Off-by-none Serverless Newsletter

Issue #362: Mo’ Models, Mo’ Problems ⚠️

2026-04-21T12:00:00Z

Mo’ Models, Mo’ Problems ⚠️

In our previous issue, AI started breaking things faster than we can defend them, AWS launched an agent registry, and S3 kinda became a filesystem. This week, Claude gets a major upgrade, AWS makes AI costs more visible, and Cloudflare goes all-in on agents. Plus, we've got some amazing cloud, serverless, and AI content from the community.

News & Announcements

Anthropic announced Claude Opus 4.7 this past week as their latest push towards world domination. Early signals point to serious gains in software engineering, especially for long-running tasks, plus stronger vision support. AWS wasted no time rolling it out in Bedrock.

AWS also introduced granular cost attribution for Amazon Bedrock, which is a big step toward actually understanding AI spend. Cost control and observability for LLMs is still pretty messy, and being able to map usage down to IAM users and roles starts to make that problem a lot more tractable.

Amazon Aurora Serverless is getting up to 30% better performance with smarter scaling, while still keeping the scale-to-zero promise. There’s a deeper dive from the team here if you want the details. I like this direction.

AWS also announced general availability of AWS Interconnect, kicking things off with Google Cloud. Dedicated bandwidth between clouds is becoming a thing, with Azure and Oracle Cloud Infrastructure expected to follow later this year. Let the homogeneity begin.

Anthropic introduced routines in Claude Code, which basically turns repeatable development workflows into something you can automate. Feels like another positive step toward making agents more useful in day-to-day dev work. They also highlighted what people are building in their ecosystem with their latest hackathon winners. No fluff, they're all practical AI solutions that address real pain points. 🤷

It was Agents Week over at Cloudflare last week, and they shipped a lot. The full rundown of launches is here, but there were a few standouts: AI Search as a core primitive for agents, Flagship to bring feature flags into the agent era, Agent Memory, and a new email service for agents in public beta.

Not on my 2026 Bingo card, but Apple announced that Tim Cook is stepping into the Executive Chairman role at Apple, with John Ternus taking over as CEO. Big shift for one of the most stable leadership runs in tech. I'm sure it has nothing to do with Apple Intelligence. 😬

And in case you missed it, the recent Vercel hack highlights a growing pattern in cybersecurity. Third-party AI tooling accessing internal systems is introducing a whole new threat model. One that most teams aren’t even aware of, never mind prepared for.

If your incident response still involves five tabs, three tools, and someone asking “who’s on point?”, it might be time to rethink things. incident.io is an all-in-one platform that runs Slack and Teams native, so you can declare, manage, and resolve incidents without leaving the conversation. It handles the busywork too, auto-assigning roles, kicking off workflows, and even surfacing insights from past incidents so you don’t keep fixing the same problem twice. Definitely worth a deeper look if you want faster response times without adding more process: incident.io. Sponsored

Tutorials

Lambda Managed Instances: A Working Demo and the Math Behind It by Eric Johnson
Transform retail with AWS generative AI services by Bhavya Chugh
The Hidden Cost of AWS Lambda SnapStart for Python, and How I Fixed It with Durable Functions by Jaya Ganesh
Best practices for using Claude Opus 4.7 with Claude Code
Power video semantic search with Amazon Nova Multimodal Embeddings by Amit Kalawat
Serverless applications on AWS with Lambda using Java 25, API Gateway and DynamoDB - Part 6 Using GraalVM Native Image by Vadym Kazulkin
Accelerate database migration to Amazon Aurora DSQL with Kiro and Amazon Bedrock AgentCore by Noorul Mahajabeen Mustafa
Using AWS Lambda Extensions to Run Post-Response Telemetry Flush by Melvin Philips
Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 5 SnapStart + full priming by Vadym Kazulkin

Reads

Navigating the generative AI journey: The Path-to-Value framework from AWS
AWS tries to put some structure around the chaos with a “Path-to-Value” framework. It’s less of a step-by-step guide and more of a reminder that AI adoption is messy, multidimensional, and mostly about tradeoffs between value, risk, and organizational reality.

Moving past bots vs. humans
The bot vs human model is breaking down fast. Cloudflare is leaning into intent over identity, which feels like the right direction as agents start acting more like users and users start looking more like bots.

The AI engineering stack we built internally — on the platform we ship
Always interesting when a company dogfoods its own stack at scale. Cloudflare’s setup is a good look at what a modern AI platform actually needs when you’re pushing billions of tokens and not just running demos.

Multi-Agent AI in Production | Taskade Engineering (2026)
Three years into multi-agent systems and the same problems keep showing up. Memory, coordination, and agents getting stuck in loops. Good practical patterns here, especially if you’ve already hit these walls.

