GPT-5.5 Now in Microsoft Foundry (GA): Build Reliable Agents for Real Enterprise Work

Taswar Bhatti April 25, 2026 No Comments

OpenAI’s GPT-5.5 is now generally available (GA) in Microsoft Foundry, and this is one of those releases that matters less for “chat” and more for getting actual work done—end-to-end.

The big theme: messy, multi-step requests → completed tasks, with stronger reliability in planning, tool use, UI navigation, and recovery when something breaks mid-flow.

If you’re building internal copilots, engineering assistants, or “agentic” workflows that touch code + docs + systems, GPT-5.5 is positioned as a practical step forward in coding/debugging intelligence, long-context reasoning, computer-use accuracy, and token efficiency for longer-running workloads.

Why this release is different

In many enterprise environments, the hardest part isn’t generating an answer—it’s executing a workflow: interpret intent, plan steps, call tools, verify output, and keep going even after a failed command or a UI detour.
Microsoft frames Foundry as the “platform layer” that turns frontier models into governable systems (security, compliance, management), while GPT-5.5 brings improvements specifically tuned for sustained professional workflows.

What’s improved in GPT-5.5 (developer lens)

1) Agentic task execution (plan → act → finish)

GPT-5.5 is designed to handle multi-step execution, not just single-turn responses—planning and following through across tools and systems.
That’s exactly what you want when the task is “fix the bug, update the tests, and summarize the PR impact,” rather than “explain the bug.”

2) Coding + debugging that feels closer to real engineering

OpenAI highlights stronger performance in writing and debugging code, while Microsoft emphasizes agentic coding and more reliable execution for engineering workflows.
In practice, this maps well to: navigating large repos, doing root-cause analysis (RCA), anticipating downstream test updates, and validating changes before you ship.

3) Long-context reasoning that stays coherent

Both announcements point to GPT-5.5 handling large documents, codebases, and extended histories without losing the thread—critical for enterprise work where context is fragmented across tickets, specs, and logs.

4) Computer use (UI navigation) with better accuracy + recovery

A lot of agent workflows eventually hit a UI: portals, dashboards, admin blades, internal tools. GPT-5.5 puts emphasis on improved “computer use” accuracy—clicking the right thing, backtracking, and recovering when the workflow changes.

5) Token efficiency for long-running workflows

Long workflows can be expensive—not only because they’re long, but because retries and drift multiply tokens. GPT-5.5 is positioned as more efficient, often completing tasks with fewer tokens and fewer retries (especially in coding-style flows).

Top use cases (what I’d actually build with it)

A) Software engineering workflows (repo-scale)

Navigate large codebases and keep context across multiple files/modules.
Debug ambiguous failures, do RCA, propose fixes, and anticipate impact.
Identify test gaps and generate validation scripts (unit/integration).

B) Document + knowledge work (high-fidelity extraction)

Pull structured insights from contracts/specs/invoices/research docs.
Synthesize across multiple sources while keeping citations/traceability in your workflow design.

C) Agentic business process automation

Plan and execute multi-step workflows across systems (CRM, ITSM, internal portals).
Generate finished artifacts (docs/sheets/decks) as part of an automated pipeline.

D) Computer-use scenarios (UI-driven automation)

Navigate UI flows more accurately; recover when a click path fails.
Great fit for repeatable tasks that don’t have clean APIs (yet).

E) Spreadsheet reasoning (structured data)

Stronger reasoning on structured tables to support summarization, anomaly detection, and transformations

Minimal “hello world” – Chat Completions (C#)

This example mirrors the OpenAI v1 pattern used by Foundry/Azure OpenAI docs and is a good baseline for API-first apps.
(You’ll plug in your endpoint + deployment name; for enterprise, prefer Entra ID flows.)

using Azure.Identity;
using OpenAI;
using OpenAI.Chat;

// Uses Entra ID (recommended). Docs show token-based auth patterns for Foundry/OpenAI v1 usage.
var credential = new DefaultAzureCredential();
var token = credential.GetToken(
    new Azure.Core.TokenRequestContext(new[] { "https://ai.azure.com/.default" })
);

var client = new OpenAIClient(new OpenAIClientOptions
{
    Endpoint = new Uri("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/")
});

// If your SDK version expects a bearer token provider/policy, follow the latest Microsoft Learn guidance.
var chat = client.GetChatClient("YOUR-DEPLOYMENT-NAME"); // deployment name maps to GPT-5.5 deployment

var completion = chat.CompleteChat(
    new SystemChatMessage("You are a senior software engineer assistant. Be concise, validate assumptions."),
    new UserChatMessage("Given this stack trace, propose an RCA and a minimal fix plan. Ask for missing logs.")
);

Console.WriteLine(completion.Content[0].Text);

