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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 .. read more  

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Context Engineering for AI Agents: Lessons from Building Manus

Failures make great teachers—especially for LLMs. Stuffing failed attempts right into the prompt helps agents recalibrate. It nudges their internal priors, cuts down on repeat mistakes, and sparks smarter behavior... read more  

Context Engineering for AI Agents: Lessons from Building Manus
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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 .. read more  

MCP Vulnerabilities Every Developer Should Know
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Is GPT-5 really worse than GPT-4o? Ars puts them to the test.

OpenAI walked back its latest release after users flaggedGPT-5for sounding flat, hallucinating more, and losing creative spark. The fix? Rolling back to the friendlierGPT-4o. Head-to-head tests told a nuanced story:GPT-5nailed accuracy and structure across most prompts. But when the task called for.. read more  

Is GPT-5 really worse than GPT-4o? Ars puts them to the test.
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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.. read more  

Building AI Products In The Probabilistic Era
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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 .. read more  

Building an AI-Powered E-commerce Chat Assistant with MongoDB
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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... read more  

Myth Or Reality: Will AI Replace Computer Programmers?
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Evolving our real-time timeseries storage again: Built in Rust for performance at scale

Datadog just dropped its 6th-gen real-time timeseries engine:RTDB. It's built inRust, sharded per core, and backed by LSM trees that don’t blink under pressure. The secret sauce? A custom storage engine calledMonocle—optimized for high-cardinality chaos and bursty workloads. It’s pulling60x faster .. read more  

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.. read more  

Can LLMs replace on call SREs today?
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Best Linux distro for developers of 2025

TechRadar rounds up the best Linux distros for devs.Manjarodelivers Arch power without the pain.DebianandUbuntu LTShold steady for those who put uptime over edge.Fedorakeeps the new stuff flowing. Solusrolls with a tight curation hand—smooth updates, no chaos.Mocaccinoaims at Gentoo lovers who want.. read more  

Best Linux distro for developers of 2025
Pelagia is a Kubernetes controller that provides all-in-one management for Ceph clusters installed by Rook. It delivers two main features:

Aggregates all Rook Custom Resources (CRs) into a single CephDeployment resource, simplifying the management of Ceph clusters.
Provides automated lifecycle management (LCM) of Rook Ceph OSD nodes for bare-metal clusters. Automated LCM is managed by the special CephOsdRemoveTask resource.

It is designed to simplify the management of Ceph clusters in Kubernetes installed by Rook.

Being solid Rook users, we had dozens of Rook CRs to manage. Thus, one day we decided to create a single resource that would aggregate all Rook CRs and deliver a smoother LCM experience. This is how Pelagia was born.

It supports almost all Rook CRs API, including CephCluster, CephBlockPool, CephFilesystem, CephObjectStore, and others, aggregating them into a single specification. We continuously work on improving Pelagia's API, adding new features, and enhancing existing ones.

Pelagia collects Ceph cluster state and all Rook CRs statuses into single CephDeploymentHealth CR. This resource highlights of Ceph cluster and Rook APIs issues, if any.

Another important thing we implemented in Pelagia is the automated lifecycle management of Rook Ceph OSD nodes for bare-metal clusters. This feature is delivered by the CephOsdRemoveTask resource, which automates the process of removing OSD disks and nodes from the cluster. We are using this feature in our everyday day-2 operations routine.