<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Blog — Neon Docs]]></title><description><![CDATA[The latest product updates from Neon]]></description><link>https://neon.com</link><generator>RSS for Node</generator><lastBuildDate>Thu, 07 May 2026 01:06:45 GMT</lastBuildDate><atom:link href="https://neon.com/blog/rss.xml" rel="self" type="application/rss+xml"/><language><![CDATA[en]]></language><item><title><![CDATA[Introducing Organization Spending Limits]]></title><description><![CDATA[<p>Your team ships a new feature, traffic spikes, and autoscaling does its job. Great — until the bill arrives and it&#8217;s three times what anyone expected. By then it&#8217;s too late to do anything about it. Most cloud providers handle this the same way: you find out what you spent after you&#8217;ve already spent it. [&hellip;]</p>
]]></description><link>https://neon.com/blog/introducing-organization-spending-limits</link><guid isPermaLink="true">https://neon.com/blog/introducing-organization-spending-limits</guid><category><![CDATA[Product]]></category><dc:creator><![CDATA[Jeffrey Christoffersen]]></dc:creator><pubDate>Fri, 24 Apr 2026 15:24:44 GMT</pubDate><content:encoded>&lt;p&gt;Your team ships a new feature, traffic spikes, and autoscaling does its job. Great — until the bill arrives and it&amp;#8217;s three times what anyone expected. By then it&amp;#8217;s too late to do anything about it. Most cloud providers handle this the same way: you find out what you spent after you&amp;#8217;ve already spent it. [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Agents grew up, so did our docs]]></title><description><![CDATA[<p>A year ago, if you asked an agent about Neon, you got whatever it half-remembered from training. Now it goes looking and reads what it finds. Our docs were written for humans who scroll, not machines that fetch. We&#8217;ve been fixing this in pieces, not all at once. This post is what worked, what didn&#8217;t, [&hellip;]</p>
]]></description><link>https://neon.com/blog/agents-grew-up-so-did-our-docs</link><guid isPermaLink="true">https://neon.com/blog/agents-grew-up-so-did-our-docs</guid><category><![CDATA[Engineering]]></category><dc:creator><![CDATA[Philip Olson]]></dc:creator><pubDate>Thu, 23 Apr 2026 13:47:50 GMT</pubDate><content:encoded>&lt;p&gt;A year ago, if you asked an agent about Neon, you got whatever it half-remembered from training. Now it goes looking and reads what it finds. Our docs were written for humans who scroll, not machines that fetch. We&amp;#8217;ve been fixing this in pieces, not all at once. This post is what worked, what didn&amp;#8217;t, [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Neon is now available as an OpenAI Codex Plugin]]></title><description><![CDATA[<p>An official Neon plugin is now available in the OpenAI Codex marketplace. It connects Codex directly to your Neon databases through MCP, so you can provision and manage Postgres databases without leaving your workflow. Once installed, Codex can interact with your Neon account, not just read static guidance about it. You can ask it to [&hellip;]</p>
]]></description><link>https://neon.com/blog/neon-codex-plugin</link><guid isPermaLink="true">https://neon.com/blog/neon-codex-plugin</guid><category><![CDATA[AI]]></category><dc:creator><![CDATA[Andy Hattemer]]></dc:creator><pubDate>Thu, 16 Apr 2026 22:06:03 GMT</pubDate><content:encoded>&lt;p&gt;An official Neon plugin is now available in the OpenAI Codex marketplace. It connects Codex directly to your Neon databases through MCP, so you can provision and manage Postgres databases without leaving your workflow. Once installed, Codex can interact with your Neon account, not just read static guidance about it. You can ask it to [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Zero-Downtime Patching Part 1: Prewarming]]></title><description><![CDATA[<p>Ensuring customer databases are always available is one of the most important things we do in Neon and Lakebase. We&#8217;ve designed the system with redundancy at every level, automatically failing over and recovering your database in the event of hardware or software failures. In a large-scale system, such unplanned failures are a statistical expectation, but [&hellip;]</p>