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using Azure.Identity;

using OpenAI;

using OpenAI.Chat;

// Uses Entra ID (recommended). Docs show token-based auth patterns for Foundry/OpenAI v1 usage.

var credential = new DefaultAzureCredential();

var token = credential.GetToken(

new Azure.Core.TokenRequestContext(new[] { "https://ai.azure.com/.default" })

);

var client = new OpenAIClient(new OpenAIClientOptions

{

Endpoint = new Uri("https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/")

});

// If your SDK version expects a bearer token provider/policy, follow the latest Microsoft Learn guidance.

var chat = client.GetChatClient("YOUR-DEPLOYMENT-NAME"); // deployment name maps to GPT-5.5 deployment

var completion = chat.CompleteChat(

new SystemChatMessage("You are a senior software engineer assistant. Be concise, validate assumptions."),

new UserChatMessage("Given this stack trace, propose an RCA and a minimal fix plan. Ask for missing logs.")

);

Console.WriteLine(completion.Content[0].Text);

Minimal “hello world” – Chat Completions (Python)

Python is great for quick evaluation, prompt iteration, and building internal tooling.

import os
from openai import OpenAI
from azure.identity import DefaultAzureCredential, get_bearer_token_provider

token_provider = get_bearer_token_provider(
    DefaultAzureCredential(),
    "https://ai.azure.com/.default"
)

client = OpenAI(
    base_url="https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/",
    api_key=token_provider
)

resp = client.chat.completions.create(
    model="YOUR-DEPLOYMENT-NAME",  # your GPT-5.5 deployment name
    messages=[
        {"role": "system", "content": "You are a debugging assistant. Provide RCA + fix + tests."},
        {"role": "user", "content": "Here is the error log... (paste). What’s the likely root cause?"}
    ]
)

print(resp.choices[0].message.content)

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import os

from openai import OpenAI

from azure.identity import DefaultAzureCredential, get_bearer_token_provider

token_provider = get_bearer_token_provider(

DefaultAzureCredential(),

"https://ai.azure.com/.default"

)

client = OpenAI(

base_url="https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/",

api_key=token_provider

)

resp = client.chat.completions.create(

model="YOUR-DEPLOYMENT-NAME", # your GPT-5.5 deployment name

messages=[

{"role": "system", "content": "You are a debugging assistant. Provide RCA + fix + tests."},

{"role": "user", "content": "Here is the error log... (paste). What’s the likely root cause?"}

]

)

print(resp.choices[0].message.content)

Conclusion: GPT-5.5 is built for “execution,” not just “answers”

If your AI roadmap includes agents that:

touch multiple tools,
reason across long contexts,
navigate UIs,
generate real artifacts (code/docs/sheets/decks),
and keep going when workflows break…

…then GPT-5.5 in Microsoft Foundry is a release worth testing early—because it targets the exact failure modes that show up when you move from demo to production.
And with Foundry’s deployment model + enterprise governance story, you can evaluate and productionize without reinventing the operational layer every time a new frontier model lands.

Bonus

Watch this video on YouTube

.NET, AI, Azure

AI Agents, Azure AI Foundry, Azure OpenAI, C#, Developer Tools, GPT-5.5, Microsoft Foundry, python

5 Highlights Thursday | 23th April 2026 (#109 Edition)

Taswar Bhatti April 23, 2026 No Comments

Published: 2026-04-23
Source: https://www.linkedin.com/pulse/5-highlights-thursday-23th-april-2026-109-edition-taswar-bhatti-1exif

Here is the #109 edition of 5 Highlights Thursday. Happy Childrens Day if you are in Turkiye. 👶 I hope this newsletter will help you in your Azure journey and keep you informed. Feel free to forward this alng to anyone who you think may enjoy or better ask them to subscribe.

1. Microsoft Agent Framework releasing version 1.0

Watch this video on YouTube

Microsoft Agent Framework has reached version 1.0 — making production-grade agent development feel like normal software development. In this episode, Jorge Arteiro, Shawn Henry and @Rong Lu walk through what’s new in the v1.0 GA release: stable APIs, multi-agent orchestration with handoff patterns, and support for Python and .NET.

2. Using Microsoft Agent Framework with Foundry managed memory

Watch this video on YouTube

In this episode, Jorge Arteiro, Amy Boyd and Lewis Liu dive into Memory in Foundry Agent Service — a managed, long-term memory layer that turns stateless LLM calls into stateful, continuous agents. Lewis Liu and Amy Boyd walk through how memory is natively integrated with Microsoft Agent Framework and LangGraph, enabling agents to persist user preferences, conversation context, and task outcomes across sessions — with zero infrastructure overhead. See how per-user memory scoping, automatic memory extraction, and CRUD APIs give developers full control while keeping enterprise governance built in.

