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@anjali shared a link, 6 months, 3 weeks ago
Customer Marketing Manager, Last9

Choosing the Right APM for Go: 11 Tools Worth Your Time

Explore 11 APM tools built for Go—from lightweight open-source options to enterprise-grade platforms that simplify debugging.

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@faun shared a link, 6 months, 4 weeks ago
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Development gets better with Age

A longtime AWS insider, Werner Vogels, breaks down the shift from slow-and-steady software growth to the generative AI rocket ride. Capabilities soared. Guardrails? Not so much. No docs, no handrails - just launch and learn. AWS didn’t chase the hype. It pulled a classic AWS move: doubled down on B2.. read more  

Development gets better with Age
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@faun shared a link, 6 months, 4 weeks ago
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Inside Husky’s query engine: Real-time access to 100 trillion events

SteamPipe just gutted its real-time storage engine and rebuilt it inRust. Expect faster performance and better scaling. Now runs oncolumnar storage, ships withvectorized queries, and rolls anobject store-backed WAL. Serious firepower for time series data. System shift:Another sign that high-throughp.. read more  

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@faun shared a link, 6 months, 4 weeks ago
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walrus: ingesting data at memory speeds

Walrusis a lock-free, single-nodeWrite Ahead Log in Rustthat rips through a million ops/sec and moves 1 GB/s of write bandwidth - on bare-metal, nothing fancy. It leans on mmap-backed sparse files, atomic counters, and zero-copy reads to get there. Each topic gets its own line of 10MB memory-mapped .. read more  

walrus: ingesting data at memory speeds
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@faun shared a link, 6 months, 4 weeks ago
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OpenAI Agent Builder: A Complete Guide to Building AI Workflows Without Code

OpenAI’sAgent Builderdrops the guardrails. It’s a no-code, drag-and-drop playground for building, testing, and shipping AI workflows - logic flows straight from your brain to the screen. Tweak interfaces inWidget Studio. Plug into real systems with theAgents SDK. Just one catch: it’s locked behind P.. read more  

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@faun shared a link, 6 months, 4 weeks ago
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Going down the rabbit hole of Postgres 18 features by Tudor Golubenco

PostgreSQL 18 just hit stable. Big swing! Async IO infrastructureis in. That means lower overhead, tighter storage control, and less CPU getting chewed up by I/O. Adddirect IO, and the database starts flexing beyond traditional bottlenecks. OAuth 2.0? Native now. No hacks needed. UUIDv7? Built-in su.. read more  

Going down the rabbit hole of Postgres 18 features by Tudor Golubenco
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@faun shared a link, 6 months, 4 weeks ago
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I'm Building a Browser for Reverse Engineers

A researcher rolled their ownChromium forkwith a customDevTools Protocol (CDP) domain- not for fun, but to surgically probe browser internals. It reaches into Canvas, WebGL, and other trickier APIs, dodging the usual sandbox and spoofing all the bot blockers they'd rather you leave alone. It injects.. read more  

I'm Building a Browser for Reverse Engineers
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@faun shared a link, 6 months, 4 weeks ago
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Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization

Advanced PostgreSQL tuning gets real results: composite indexes and CTEs can cut query latency hard when slicing huge datasets. AddLATERALjoins and indexed subqueries into the mix, and you’ve got a top-N query pattern that holds up—even when hammering long ID lists... read more  

Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization
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@faun shared a link, 6 months, 4 weeks ago
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Technical Tuesday: 10 best practices for building reliable AI agents in 2025

UiPath just droppedAgent Builder in Studio- a legit development environment for AI agents that can actually handle enterprise chaos. Think production-grade: modular builds, traceable steps, and failure handling that doesn’t flake under pressure. It’s wired forschema-driven prompts,tool versioning, a.. read more  

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@faun shared a link, 6 months, 4 weeks ago
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Write Deep Learning Code Locally and Run on GPUs Instantly

Modal cuts the drama out of deep learning ops. Devs write Python like usual, then fire off training, eval, and serving scripts to serverless GPUs - zero cluster wrangling. It handles data blobs, image builds, and orchestration. You focus on tuning with libraries like Unsloth, or serving via vLLM... read more  

Write Deep Learning Code Locally and Run on GPUs Instantly
GPT-5.3-Codex is OpenAI’s advanced agentic coding model, designed to go beyond writing code and operate as a general-purpose collaborator on a computer. It builds on GPT-5.2-Codex by combining stronger coding performance with improved reasoning and professional knowledge, while running about 25% faster. The model is optimized for long-running tasks that involve research, tool use, and complex execution, and it performs at the top of industry benchmarks such as SWE-Bench Pro and Terminal-Bench.

Unlike earlier Codex models that focused primarily on code generation and review, GPT-5.3-Codex can reason, plan, and act across the full software lifecycle. It supports activities such as debugging, deploying, monitoring, writing product requirement documents, creating tests, and analyzing metrics. It can also autonomously build and iterate on complex applications and better interpret underspecified prompts, producing more complete and production-ready results by default.

A defining feature of GPT-5.3-Codex is its interactive, agentic workflow. Users can steer the model while it is working, receive progress updates, and adjust direction without losing context, making it feel more like a teammate than a batch automation tool. The model was even used internally to help debug its own training and deployment processes. GPT-5.3-Codex is available through paid ChatGPT plans in the Codex app, CLI, IDE extension, and web, with API access planned for the future.