Why AWS Certified GenAI Developer stands apart from other AWS certs
Anwaar Hussain points out that this cert is less about knowing AI and more about wiring it into real systems. Which is probably the right shift, because building with AI is quickly becoming more of an architecture problem than a modeling one.

Lessons I learned building a memory-aware agent with Amazon Bedrock AgentCore Runtime
Memory is still the hardest part of agent design. Amit Kayal gives us a solid walkthrough of scoping, lifecycle, and not blowing up your prompts while trying to make agents feel stateful.

Learnings from conducting ~1,000 interviews at Amazon
Steve Huynh shares a good reminder that hiring is its own system with its own signals. If you don’t understand what a company actually optimizes for, you’re probably optimizing for the wrong thing.

Podcasts, Videos, and more

Serverless Apache Airflow | Serverless Office Hours
Airflow, but make it serverless. John Jackson and Kamen Sharlandjiev breakdown when MWAA actually makes sense versus just reaching for Step Functions, especially once you factor in cost, scaling, and how much orchestration complexity you really need.

Building, Managing & Governing APIs on AWS
APIs aren’t just for humans anymore. Giedrius Praspaliauskas covers the full lifecycle on AWS, but the interesting part is how API strategies are evolving to support agents, not just apps. Same primitives, very different consumers.

New from AWS

Developer Tools

brognilucas/sls-testing by Lucas Brogni
Typed, composable testing utilities for AWS Lambda from Lucas Brogni that provides event builders and Jest matchers for Lambda functions.

pujaaan/simple-cdk by pujaaan
A thin runtime over CDK that scans your folders, runs adapters in a deterministic three-phase pipeline (discover → register → wire), and emits real CDK constructs.

ToolSimulator: scalable tool testing for AI agents by Darren Wang
An LLM-powered tool simulation framework within Strands Evals to thoroughly and safely test AI agents that rely on external tools, at scale.

Final Thoughts 🤔

It’s getting a lot easier to build powerful systems.

Models are getting better at real work. Agents are starting to handle meaningful workflows. And the infrastructure around all of this is finally catching up, from cost visibility to orchestration to deployment patterns.

But the gaps are still there.

We’re wiring these capabilities into systems that were never designed for autonomous behavior. Giving tools access to internal systems. Letting agents make decisions across boundaries that used to be tightly controlled. And in some cases, we’re doing it faster than we understand the implications.

That’s where things start to break.

The Vercel incident isn’t an outlier. It’s a preview. A glimpse into what happens when powerful models meet loosely defined boundaries and third-party integrations. The tooling is evolving quickly, but the assumptions behind our systems haven’t fully caught up yet.

At the same time, you can see the industry starting to respond.

Better cost attribution. More structured agent workflows. Dedicated primitives for memory, search, and control. Even multicloud connectivity is starting to blur the lines between platforms. It’s not just about building faster anymore, it’s about building systems that can actually support what we’re asking them to do.

Still early. Still messy. But the pattern is emerging. More power, more abstraction, and more responsibility to get the boundaries right.

Because “Mo’ Models, Mo’ Problems” isn’t really a joke. It’s just the beginning.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #361: S3 is Still Not A File System 🤷

2026-04-14T12:00:00Z

S3 is Still Not A File System 🤷

In our previous issue, Claude leaked its secrets, AWS locked down S3, and Cloudflare made a run at WordPress. This week, AI starts breaking things faster than we can defend them, AWS launches an agent registry, and S3 becomes a filesystem (sort of). Plus, we've got plenty of awesome content from the cloud, serverless, and AI communities.

News & Announcements

Anthropic just dropped Claude Mythos Preview, a gated research release (available on Amazon Bedrock) that’s already raising eyebrows. Early reports suggest it’s extremely good at finding vulnerabilities in long-standing systems, which is both impressive and a little terrifying. They’re rolling it out slowly so people can prepare their security programs for AI-accelerated offense. The reality is AI is getting very, very good at breaking things, and we’re going to need to rethink how we defend systems that were never designed for this level of pressure.

AWS made a bunch of moves in Bedrock this week. They added cost allocation by IAM user and role, which is a big win for visibility into AI spend. They also introduced stateful MCP client capabilities in AgentCore Runtime and added OS-level actions to the AgentCore Browser. Good stuff.

AWS also launched the Agent Registry in preview. Centralized discovery and governance is going to be critical as agent sprawl becomes a thing (think shadow APIs on steroids). There’s a deeper dive on the vision in this post on managing agents at scale.

Big S3 news this week with the launch of S3 Files, which essentially puts a filesystem interface in front of your buckets. If you want more detail, the full breakdown is in this launch post. Still not a filesystem… but closer than ever before.

AWS Lambda response streaming is now available in all commercial regions, which is great to see. This feature has unlocked much better UX for real-time apps. I'm glad there's no longer a regional bottleneck.

If you still love PHP, you can now plug into Aurora DSQL with the new PHP connector. Not flashy, but extremely useful.

