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תוכן מסופק על ידי Modern Web. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Modern Web או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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What’s New About Heroku in 2025? AI Platform as a Service + What are MCPs?

38:31
 
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Manage episode 484060924 series 2927306
תוכן מסופק על ידי Modern Web. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Modern Web או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

In this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson sit down with Julián Duque, Principal Developer Advocate at Heroku, to talk about Heroku’s evolution into an AI Platform-as-a-Service. Julián breaks down Heroku’s new Managed Inference and Agents (MIA) platform, how they’re supporting Claude, Cohere, and Stable Diffusion, and what makes their developer experience stand out.

They also get into Model Context Protocols (MCPs)—what they are, why they matter, and how they’re quickly becoming the USB-C for AI. From internal tooling to agentic infrastructure and secure AI deployments, this episode explores how MCPs, trusted environments, and better AI dev tools are reshaping how we build modern software.

Key Points from this episode:

- Heroku is evolving into an AI Platform-as-a-Service with its new MIA (Managed Inference and Agents) platform, supporting models like Claude, Cohere, and Stable Diffusion while maintaining a strong developer experience.

- MCPs (Model Context Protocols) are becoming a key standard for extending AI capabilities—offering a structured, secure way for LLMs to access tools, run code, and interact with resources.

- Heroku's AI agents can perform advanced operations like scaling dynos, analyzing logs, and self-healing failed deployments using grounded MCP integrations tied to the Heroku CLI.

- Despite rapid adoption, MCPs still have rough edges—developer experience, tooling, and security protocols are actively improving, and a centralized registry for MCPs is seen as a missing piece.

Chapters

0:00 – What is MCP and why it matters

3:00 – Heroku’s pivot to AI Platform-as-a-Service

6:45 – Agentic apps, model hosting, and tool execution

10:50 – Why REST isn’t ideal for LLMs

14:10 – Developer experience challenges with MCP

18:00 – Hosting secure MCPs on Heroku

23:00 – Real-world use cases: scaling, healing, recommendations

30:00 – Common scaling challenges and hallucination risks

34:30 – Testing, security, and architecture tips

36:00 – Where to start and final advice on using AI tools effectively

Follow Julián Duque on Social MediaTwitter/X: https://x.com/julian_duque

Linkedin: https://www.linkedin.com/in/juliandavidduque/

Sponsored by This Dot: thisdotlabs.com

  continue reading

169 פרקים

Artwork
iconשתפו
 
Manage episode 484060924 series 2927306
תוכן מסופק על ידי Modern Web. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Modern Web או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

In this episode of the Modern Web Podcast, Rob Ocel and Danny Thompson sit down with Julián Duque, Principal Developer Advocate at Heroku, to talk about Heroku’s evolution into an AI Platform-as-a-Service. Julián breaks down Heroku’s new Managed Inference and Agents (MIA) platform, how they’re supporting Claude, Cohere, and Stable Diffusion, and what makes their developer experience stand out.

They also get into Model Context Protocols (MCPs)—what they are, why they matter, and how they’re quickly becoming the USB-C for AI. From internal tooling to agentic infrastructure and secure AI deployments, this episode explores how MCPs, trusted environments, and better AI dev tools are reshaping how we build modern software.

Key Points from this episode:

- Heroku is evolving into an AI Platform-as-a-Service with its new MIA (Managed Inference and Agents) platform, supporting models like Claude, Cohere, and Stable Diffusion while maintaining a strong developer experience.

- MCPs (Model Context Protocols) are becoming a key standard for extending AI capabilities—offering a structured, secure way for LLMs to access tools, run code, and interact with resources.

- Heroku's AI agents can perform advanced operations like scaling dynos, analyzing logs, and self-healing failed deployments using grounded MCP integrations tied to the Heroku CLI.

- Despite rapid adoption, MCPs still have rough edges—developer experience, tooling, and security protocols are actively improving, and a centralized registry for MCPs is seen as a missing piece.

Chapters

0:00 – What is MCP and why it matters

3:00 – Heroku’s pivot to AI Platform-as-a-Service

6:45 – Agentic apps, model hosting, and tool execution

10:50 – Why REST isn’t ideal for LLMs

14:10 – Developer experience challenges with MCP

18:00 – Hosting secure MCPs on Heroku

23:00 – Real-world use cases: scaling, healing, recommendations

30:00 – Common scaling challenges and hallucination risks

34:30 – Testing, security, and architecture tips

36:00 – Where to start and final advice on using AI tools effectively

Follow Julián Duque on Social MediaTwitter/X: https://x.com/julian_duque

Linkedin: https://www.linkedin.com/in/juliandavidduque/

Sponsored by This Dot: thisdotlabs.com

  continue reading

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