MCP For Software Engineers | Part 1 : Building Your First Server New to MCP? Heres how to build your first MCP server and a Host Application that integrates and uses the server.

[1] MCP For Software Engineers | Part 1 : Building Your First Server newsletter.victordibia.com/p/mcp-for-so...
[2] Can You Build Agent2Agent Communication on MCP? Yes! developer.microsoft.com/blog/can-you...

- Resources: Defining server resources, client operations (list/read/subscribe), and real-time update notifications
- Prompts: Creating reusable LLM prompt templates that can be used to modify host application behavior without modifying client/host application code.

Part 2 of the series [1] is now out in which I explore the low level MCP python api and cover:

- Tools: Advanced features including annotations, requesting user input (elicitation), LLM assistance (sampling), progress notifications, cancellation, and structured return types

MCP For Software Engineers | Part 2: Interactive & Long-Running Tools (Progress streaming, User Input, Cancellation), Resources & Prompts A deep dive into implementing Tools, Resources, Prompts, Roots in the MCP

MCP For Software Engineers | Part 2: Interactive & Long-Running Tools (Progress streaming, User Input, Cancellation), Resources & Prompts

Most MCP tutorials only show simple request/response patterns. But MCP can handle SO much more! newsletter.victordibia.com/p/mcp-for-so...

- How to build long-running agents with a complete Python implementation (an MCP server with a travel agent and research agents that stream updates, request input and are resumable.)

The article covers:

- How to build agent-to-agent communication with MCP capabilities where MCP hosts and tools both act as intelligent agents
- Four key capabilities that make MCP tools “agentic” – streaming, resumability, durability, and multi-turn interactions

Can You Build Agent2Agent Communication on MCP?
Yes.

I wrote an article about how you can compose some of the recent features within MCP( resumable streams, elicitation, sampling, and notifications ) to implement long running agents (as tools):
devblogs.microsoft.com/blog/can-you...

4 UX Design Principles for Semi-Autonomous Multi-Agent Systems

I gave a keynote talk at the June AI.Engineer conf
newsletter.victordibia.com/p/4-ux-desig...
Bonus: I cover lessons from building a multi-agent system from scratch

PSA: Start with a non-agent baseline, invest in tools and evals, before implementing complex agentic behaviours newsletter.victordibia.com/p/4-ux-desig...

There is a new version that should be released this week that supports MCP workbenches (including MCP servers).
Will update here!

Yay!!

Thanks for the kind words folks! I am fortunate to have great colleagues like you both!! I should hang out on @bsky.app more often!!

YouTube video by Designing With AI by Victor Dibia A Friendly Introduction to AutoGen Studio v0.4 (UI for Building AI Agents with AutoGen)

A walk through of the new v0.4 version of AutoGen Studio.
www.youtube.com/watch?v=oum6...

2024: A year of extraordinary progress and advancement in AI As we move into 2025, we’re looking back at the astonishing progress in AI in 2024.

Demis Hassabis, James Manyika, and I wrote up an overview of the AI research work & advances across Google in 2024 (Gemini, NotebookLM, robotics, ML for science, & advances in responsible AI+more). 🎊

Given it a read or paste it into NotebookLM to listen, if you prefer!

blog.google/technology/a...

Some of the hardest posts to write are not the ones that require writing code or running extensive experiments. Its usually the ones that require sifting through a host of noisy ideas, brutally clear thinking and distilling clear insights or positions.

Once it is complete and communicated well, it looks straightforward and simple.

It is not.

Some of the hardest posts to write are not the ones that require writing code or running extensive experiments. Its usually the ones that require sifting through a host of noisy ideas, brutally clear thinking and distilling clear insights or positions.

With AI, we can have software creators that dont understand complex software systems they create. We’d need to explore co-creation setups that minimize this sort of outcomes.

Yes, drivers dont know how car engines work, pilots probably dont know the details of airplane engines … but mechanics and jet engine designers do.

An interesting conundrum with working with AI tools (e.g., a coding assistant in this case) is that you can genuinely use it to create a complex system which you do not understand.

There is still more work to be done, and we are all excited to make progress with the community!

I will be writing more and showing more examples - afterall a framework is only useful to the extent that it can be used to easily express ideas.

Async stack, event-based messaging, improved observability and control, a low level extremely flexible core api and a high level api with presets, and an improved autogen studio!

I am incredibly excited to share the release of AutoGen v0.4.
We have learned alot from all of the emerging simple and complex ways people want to build agents and we believe this version gets us closer to those goals

A the AI field evolves, the value of the ML/AI PhD is changing newsletter.victordibia.com/p/you-have-a...

You have 'AI Fatigue' - Thats Why You Feel Awful When Progress Becomes a Sprint: The Human Side of AI's Rapid Advancement

You have 'AI Fatigue' - Thats Why You Feel Awful
newsletter.victordibia.com/p/you-have-a...

Hello and welcome @jeffdean.bsky.social !

The lesson?
Right now is the greatest time to work on a side project.

AI Agents 2024 Rewind - A Year of Building and Learning Listen now (14 mins) | What were the top 5 trends in AI Multi-Agent Systems from 2024? What can we expect in 2025?

How do you stay in touch or updated ? I'll keep sharing what I learn through my newsletter - consider subscribing newsletter.victordibia.com/p/ai-agents-...

5. End-to-End Agent Benchmarks

Before: Ad-hoc evaluation focused on individual model capabilities (language, reasoning, tool use)

Trend: Comprehensive task completion benchmarks measuring end-to-end agent performance.

4. A Shift to Complex Tasks and the Rise of Frameworks

Before: Agents built as chains and tool-calling sequences patterns applied to simple tasks.

Trend: Sophisticated patterns for handling complex, multi-step tasks requiring planning, reflection, and coordination.