]]></description><link>https://neon.com/blog/prewarming</link><guid isPermaLink="true">https://neon.com/blog/prewarming</guid><category><![CDATA[Engineering]]></category><dc:creator><![CDATA[Hans Norheim]]></dc:creator><pubDate>Fri, 27 Mar 2026 14:04:17 GMT</pubDate><content:encoded>&lt;p&gt;Ensuring customer databases are always available is one of the most important things we do in Neon and Lakebase. We&amp;#8217;ve designed the system with redundancy at every level, automatically failing over and recovering your database in the event of hardware or software failures. In a large-scale system, such unplanned failures are a statistical expectation, but [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Neon works with Stripe Projects for agentic provisioning]]></title><description><![CDATA[<p>For most of 2025, AI coding agents got good at a specific thing: writing code. Give an agent a prompt, and it could scaffold an app, wire up an API, write migrations. But when the code was done, the agent stopped. Spinning up a real database, creating an account, getting credentials into the environment&#8230; that [&hellip;]</p>
]]></description><link>https://neon.com/blog/neon-works-with-stripe-projects-for-agentic-provisioning</link><guid isPermaLink="true">https://neon.com/blog/neon-works-with-stripe-projects-for-agentic-provisioning</guid><category><![CDATA[Product]]></category><dc:creator><![CDATA[Brad Van Vugt]]></dc:creator><pubDate>Thu, 26 Mar 2026 16:14:37 GMT</pubDate><content:encoded>&lt;p&gt;For most of 2025, AI coding agents got good at a specific thing: writing code. Give an agent a prompt, and it could scaffold an app, wire up an API, write migrations. But when the code was done, the agent stopped. Spinning up a real database, creating an account, getting credentials into the environment&amp;#8230; that [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[How Specific Provisions Thousands of Databases for Coding Agents Using Neon]]></title><description><![CDATA[<p>&#8220;I&#8217;m genuinely surprised by how well it handles that scale. You can create tons of databases and they&#8217;re available immediately. You can branch out immediately. All of those things make it really nice for agent-managed infra.&#8221; Iman Radjavi, Co-founder, Specific.dev What Specific builds Specific (YC F25) is a cloud platform designed for coding agents. With [&hellip;]</p>
]]></description><link>https://neon.com/blog/how-specific-provisions-thousands-of-databases-for-coding-agents-using-neon</link><guid isPermaLink="true">https://neon.com/blog/how-specific-provisions-thousands-of-databases-for-coding-agents-using-neon</guid><category><![CDATA[Case Studies]]></category><dc:creator><![CDATA[Andy Hattemer]]></dc:creator><pubDate>Wed, 18 Mar 2026 19:19:23 GMT</pubDate><content:encoded>&lt;p&gt;&amp;#8220;I&amp;#8217;m genuinely surprised by how well it handles that scale. You can create tons of databases and they&amp;#8217;re available immediately. You can branch out immediately. All of those things make it really nice for agent-managed infra.&amp;#8221; Iman Radjavi, Co-founder, Specific.dev What Specific builds Specific (YC F25) is a cloud platform designed for coding agents. With [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Ctrl-C in psql gives me the heebie-jeebies]]></title><description><![CDATA[<p>There are a few different reasons to hit the brakes on a Postgres query. Maybe it’s taking too long to finish. Maybe you realised you forgot to create an index that will make it orders of magnitude quicker. Maybe there’s some reason the results are no longer needed. Or maybe you, or your LLM buddy, [&hellip;]</p>