3. Azure confidential computing in the sovereign cloud era

Watch this video on YouTube

Join Vikas Bhatia, head of product for Azure Compute Security & Confidential Computing, as he presents the latest innovations in Azure Confidential Computing and Microsoft Sovereign Cloud. This session explores how Azure empowers organizations to achieve digital sovereignty, secure sensitive data, and meet global compliance requirements. Learn about real-world use cases, hardware advancements, and strategies for resilient, mission-critical workloads—directly from the leader driving Azure’s security vision.

4. Discover, manage, and secure AI agents with Microsoft Agent 365

Watch this video on YouTube

In this session from Vasu Jakkal RSAC 2026 Main Stage keynote, see how Microsoft Agent 365 helps organizations discover, manage, and secure AI agents at scale. Learn how IT and security teams gain centralized visibility into agent activity, apply consistent policies, and protect data across the agent lifecycle, no matter where agents are built or deployed.

5. From code to cloud: Deploy an AI agent to Microsoft Foundry in minutes with azd

Embedded content: From code to cloud: Deploy an AI agent to Microsoft Foundry in minutes with azd

This post walks through the full end-to-end workflow: deploying an AI agent to Microsoft Foundry, invoking it remotely, running it locally for development, and monitoring it in real time—all from Visual Studio (VS) Code.

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

Subscribe on LinkedIn

Have a wonderful Thursday 🙂

Taswar

Newsletter

.net, AI, azure, Azure AI Foundry, Azure Weekly Digest, Cloud Computing, Microsoft Azure, security

gpt-image-2-microsoft-foundry-for-developers

GPT‑Image‑2 Comes to Microsoft Foundry: What Developers Need to Know

Taswar Bhatti April 22, 2026 1 Comment

Generative AI for images has gone from “cool demo” to something teams actually run in production. Microsoft has now made OpenAI’s GPT‑image‑2 generally available in Microsoft Foundry, and it’s a meaningful upgrade for developers building image-heavy workflows at scale.

This isn’t just “another image model.” GPT‑image‑2 focuses on instruction accuracy, higher resolution output, localization, and enterprise‑ready scaling—all crucial if you’re building real products instead of playing with prompts.

Let’s break down what’s new, why it matters, and how this changes image generation inside Microsoft Foundry.

Key Improvements in GPT‑Image‑2

1. Stronger Real‑World Context

GPT‑image‑2 is trained with knowledge up to December 2025, giving it better awareness of:

Current products
Modern design patterns
Recent cultural references

More importantly, it uses enhanced “thinking” capabilities to:

Refine outputs
Self-check generated content
Create multiple image variations from a single request

That makes it feel less like a static image generator and more like a creative assistant you can automate.

2. Built‑In Multilingual and Localization Support

One standout improvement is better multilingual understanding, especially for:

Japanese
Korean
Chinese
Hindi
Bengali

This matters when you need:

Text rendered correctly inside images
Culturally accurate visuals
Region-specific variations generated automatically

For global products, this alone removes a huge amount of downstream manual work.

Example of image created with GPT-Image-2 vs MAI-Image-2e

var prompt = “Create a simple poster-style graphic with 3 panels showing the same message rendered in Japanese, Korean, and Hindi. The message should be short and generic like ‘Hello World’. Use clean typography, white text on colored blocks, modern UI style, high legibility, no logos.”;

GPT Image 2	MAI Image 2e
GPT-Image-2	MAI-Image-2e

3. High‑Resolution Image Generation (Up to 4K)

GPT‑image‑2 introduces 4K image support, making it viable for:

Marketing assets
Product mockups
High-quality digital content

Important technical constraints to keep in mind:

Maximum pixel count: ~8.3 million pixels
Minimum pixel count: ~655k pixels
Dimensions must be multiples of 16
Requests exceeding limits are automatically resized

Supported resolutions include:

1024 × 1024
1536 × 1024
1024 × 1536
4K custom-sized images (within limits)

This brings image generation much closer to production-grade quality, not just prototyping.

Intelligent Routing: Less Guesswork for Developers

One of the more subtle—but important—features is the intelligent routing layer.

Instead of forcing developers to manually pick image sizes every time, Foundry can now automatically select the best configuration based on the request.

Routing Mode 1: Legacy Size Selection

If you’ve used previous image APIs, this mode maps your request to familiar tiers (small, standard, large) without you changing anything.

Routing Mode 2: Token‑Based Size Buckets

A more advanced mode where requests are routed using token buckets (16 → 96 tokens), offering more granular scaling while still abstracting complexity away from the app layer.

The net result: cleaner code, fewer hardcoded decisions, and more consistent outputs.

