artifact to Product as Organism

Asha Sharma discusses the shift in product development towards viewing products as living organisms rather than mere artifacts. This evolution is fueled by advancements in AI, where products continuously learn and adapt from user interactions, enhancing their performance and effectiveness over time. This dynamic approach allows companies to measure the 'metabolism' of product teams in terms of data ingestion and outcome generation.

Planning in the Age of AI: The Seasons Framework

To navigate the rapid changes in AI, Microsoft employs a 'seasons' framework for planning. Instead of rigid long-term roadmaps, they adapt strategies based on industry shifts. This framework helps teams ground their objectives around current trends, allowing for agile responses to developments within the AI landscape.

The Rise of Agents and the Death of Org Charts

The discussion highlights a future where AI agents will outperform human employees, leading to the redefinition of organizational structures. Instead of traditional hierarchies, work will be organized around tasks that agents and humans execute collaboratively, known as the ‘work chart.’ This evolution reflects a growing efficiency and a need for adaptive work environments.

Post-Training vs. Pre-Training in AI Development

Asha emphasizes the increasing investment in post-training as companies recognize its importance in fine-tuning models for specific outcomes. This trend arises from the realization that extensive foundational models require ongoing optimization to achieve desired performance, marking a shift in how companies view AI development.

Learning from Leadership: Insights from Satya Nadella

Asha shares valuable lessons learned from Satya Nadella about the power of optimism in leadership. His ability to inspire and energize the team fosters a culture of growth and innovation, essential for navigating the fast-paced changes within the tech industry.

The Future of Human-AI Collaboration

A fascinating theme of the podcast focuses on how humans and AI will collaborate in the future. Asha predicts an agentic society where AI enhances human capabilities, driving productivity and expanding skill sets, ultimately benefiting both employees and businesses.

Show notes

Asha Sharma leads AI product strategy at Microsoft, where she works with thousands of companies building AI products and has unique visibility into what’s working (and what’s not) across more than 15,000 startups and enterprises. Before Microsoft, Asha was COO at Instacart, and VP of Product & Engineering at Meta, notably leading product for Messenger.

What you’ll learn:

1. Why we’re moving from “product as artifact” to “product as organism” and what this means for builders

2. Microsoft’s “seasons” planning framework that allows them to adapt quickly in the AI era

3. The death of the org chart: how agents are turning hierarchies into task networks and why “the loop, not the lane” is the new organizing principle

4. Why post-training will soon see more investment than pre-training—and how to build your own AI moat with fine-tuning

5. Her prediction for the “agentic society”—where org charts become work charts and agents outnumber humans in your company

6. The three-phase pattern every successful AI company follows (and why most fail at phase one)

7. The rise of code-native interfaces and why GUIs might be going the way of the desktop

8. What Asha learned from Satya Nadella about optimism

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Transcript: ⁠https://www.lennysnewsletter.com/p/how-80000-companies-build-with-ai-asha-sharma

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My biggest takeaways (for paid newsletter subscribers): ⁠https://www.lennysnewsletter.com/i/171413445/my-biggest-takeaways-from-this-conversation⁠

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Where to find Asha Sharma:

• LinkedIn: https://www.linkedin.com/in/aboutasha/

• Blog: https://azure.microsoft.com/en-us/blog/author/asha-sharma/

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Where to find Lenny:

• Newsletter: https://www.lennysnewsletter.com

• X: https://twitter.com/lennysan

• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/

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In this episode, we cover:

(00:00) Introduction to Asha Sharma

(04:18) From “product as artifact” to “product as organism”

(06:20) The rise of post-training and the future of AI product development

(09:10) Successful AI companies: patterns and pitfalls

(12:01) The evolution of full-stack builders

(14:15) “The loop, not the lane”—the new organizing principle

(16:24) The future of user interfaces: from GUI to code-native

(19:34) The rise of the agentic society

(22:58) The “work chart” vs. the “org chart”

(26:24) How Microsoft is using agents

(28:23) Planning and strategy in the AI landscape

(35:38) The importance of platform fundamentals

(39:31) Lessons from industry giants

(42:10) What’s driving Asha

(44:30) Reinforcement learning (RL) and optimization loops

(49:19) Lightning round and final thoughts

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Referenced:

• Copilot: https://copilot.microsoft.com/

• Cursor: https://cursor.com/

• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell

• Inside ChatGPT: The fastest growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley

• GitHub: https://github.com

• Dragon Medical One: https://www.microsoft.com/en-us/health-solutions/clinical-workflow/dragon-medical-one

• Windsurf: https://windsurf.com/

• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan

• Lovable: https://lovable.dev/

• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika

• Bolt: http://bolt.com

• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons

• Replit: https://replit.com/

•Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad

• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor

• Sierra: https://sierra.ai/

• Spark: https://github.com/features/spark

• Peter Yang on X: https://x.com/petergyang

• How AI will impact product management: https://www.lennysnewsletter.com/p/how-ai-will-impact-product-management

• Instacart: http://instacart.com/

• Terminator: https://en.wikipedia.org/wiki/Terminator_(franchise)

• Porch Group: https://porchgroup.com/

• WhatsApp: https://www.whatsapp.com/

• Maslow’s Hierarchy of Needs: https://www.simplypsychology.org/maslow.html

• Satya Nadella on X: https://x.com/satyanadella

• Perfect Match 360°: Artificial intelligence to find the perfect donor match: https://ivi-fertility.com/blog/perfect-match-360-artificial-intelligence-to-find-the-perfect-donor-match/

• OpenAI’s GPT-5 shows potential in healthcare with early cancer detection capabilities: https://economictimes.indiatimes.com/news/international/us/openais-gpt-5-shows-potential-in-healthcare-with-early-cancer-detection-capabilities/articleshow/123173952.cms