]]></description><link>https://neon.com/blog/ctrl-c-in-psql-gives-me-the-heebie-jeebies</link><guid isPermaLink="true">https://neon.com/blog/ctrl-c-in-psql-gives-me-the-heebie-jeebies</guid><category><![CDATA[Postgres]]></category><dc:creator><![CDATA[George MacKerron]]></dc:creator><pubDate>Thu, 05 Mar 2026 16:32:34 GMT</pubDate><content:encoded>&lt;p&gt;There are a few different reasons to hit the brakes on a Postgres query. Maybe it’s taking too long to finish. Maybe you realised you forgot to create an index that will make it orders of magnitude quicker. Maybe there’s some reason the results are no longer needed. Or maybe you, or your LLM buddy, [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[15,000+ Apps Built Over WhatsApp: Inside QwikBuild’s Neon-Powered Architecture]]></title><description><![CDATA[<p>“The biggest strength of Neon is how it decouples storage and compute and makes them independently scalable. When an app isn’t being used, the compute node can be put in idle mode at extremely low cost, which lets us handle a wide range of scale and complexity without compromise.” (Nilesh Trivedi, co-founder and CTO at [&hellip;]</p>
]]></description><link>https://neon.com/blog/inside-qwikbuild-neon-powered-architecture</link><guid isPermaLink="true">https://neon.com/blog/inside-qwikbuild-neon-powered-architecture</guid><category><![CDATA[AI]]></category><category><![CDATA[Case Studies]]></category><dc:creator><![CDATA[Carlota Soto]]></dc:creator><pubDate>Thu, 26 Feb 2026 17:49:06 GMT</pubDate><content:encoded>&lt;p&gt;“The biggest strength of Neon is how it decouples storage and compute and makes them independently scalable. When an app isn’t being used, the compute node can be put in idle mode at extremely low cost, which lets us handle a wide range of scale and complexity without compromise.” (Nilesh Trivedi, co-founder and CTO at [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Where Agents Meet Infrastructure: Encore, Leap, and Neon]]></title><description><![CDATA[<p>From the start, the team at Encore has been focused on solving a simple problem: shipping production infrastructure shouldn’t require a dedicated platform engineering team. They set out to make deploying real applications feel simple without abstracting away control; in Encore, devs can define infrastructure directly in Go or TypeScript, and the platform turns that [&hellip;]</p>
]]></description><link>https://neon.com/blog/where-agents-meet-infrastructure-encore-leap-and-neon</link><guid isPermaLink="true">https://neon.com/blog/where-agents-meet-infrastructure-encore-leap-and-neon</guid><category><![CDATA[AI]]></category><category><![CDATA[Case Studies]]></category><dc:creator><![CDATA[Carlota Soto]]></dc:creator><pubDate>Wed, 25 Feb 2026 19:45:21 GMT</pubDate><content:encoded>&lt;p&gt;From the start, the team at Encore has been focused on solving a simple problem: shipping production infrastructure shouldn’t require a dedicated platform engineering team. They set out to make deploying real applications feel simple without abstracting away control; in Encore, devs can define infrastructure directly in Go or TypeScript, and the platform turns that [&amp;hellip;]&lt;/p&gt;
</content:encoded></item><item><title><![CDATA[Building a Deep Research Agent with Neon and Durable Endpoints]]></title><description><![CDATA[<p>Every AI lab is shipping research agents. OpenAI&#8217;s Deep Research, Perplexity, and Gemini&#8217;s research mode. These products are not simple RAG pipelines. Recent papers like DeepResearcher and Step-DeepResearch formalize what makes them work: a recursive loop of planning, searching, learning, and reflecting, where the agent decides when to go deeper and when to stop. The [&hellip;]</p>
]]></description><link>https://neon.com/blog/building-a-deep-research-agent-with-neon-and-durable-endpoints</link><guid isPermaLink="true">https://neon.com/blog/building-a-deep-research-agent-with-neon-and-durable-endpoints</guid><category><![CDATA[Community]]></category><category><![CDATA[AI]]></category><dc:creator><![CDATA[Charly Poly]]></dc:creator><pubDate>Tue, 24 Feb 2026 17:14:34 GMT</pubDate><content:encoded>&lt;p&gt;Every AI lab is shipping research agents. OpenAI&amp;#8217;s Deep Research, Perplexity, and Gemini&amp;#8217;s research mode. These products are not simple RAG pipelines. Recent papers like DeepResearcher and Step-DeepResearch formalize what makes them work: a recursive loop of planning, searching, learning, and reflecting, where the agent decides when to go deeper and when to stop. The [&amp;hellip;]&lt;/p&gt;
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