C# Code to generate your own image

using Azure.Identity;
using Azure.Core;
using System.Net.Http.Headers;
using System.Text;
using System.Text.Json;

class Program
{
    static async Task Main(string[] args)
    {

        string endpoint_gpt = GetEnvironmentVariable("AZURE_GPT_ENDPOINT") ??
            "https://xyz.cognitiveservices.azure.com/openai/deployments/gpt-image-2/images/generations?api-version=2024-02-01";
                
        string gptModelName = GetEnvironmentVariable("AZURE_GPT_MODEL") ?? "gpt-image-2";
        string prompt = "Create a simple poster-style graphic with 3 panels showing the same message rendered in Japanese, Korean, and Hindi. The message should be short and generic like 'Hello World'. Use clean typography, white text on colored blocks, modern UI style, high legibility, no logos.";        

        var credential = new DefaultAzureCredential();
        AccessToken token = await credential.GetTokenAsync(
            new TokenRequestContext(new[] { "https://cognitiveservices.azure.com/.default" }));

        using var http = new HttpClient();
        http.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", token.Token);
        
        var gpt_payload = new
        {
            prompt,
            model = gptModelName,
            size = "1024x1024",
            quality = "medium",
            output_compression = 100,
            output_format = "png",
            n = 1
        };
        
        using var content = new StringContent(
            JsonSerializer.Serialize(gpt_payload),
            Encoding.UTF8,
            "application/json");

        using HttpResponseMessage response = await http.PostAsync(endpoint_gpt, content);
        string responseBody = await response.Content.ReadAsStringAsync();

        if (!response.IsSuccessStatusCode)
        {
            Console.WriteLine($"Image generation failed: {(int)response.StatusCode} {response.ReasonPhrase}");
            Console.WriteLine(responseBody);
            throw new InvalidOperationException("GPT Image 2 image generation request failed.");
        }

        using JsonDocument json = JsonDocument.Parse(responseBody);
        string? b64 = json.RootElement
            .GetProperty("data")[0]
            .GetProperty("b64_json")
            .GetString();

        if (string.IsNullOrWhiteSpace(b64))
        {
            throw new InvalidOperationException("Response did not contain data[0].b64_json.");
        }

        byte[] imageBytes = Convert.FromBase64String(b64);
        string outputPath = Path.Combine(Environment.CurrentDirectory, "generated_image.png");
        await File.WriteAllBytesAsync(outputPath, imageBytes);
        Console.WriteLine($"Image saved to: {outputPath}");
    }

    static string? GetEnvironmentVariable(string name) => Environment.GetEnvironmentVariable(name);
}

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using Azure.Identity;

using Azure.Core;

using System.Net.Http.Headers;

using System.Text;

using System.Text.Json;

class Program

{

static async Task Main(string[] args)

{

string endpoint_gpt = GetEnvironmentVariable("AZURE_GPT_ENDPOINT") ??

"https://xyz.cognitiveservices.azure.com/openai/deployments/gpt-image-2/images/generations?api-version=2024-02-01";

string gptModelName = GetEnvironmentVariable("AZURE_GPT_MODEL") ?? "gpt-image-2";

string prompt = "Create a simple poster-style graphic with 3 panels showing the same message rendered in Japanese, Korean, and Hindi. The message should be short and generic like 'Hello World'. Use clean typography, white text on colored blocks, modern UI style, high legibility, no logos.";

var credential = new DefaultAzureCredential();

AccessToken token = await credential.GetTokenAsync(

new TokenRequestContext(new[] { "https://cognitiveservices.azure.com/.default" }));

using var http = new HttpClient();

http.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", token.Token);

var gpt_payload = new

{

prompt,

model = gptModelName,

size = "1024x1024",

quality = "medium",

output_compression = 100,

output_format = "png",

n = 1

};

using var content = new StringContent(

JsonSerializer.Serialize(gpt_payload),

Encoding.UTF8,

"application/json");

using HttpResponseMessage response = await http.PostAsync(endpoint_gpt, content);

string responseBody = await response.Content.ReadAsStringAsync();

if (!response.IsSuccessStatusCode)

{

Console.WriteLine($"Image generation failed: {(int)response.StatusCode} {response.ReasonPhrase}");

Console.WriteLine(responseBody);

throw new InvalidOperationException("GPT Image 2 image generation request failed.");

}

using JsonDocument json = JsonDocument.Parse(responseBody);

string? b64 = json.RootElement

.GetProperty("data")[0]

.GetProperty("b64_json")

.GetString();

if (string.IsNullOrWhiteSpace(b64))

{

throw new InvalidOperationException("Response did not contain data[0].b64_json.");

}

byte[] imageBytes = Convert.FromBase64String(b64);

string outputPath = Path.Combine(Environment.CurrentDirectory, "generated_image.png");

await File.WriteAllBytesAsync(outputPath, imageBytes);

Console.WriteLine($"Image saved to: {outputPath}");

}

static string? GetEnvironmentVariable(string name) => Environment.GetEnvironmentVariable(name);

}

Final Thoughts

GPT‑image‑2 is less about flashy demos and more about operational reality:

Fewer retries
Better instruction adherence
Cleaner localization
Higher‑quality visuals at scale

If you’re building AI‑powered apps, internal tools, or content pipelines on Azure, this model is a strong signal that image generation is now a serious enterprise capability, not an experiment.

