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MCP Vulnerabilities Every Developer Should Know

MCP’s blowing up across platforms—but the security? Still sketchy. Think tool description injection. Botched OAuth. Open doors to supply chain attacks. The new MCP 2025-06-18 spec tries to clean house (no token passthrough, mandatory user consent), but most real-world setups either drag their feet ..

MCP Vulnerabilities Every Developer Should Know
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Building AI Products In The Probabilistic Era

Modern AI broke the rulebook. By spitting outstochastic outputs from unbounded inputs, it flipped software dev from a game of precision to one of probability. Old tools—funnels, SLO dashboards, crisp A/B tests—don’t quite fit anymore. They were built for systems that behaved. Today’s AI stacks mov..

Building AI Products In The Probabilistic Era
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Tiny Agents in Python: a MCP-powered agent in ~70 lines of code

A new demo walks through buildingTiny Agents in Python—just ~70 lines using theModel Context Protocol (MCP). No boilerplate. Just clean LLM-to-tool hookups with standardized agent configs. Agents plug into multiple MCP servers out of the box—from local filesystems to Playwright browsers—and handle ..

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Myth Or Reality: Will AI Replace Computer Programmers?

Generative AI tools likeGPT-4oandClaude Sonnetnow handle the grunt work—fixing bugs, cranking out code, writing docs—with scary accuracy. Amazon and Anthropic are already hinting at hiring fewer engineers. But the jobs aren’t vanishing; they’re mutating...

Myth Or Reality: Will AI Replace Computer Programmers?
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Building an AI-Powered E-commerce Chat Assistant with MongoDB

freeCodeCamp dropped a new course that walks devs through building an AI-powered shopping agent from scratch. It ties togetherLangGraphfor orchestration,Geminifor reasoning, andMongoDB Atlasas the vector memory layer. The build covers aNode.js backend, aReact frontend, and wires inmulti-step agent ..

Building an AI-Powered E-commerce Chat Assistant with MongoDB
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Evolving our real-time timeseries storage again: Built in Rust for performance at scale

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Evolving our real-time timeseries storage again: Built in Rust for performance at scale
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Can LLMs replace on call SREs today?

ClickHouse ran five LLMs through an autonomous root cause gauntlet using OpenTelemetry data. None nailed it solo. OpenAI’s o3 and Claude Sonnet 4 came closest. GPT-4.1 was the cheapest brain on the block. Things got weird under the hood. Token usage spiked unpredictably. Queries slammed observabili..

Can LLMs replace on call SREs today?
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Migrating Airbnb’s JVM Monorepo to Bazel

Airbnb yanked tens of millions of lines of Java, Kotlin, and Scala out of Gradle and dropped them intoBazel. Why? Faster builds, reproducible results, and smoother dev workflows. They didn’t just swap tools—they rewired the whole thing. A customautomated build file generatornow slices up targets fi..

Migrating Airbnb’s JVM Monorepo to Bazel
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Worktrees: Git's best kept secret (and why you should use them)

Git worktrees have been around since 2015, but few devs use them like they could. They let you work on multiple branches at once—each in its own directory—without the usual stash-switch-stash-repeat dance. The real power move? Pair them with abare repo. That gives you a clean, central base where ea..

Worktrees: Git's best kept secret (and why you should use them)
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Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps

GitHub Advanced Security for Azure DevOps just got sharper: it now checks if leaked secrets are actuallyvalid. Secrets are flagged asActiveorUnknownby pinging providers in real time. No setup needed. It auto-kicks in for supported secret types. Why care?Because not every secret leak is an emergenc..

Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps
The use of artificial intelligence (AI) in e-commerce has resulted in significant enhancements to various aspects of the customer experience, including personalization, operations, and sales.

Natural language generation (NLG) tools, powered by machine learning algorithms, have emerged as one of the key ways in which AI has facilitated these improvements. These tools can autonomously create human-like written content, such as product descriptions and website copy, thereby reducing the workload of content creators. By integrating AI with Magento 2, online retailers can reap a multitude of benefits.

MageComp’s Magento 2 ChatGPT AI PRO extension automatically generates content for your Magento 2 store. The AI-powered Magento 2 extension seamlessly streamlines your website content operations. The ChatGPT AI for Magento 2 module automatically generates multiple types of website content like product description, metadata, image ALT text and other CMS page descriptions.

The admin is allowed to choose the length of the metadata and image ALT text content and the Magento 2 plugin will generate the content according to that. The plugin also lets the admin set custom prompts for AI-powered description generation. With the Magento 2 ChatGPT AI PRO module, Magento admins can save tons of valuable time and invest that time in other strategic activities.

Why Choose MageComp’s Magento 2 ChatGPT AI Pro extension?

Connects your Magento 2 store with Open API key.
Increases your Magento 2 store’s productivity.
Generates AI-powered content with the help of the page builder.
You can easily generate SEO-rich website content in bulk.
The module allows you to choose the content limit you want to generate.
You can add content prompts for exact AI-powered results.
Generates metadata like page titles, meta keywords and meta descriptions.
Speed up your content development process.
Improves your search engine rankings with SEO-rich keywords.
Boosts your business by creating SEO-rich content for it.

For More Magento 2 Extension Visit Magecomp.Com