Heena Purohit

Everyone’s racing to scale AI.
Akamai's CIO did the opposite. She slowed it down.

5 lessons from how Akamai Technologies' CIO Kate Prouty is leading the company through the AI surge 👇

1/ Move to a centralized AI strategy
- In late 2022, Akamai let all employees experiment in GenAI sandboxes.
- It fueled learning, but not scale.
- Now, all AI efforts roll up into a single, centralized AI program.

2/ Look beyond big tech and innovate with AI startups
- Yes they work with Microsoft, Google, Cisco,…
- But they also meet regularly with AI startups.
- It’s how they spot new tech early, shape their innovation roadmap, and plan investments they need to stay "AI ready".

3/ Pilot with purpose
- Every AI solution is tested in a small, measured rollout. 
- Each one with clear success metrics and strict governance.
- That's how they understand the tech and separate hype from real impact.

4/ Share what’s working (and what’s not)
- Each pilot gets a company-wide channel.
- Teams post experiments, screenshots, and lessons learned.  
- This transparency helps speed up patten recognition, and gives keeps everyone grounded in reality when trying new AI.

5/ Balance innovation with governance
- The mantra: “Encourage, don’t discourage” .
- Employees can bring any use case. IT helps them execute it securely and within cost controls.
- Even with tighter oversight, they maintain an open-door policy for new ideas.

Akamai's AI philosophy is similar to what I'm seeing at across enterprises:
AI adoption isn’t just about speed. It’s about structure.
Experiment boldly. Deploy carefully. Keep trust and accountability at the core.

👉 How is your company balancing AI innovation within guardrails? 
💬 Any other best practices you’d like to share?

🔗 Full article in comments.

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🚀 Excited to welcome NeuBird.ai to the Microsoft for Startups Pegasus Program!

They’ve built Hawkeye, the world’s first agentic AI Site Reliability Engineer (SRE).

It doesn’t just observe. It acts.
Built to autonomously diagnose incidents, find root causes, and trigger real-time remediation.

For enterprise IT and DevOps teams, that means:
- Up to 90% faster incident resolution
- Far fewer 3 a.m. alerts.
- More time for engineering that actually moves the business

Glad to have Gou Rao, Patrick Brennan, Paul Searles, Shilpi Srivastava, Justin Griffin in the program, building what's next in agentic reliability engineering.

The future of DevOps just got a lot more autonomous.

👇 If you're focused on DevOps productivity, check them out below.
or DM me for an intro.

Tom Davis Sally Ann Frank ShiSh Shridhar Kevin Magee Kevin Li-Kai Kuo Tiffany Johnson Jared Prins Bethany Cordes M12, Microsoft's Venture Fund Michael Stewart Jose Clautier Marion Desmazières

#MicrosoftForStartups #PegasusProgram #AgenticSoftwareEngineering #DevOpsTransformation

🚀 AI isn’t just helping write code faster. It’s rewriting the entire playbook of how software is built, tested, secured, deployed and maintained.

And you can see it all firsthand at GitHub Universe 2025.

This year, I’m bringing an incredible lineup of Microsoft for Startups Pegasus startups reimagining software engineering.

Each of them is redefining a layer of the new AI-native engineering stack:
Anyscale → Run and scale every AI/ML workloads seamlessly, from laptop to cloud
Endor Labs → Identify and fix critical risks in complex code - whether written by humans or AI
Faros AI → Turn engineering data into actionable insights; Measure productivity and ROI of coding assistants
Kubiya.ai → Agentic, context-aware DevOps copilot for every engineering team
Qodo → Ensure code integrity and quality - catch bugs, boost test coverage, enforce best practices, etc.
Roboflow → Empower every engineer with the power of computer vision in just a few lines of code

These aren’t just tools.
They’re a glimpse into how software engineering is evolving:
→ from reactive to proactive
→ from manual to agentic
→ from siloed to fully autonomous

If you’re heading to #GitHubUniverse, come find me and meet the founders transforming how the world builds and runs software.

📌 Learn more about these enterprise-ready startups: https://lnkd.in/e6hNBQ8n
📌 To schedule a meeting with any of them, DM me or reach out at: mfsgtm@microsoft.com

PS: There's only a couple of seats left for my Engineering Leaders Dinner on Oct 27. Let me know if you want in!

Microsoft Developer Microsoft Events #AgenticSoftwareEngineering #EnterpriseAI #AIforBusiness

The best engineering leaders aren’t “adding more AI.”
They’re designing smarter systems for people.

Here are the top 5 things enterprise leaders shared about their AI use:

𝟭/ 𝗠𝗮𝗻𝘆 𝘁𝗲𝗮𝗺𝘀 𝘂𝘀𝗲 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘁𝗼𝗼𝗹𝘀
- Each tool has different strengths.
- So engineers are given access to all of them; and they choose the tool they want. Sometimes it’s preference, sometimes task-specific.
- Most are great for greenfield development (starting from scratch).
- Some are bad at long-form manipulation (e.g. changing code across 500+ repos.
- Some are bad at ingesting a large codebase.
- They’ll all get better, but for now: there are preferences, styles, strengths and weaknesses.

𝟮/ 𝗖𝗼𝗱𝗶𝗻𝗴 𝗶𝘀 𝗮 𝘀𝗺𝗮𝗹𝗹 𝗽𝗮𝗿𝘁 𝗼𝗳 𝗮 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿’𝘀 𝗷𝗼𝗯. 
- Actual coding might be only 10-30% of the week.
- The rest? Tasks like search, debugging, reviews, compliance, change-management
- Teams are applying AI to optimize those, too

𝟯/ 𝗧𝗵𝗲 𝗹𝗲𝗴𝗮𝗰𝘆 𝗰𝗼𝗱𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗶𝘀 𝗿𝗲𝗮𝗹. 
- A huge chunk of code may be written by people who’ve since left the org.
- Teams still have to understand, maintain, and even modernize it

𝟰/ 𝗔𝗻𝗱 𝗻𝗼, 𝘁𝗵𝗲 𝗮𝗻𝘀𝘄𝗲𝗿 𝗶𝘀𝗻’𝘁 “𝘁𝗵𝗿𝗼𝘄 𝗺𝗼𝗿𝗲 𝗔𝗜 𝗮𝘁 𝗶𝘁.”
- That’s how you get AI solving AI-created problems.
- Tools need to be integrated thoughtfully. Avoid tool sprawl.

𝟱/ 𝗧𝗵𝗲 𝘄𝗶𝗻𝗻𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 𝗮𝗿𝗲 𝗳𝗼𝗹𝗹𝗼𝘄𝗶𝗻𝗴 𝗼𝗻𝗲 𝗼𝗿𝗱𝗲𝗿:
- People → process → tools.
- Start with workflows, ownership, and guardrails.
- Then pick the smallest tool that actually helps you drive some outcomes.

💬 𝗜𝗳 𝘆𝗼𝘂’𝗿𝗲 𝗮𝗻 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗹𝗲𝗮𝗱𝗲𝗿 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗱𝗲𝗲𝗽𝗹𝘆 𝗮𝗯𝗼𝘂𝘁 𝘁𝗵𝗶𝘀… 
I’m hosting another private dinner on October 26 in SF to swap real stories on AI adoption, developer experience, and what’s actually working.
DM me if you’d like to join the table!

🤔 𝗛𝗼𝘄 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜 𝗶𝗻 𝘆𝗼𝘂𝗿 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝘁𝗲𝗮𝗺𝘀 𝘁𝗼𝗱𝗮𝘆?

#softwareengineering #agenticsoftwareengineering #enterpriseAI #GitHubUniverse25