AI

AI, GPT, GPT-Image-2

5 Highlights Thursday | 16th April 2026 (#108 Edition)

Taswar Bhatti April 16, 2026 No Comments

Published: 2026-04-16
Source: https://www.linkedin.com/pulse/5-highlights-thursday-16th-april-2026-108-edition-taswar-bhatti-boevf

Here is the #108 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Use AI to Achieve Operational Excellence with the Well-Architected Framework practices

Watch this video on YouTube

If you’re a cloud architect, platform engineer, or developer responsible for operating systems in production, this video Boris Scholl & Niels Buit will help you understand Well Architected Framework and how to apply AI practically, assess risks and tradeoffs in real-world environments.

2. Next-Level SQL in VS Code: GitHub Copilot Custom Instructions, Plan Mode & Skills

Watch this video on YouTube

GitHub Copilot already generates awesome SQL code but awesome is different from aligned with your team. In this episode, Anna Hoffman & Carlos Robles explore how to take full control of GitHub Copilot context inside VS Code using the MSSQL extension.

3. The future of identity protection with Predictive Shielding

Watch this video on YouTube

In this episode, we explore how predictive shielding anticipates attacks before they unfold. Nimrod Roimy my and Aviv Sharon join us to share how Microsoft is the first vendor to leverage attack path graphs to detect early signs of compromise, pioneering a way to harden devices that store critical identities and proactively block domain-wide breaches.

4. Migrate Oracle Workloads to PostgreSQL Using AI-Powered Tools in the VS Code PostgreSQL Extension

Watch this video on YouTube

This week on Azure Friday, Scott Hanselman talks with Jonathon Frost about AI-enhanced migration from Oracle to PostgreSQL using the VS Code PostgreSQL extension. See how developers can automate schema conversion, transform application code, and validate results using an intelligent, agent-driven workflow.

5. Is Postgres the wave of the future?

Watch this video on YouTube

In this episode of The Shift, members of the Microsoft Azure Database team, Eric Hudson , Marko Hotti , Claire Giordano and Abinav Rameesh explore a question from you, our community and the question in mind is Is Postgres the wave of the future?

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

Subscribe on LinkedIn

Have a wonderful Thursday 🙂

Taswar

Newsletter

AI, azure, Azure Weekly Digest, Cloud Computing, Databases, GitHub Copilot, Microsoft Azure, PostgreSQL, security

5 Highlights Thursday | 9th April 2026 (#107 Edition)

Taswar Bhatti April 9, 2026 No Comments

Published: 2026-04-09
Source: https://www.linkedin.com/pulse/5-highlights-thursday-9th-april-2026-107-edition-taswar-bhatti-bgcyf

Here is the #107 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Tech Brief: Agentic DevOps with GitHub Copilot (April 28th)

Tech Brief: Agentic DevOps with GitHub Copilot

Join the Tech Brief if you are building intelligent applications requires more than just powerful AI models—it also demands a seamless, adaptive development life cycle. Join us to explore how agentic DevOps is transforming the way that teams build, deploy, and scale AI-powered applications on Microsoft Azure. This session is designed for technology and development decision-makers.

2. Network-layer data protection with Microsoft Entra GSA and Purview DLP

Watch this video on YouTube

Watch the session to learn how this Network Data Security integration allows Purview DLP policies to inspect and control sensitive file traffic in transit through GSA Internet Access, preventing data from reaching unsanctioned cloud apps, generative AI platforms, and cloud storage services.

3. Clean Architecture with ASP .NET Core 10

Watch this video on YouTube

ASP.NET Core provides better support for clean, testable, maintainable architectures than any of its predecessors. Learn the underlying principles that apply to project/solution organization, how best to arrange your projects to support loosely coupled, maintainable code, and how to refactor existing solutions toward this architecture.

