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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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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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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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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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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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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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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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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.. read more  

Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps
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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.. read more  

Migrating Airbnb’s JVM Monorepo to Bazel
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Dynamo, DynamoDB, and Aurora DSQL

Marc Brooker breaks down the jump fromAmazon DynamotoDynamoDBandAurora DSQL, tracing how the guts of cloud databases have changed. It’s a story about dropping old trade-offs and picking up stronger guarantees. DynamoDB ditches the old hash-ring replication for multi-AZ replica sets backed by Paxos... read more  

At its core, Argo CD treats Git as the single source of truth for application definitions. You declare the desired state of your Kubernetes applications in Git (manifests, Helm charts, Kustomize overlays), and Argo CD continuously compares that desired state with what is actually running in the cluster. When drift is detected, it can alert you or automatically reconcile the cluster back to the Git-defined state.

Argo CD runs inside Kubernetes and provides:

- Declarative application management
- Automated or manual sync from Git to cluster
- Continuous drift detection and health assessment
- Rollbacks by reverting Git commits
- Fine-grained RBAC and multi-cluster support

It integrates natively with common Kubernetes configuration formats:

- Plain YAML
- Helm
- Kustomize
- Jsonnet

Operationally, Argo CD exposes both a web UI and CLI, making it easy to visualize application state, deployment history, diffs, and sync status. It is commonly used in platform engineering and SRE teams to standardize deployments, reduce configuration drift, and enforce auditability.

Argo CD is part of the Argo Project, which is hosted by the Cloud Native Computing Foundation (CNCF), and is widely adopted in production Kubernetes environments ranging from startups to large enterprises.