4. Building a Real-Time Multi-Agent UI with AG-UI and Microsoft Agent Framework Workflows

Embedded content: Building a Real-Time Multi-Agent UI with AG-UI and Microsoft Agent Framework Workflows | Microsoft Agent Framework

This post shows what a better answer looks like. It build’s a customer support workflow that pairs Microsoft Agent Framework (MAF) handoffs with AG-UI,

5. GitHub Copilot CLI in Action: Getting Started

Watch this video on YouTube

GitHub Copilot CLI provides a terminal-based AI coding companion that can be used to explain code, generate code, do code reviews, work with PRs, run and generate tests, and much more. In this video you’ll learn about what Copilot CLI is, how you can get started using it, and examples of it in action.

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

Subscribe on LinkedIn

Have a wonderful Thursday 🙂

Taswar

Newsletter

.net, AI, azure, Azure DevOps, Azure Weekly Digest, Cloud Computing, GitHub Copilot, Microsoft Azure, Networking, security

5 Highlights Thursday | 2nd April 2026 (#106 Edition)

Taswar Bhatti April 2, 2026 No Comments

Published: 2026-04-02
Source: https://www.linkedin.com/pulse/5-highlights-thursday-2nd-april-2026-106-edition-taswar-bhatti-u3pxf

Here is the #106 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Native Regex in SQL Server 2025

Watch this video on YouTube

REGEX in Microsoft SQL (SQL Server, Azure SQL, SQL database in Fabric) – did you know we have T-SQL functions for this and it just works? Join Anna Hoffman & Ed Pollack where they take us through it, on #DataExposed #MVPEdition.

2. Foundry IQ: Querying the Multi-Source AI Knowledge Bases

Watch this video on YouTube

The third episode of The IQ Series opens with Amanda Silver introducing Knowledge Bases and how multiple Knowledge Sources unify behind a single endpoint. Pamela Fox and Matthew Gotteiner then walk through topic-centric Knowledge Bases and demonstrate a multi-source query path, showing how Foundry IQ moves from isolated data pipelines to reusable, queryable knowledge. The episode closes with Tomomi Imura visual doodles, illustrating how this shift unlocks a more connected and scalable knowledge architecture.

3. Developer Tools for Agent ID: SDKs, CLIs & Samples

Watch this video on YouTube

Join Kyle Marsh on how to accelerate agent and app development with the Microsoft Entra developer toolchain in this deep‑dive session focused on real‑world identity scenarios. Explore SDKs, sample repositories, and ready‑to‑run resources that help you acquire tokens, implement consent flows, and securely call downstream APIs with confidence.

4. Modernizing Legacy .NET applications with GitHub Copilot

Watch this video on YouTube

Modernizing legacy .NET applications is often intimidating: no one wants to be the developer who breaks code in production. But what if you could approach it with low risk and high confidence? In this live coding session, Jorge Balderas, will demonstrate how GitHub Copilot CLI and the modernize-dotnet custom agent can be used to safely and systematically modernize legacy code.

5. Decision Matrix: API vs MCP Tools — The Great Integration Showdown

Embedded content: Decision Matrix: API vs MCP Tools — The Great Integration Showdown 🥊 | Microsoft Community Hub

Here is a blog post by Sabyasachi Samaddar on deep dive of API vs MCP.

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

Subscribe on LinkedIn

Have a wonderful Thursday 🙂

Taswar

Newsletter

AI, AKS, azure, Azure AI Foundry, Azure SQL, Azure Weekly Digest, Cloud Computing, Databases, GitHub Copilot, Kubernetes, Microsoft Azure, security

5 Highlights Thursday | 26th March 2026 (#105 Edition)

Taswar Bhatti March 26, 2026 No Comments

Published: 2026-03-26
Source: https://www.linkedin.com/pulse/5-highlights-thursday-26th-march-2026-105-edition-taswar-bhatti-ypuxf

Here is the #105 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Build & Deploy a fullstack JavaScript App with GitHub Copilot CLI and Azure MCP

Watch this video on YouTube

Watch this video where Karishma Ghiya builds a fullstack JavaScript-based photo gallery web app from scratch using GitHub Copilot CLI and Azure MCP with the Azure Skills plugin, then deploy it to Microsoft Azure.

2. Ten Open-Source projects from KubeCon Project Pavillion

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Watch Jorge Arteiro at KubeCon Atlanta 2025 Project Pavillion. It’s a group of 10 Short videos of CNCF projects. Projects are COPA, Drasi, External Secrets, Headlamp, Inspektor Gadget, K3S, KubeScape, Fluentd/FluentBit, Dapr and Flux

3. Runtime Reality Check – from poisoned packages to AI workloads as adversaries.

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Cloud attackers are gaining the insider advantage. In this latest S.T.A.R. video episode, our team Avi Sharma, Diwas Sedai , Raae Wolfram reveals how the latest attacks are bypassing perimeters to strike directly in cloud runtimes. Key topics, Learn how adversaries inject malicious code into dependencies and exploit package managers.

4. .NET AI Community Standup: Real-World AI Agent Architecture in .NET

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Join Bruno Capuano & Justin Yoo on what does a real AI agent application look like beyond Hello World? Using the open-source Interview Coach sample, we’ll explore production patterns for building multi-agent systems in .NET using: – Microsoft Agent Framework – Microsoft Foundry as the model backend – Model Context Protocol (MCP) for tool integration – Aspire for orchestration and observability

5. Generative AI for Beginners .NET: Version 2 on .NET 10

Embedded content: Generative AI for Beginners .NET: Version 2 on .NET 10 – .NET Blog

AI needle keeps moving thus here is version 2 of Gen AI for Beginners, with completely rewritten curriculum with five structured lessons, updated to .NET 10, etc

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

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Taswar

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.net, AI, azure, Azure AI Foundry, Azure Weekly Digest, Cloud Computing, GitHub Copilot, Microsoft Azure, Networking

5 Highlights Thursday | 19th March 2026 (#104 Edition)

Taswar Bhatti March 19, 2026 No Comments

Published: 2026-03-19
Source: https://www.linkedin.com/pulse/5-highlights-thursday-19th-march-2026-104-edition-taswar-bhatti-n8xvf

Happy Eid (iyi Bayramlar) for the everyone; here is the #104 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Foundry IQ: Unlocking Knowledge for Your Agents

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Watch the first IQ Series with Pablo Castro introducing Foundry IQ and the role it plays in building knowledge‑centric AI systems. Ayça Baş and Farzad Sunavala then walk through how Foundry IQ supports agents by bringing together core building blocks such as retrieval, reasoning, synthesis, and orchestration, and how these components work together in practice.

2. Build AI Agents with Your Data for Under $10 a Month!

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Watch Bob Ward, Principal Architect on the Azure Data team, where Bob walks through building a simple AI Application that ‘knows’ your data using Copilot Studio and Azure SQL Database. Help your marketing team or your shoppers in these real-life use cases – and then rise and repeat to build more! All for only $10 a month, with no coding skills required.

3.Beyond KQL: Unlocking SOC Insights with Sentinel data lake Jupyter Notebook

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Join Javier Soriano and David H. where they introduce Jupyter Notebooks, explore the benefits they offer, and highlight their value within Microsoft Sentinel’s data lake. Join them for a step-by-step walkthrough on getting started, reading from and writing to the data lake, scheduling recurring notebook tasks, and applying advanced techniques to shape and analyze your data.

4. Building MCP on Entra: Design Choices for Enterprise Agents

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Join Merill Fernando where in this session, he explores approaches for integrating MCP with Microsoft Entra Agent ID, with a focus on the foundational aspects of agent identity, consent, and authorization in enterprise environments.

5. Deploying Python apps on Azure App Service

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Join Scott Hanselman and Nir Mashkowski where they will go through the simplest way to get started with Python in the cloud. The video explores different deployment approaches and recent changes to the platform to be even simpler.

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

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Have a wonderful Thursday 🙂

Taswar

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AI, azure, Azure AI Foundry, Azure SQL, Azure Weekly Digest, Cloud Computing, Databases, GitHub Copilot, Microsoft Azure, Microsoft Sentinel, Networking, security

5 Highlights Thursday | 12th March 2026 (#103 Edition)

Taswar Bhatti March 12, 2026 No Comments

Published: 2026-03-12
Source: https://www.linkedin.com/pulse/5-highlights-thursday-12th-march-2026-103-edition-taswar-bhatti-aqn3f

Here is the #103 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Agent‑ready in 30 days: a practical blueprint for Copilot Agents

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Join Daniel Rohregger on Agent ready in 30 days where he explains how enterprises don’t need a massive program to start with agents! They need a safe, fast, and provable path. This session delivers a 30‑day blueprint to launch your first Microsoft 365 agent fast, easy and securely. Including a long‑term strategy for a scalable agent environment in M365. Learn how to finally cut oversharing by govern Teams and SharePoint Online and use Purview and label controls! I share best practices and tips for agent management to ensure sustainable agentic success.

2. Figma MCP for VS Code: Bringing Designs to Life with AI, with Joanna Oikawa

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Join Joanna Oikawa & John Maeda on how designers have long handed off work from Figma to engineering—but Model Context Protocol (MCP) is changing that workflow. In this episode of Cozy AI Kitchen, Joanna Oikawa (Product Design Lead, VS Code) walks through how Figma MCP connects Figma designs directly to VS Code, enabling faster iteration, live collaboration, and AI‑assisted UI development.

3. QR code authentication: Fast, simple sign‑in designed for Frontline Workers

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Join Akshat Goel where he explains QR Code Auth. Frontline teams often share mobile devices, and long usernames and passwords slow work down. This session introduces QR code authentication in Microsoft Entra ID, a faster and more secure way to sign in on shared iOS, iPadOS, and Android devices using a unique QR code and PIN. No personal phones or complex credentials required

4. What’s new in Microsoft Foundry | February 2026

Embedded content: What's new in Microsoft Foundry | February 2026 | Microsoft Foundry Blog

Here is a quick read for what’s new in Microsoft Foundry 2026 by Nick Brady

5. Getting started with GitHub Copilot CLI | Tutorial for beginners

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In this video, Christopher Harrison covers the essentials of getting started with your new terminal-based AI coding assistant: the GitHub Copilot CLI.

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

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Taswar

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AI, AKS, azure, Azure AI Foundry, Azure Weekly Digest, Cloud Computing, GitHub Copilot, Kubernetes, Microsoft Azure, Networking, security

5 Highlights Thursday | 5th March 2026 (#102 Edition)

Taswar Bhatti March 5, 2026 No Comments

Published: 2026-03-05
Source: https://www.linkedin.com/pulse/5-highlights-thursday-5th-march-2026-102-edition-taswar-bhatti-4pkcf

Here is the #102 edition of 5 Highlights Thursday to help you in your Azure journey and keep you informed. Feel free to forward this along to anyone who you think may enjoy or better ask them to subscribe.

1. Agentic RAG for Everyone Using Azure SQL, OpenAI, and Web Apps

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Join the legendary Davide Mauri as he builds an agentic RAG solution on a tiny budget using Azure SQL, OpenAI, and Web Apps.

2. VS Code for the Web

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Join Scott Hanselman & Meera Haridasa on how to get started with VS Code for the Web – Azure to seamlessly run, debug and deploy your applications with no setup! This browser based VS Code environment allows you to work as you would locally, but wherever you are. Watch this video to see us create an enterprise-grade application, run it and deploy it to Azure within minutes!

3. Azure Firewall Integration with Microsoft Sentinel

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Join Shabaz Shaik & Sai Prasanna Kishor for a focused session on how Azure Firewall integrates with Microsoft Sentinel to enhance threat visibility and streamline security investigations.

4. Vector Data in .NET – Building Blocks for AI Part 2

Embedded content: Vector Data in .NET – Building Blocks for AI Part 2 – .NET Blog

If you want to earn about VectorData in .NET, then you dont want to miss the series written by Jeremy Likness Where he explains the same benefits to vector databases that Microsoft.Extensions.AI brings to LLMs.

5. Reduce Azure Networking Costs: Smart Routing, Locality & Efficient Connectivity

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Join Andrea Michael on how to cut Azure networking spend by minimizing egress, optimizing routing, using Private Link and NAT Gateway, and right‑sizing ExpressRoute and load balancing services—without sacrificing performance.

As always, please give me feedback on LinkedIn. Which bullet above is your favorite? What do you want more or less of? Other suggestions? Please let me know.

Last by not least, know someone who might be interested in this newsletter? Share it with them.

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Have a wonderful Thursday 🙂

Taswar

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.net, AI, azure, Azure SQL, Azure Weekly Digest, Cloud Computing, Cost Optimization, Databases, Microsoft Azure, Microsoft Sentinel, Networking, security

GPT-5.5 Now in Microsoft Foundry (GA): Build Reliable Agents for Real Enterprise Work

Why this release is different

What’s improved in GPT-5.5 (developer lens)

1) Agentic task execution (plan → act → finish)

2) Coding + debugging that feels closer to real engineering

3) Long-context reasoning that stays coherent

4) Computer use (UI navigation) with better accuracy + recovery

5) Token efficiency for long-running workflows

Top use cases (what I’d actually build with it)

A) Software engineering workflows (repo-scale)

B) Document + knowledge work (high-fidelity extraction)

C) Agentic business process automation

D) Computer-use scenarios (UI-driven automation)

E) Spreadsheet reasoning (structured data)

Minimal “hello world” – Chat Completions (C#)

Minimal “hello world” – Chat Completions (Python)

Conclusion: GPT-5.5 is built for “execution,” not just “answers”

Bonus

GPT‑Image‑2 Comes to Microsoft Foundry: What Developers Need to Know

Key Improvements in GPT‑Image‑2

1. Stronger Real‑World Context

2. Built‑In Multilingual and Localization Support

Example of image created with GPT-Image-2 vs MAI-Image-2e

3. High‑Resolution Image Generation (Up to 4K)

Intelligent Routing: Less Guesswork for Developers

Routing Mode 1: Legacy Size Selection

Routing Mode 2: Token‑Based Size Buckets

C# Code to generate your own image

Final Thoughts

Opinions are my own and not the views of my employer

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