Anthropic also introduced Claude Managed Agents, which is basically a faster path to getting agents into production without wiring everything up yourself. Less plumbing, more doing.

Cloudflare announced Sandboxes GA. Giving agents their own isolated environments feels like table stakes at this point.

And finally, Vercel might be getting ready for Wall Street. Their CEO is signaling IPO readiness as AI agents drive growth. You can read more about it here.

Tutorials

Embed a live AI browser agent in your React app with Amazon Bedrock AgentCore by Sundar Raghavan
Manage AI costs with Amazon Bedrock Projects by Ba'Carri Johnson
Seeing like an agent: how we design tools in Claude Code by Thariq Shihipar
Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 4 SnapStart + DSQL request priming by Vadym Kazulkin
Building intelligent audio search with Amazon Nova Embeddings: A deep dive into semantic audio understanding by Madhavi Evana
Lambda Just Got a File System. I Put AI Agents on It. by Eric Johnson
Serverless applications on AWS with Lambda using Java 25, API Gateway and DynamoDB - Part 5 SnapStart + full priming by Vadym Kazulkin

Reads

How I Use OpenClaw as My AI-Powered Personal Operating System
Running an “AI OS” stops sounding crazy once you see it working. I like Martin Mueller's isolation model here. The Agent Hub project I've been working on takes a similar approach, running agents in Docker sandboxes (lightweight VMs built for exactly this use case).

Scaling MCP adoption: Our reference architecture for simpler, safer and cheaper enterprise deployments of MCP
Cloudflare lays out a very real architecture for scaling MCP across an enterprise. This is exactly the kind of thing you have to think about. Context, auth, routing, and security all become first-class concerns once your agents start doing real work.

Multi-agent coordination patterns: Five approaches and when to use them
I’m a huge fan of patterns, and seeing these emerge in the agent ecosystem is exciting. We’re finally getting reusable, battle-tested approaches that unlock real capabilities instead of everyone rebuilding one-off hacks.

I Tested Three Spec-Driven AI Tools. Here’s My Honest Take.
I’m still not sold on spec-driven being the end state. It feels a bit too waterfall for how fast things move. That said, it’s a solid pattern for documentation and grounding the model upfront.

S3 Is Not a Filesystem (But Now There's One In Front of It)
Corey Quinn still says S3 isn't a filesystem, but he believes layering a real one in front of it actually makes sense. He also says the pricing is pretty reasonable for what you get, which means a lot coming from him.

The advisor strategy: Give Sonnet an intelligence boost with Opus
This is a really smart cost pattern. Let the expensive model do the hard thinking once, then have the cheaper models following instructions, which they're surprisingly good at.

Podcasts, Videos, and more

AWS Distinguished Eng: Learning From 3000 Incidents And How Engineering Is Changing | Marc Brooker
Marc Brooker shares some really interesting insights here on finding impactful engineering problems and system design patterns that actually hold up under real-world pressure. His advice for both junior and senior engineers navigating the AI shift is worth your time for a listen.

New from AWS

Final Thoughts 🤔

It’s getting a lot easier to break things.

Between models that can uncover vulnerabilities faster than ever, agents operating with increasing autonomy, and systems that were never designed for this kind of pressure, the attack surface is expanding in real time. The tools are getting smarter, but so are the ways they can be used against us.

And we’re still figuring out how to keep up with it.

But there are signs the industry is adjusting.

We’re seeing better visibility into AI spend, more structured ways to manage and govern agents, and even isolated environments becoming the default for running them. There’s a growing recognition that if agents are going to act on our behalf, we need systems that can track them, constrain them, and clean up after them when things go sideways.

Even S3 Files is part of that story. Not because it changes what S3 is, but because it makes powerful primitives easier to use, observe, and secure correctly.

It’s not clean yet, and it’s definitely not solved.

But the direction is clear. Smarter systems, stronger boundaries, and a shift toward building with the assumption that things will break.

Because they most definitely will.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #360: Anthropic’s Wardrobe Malfunction 🫣

2026-04-07T12:00:00Z

Anthropic’s Wardrobe Malfunction 🫣

In our previous issue, App Runner got sent to maintenance mode, agents started looking like real software, and efficiency may have become the new AI race. This week, Claude leaks its secrets, AWS locks down S3, and Cloudflare makes a run at WordPress. Plus, we've got a whole bunch of amazing content from the cloud, serverless, and AI communities.

News & Announcements

Anthropic is having a month. Their very public Claude Code leak gave us an unexpected peek under the hood. Lots to learn from it, including their concept of “skeptical memory” and how it maps to patterns emerging in agent design. Not exactly how you want transparency to happen, but still… fascinating.

AWS is continuing to tighten the screws on security with S3 rolling out new default bucket protections they announced last year. I'm sure this will break someone's CI/CD pipeline, but if this prevents another “oops, we exposed millions of records to the internet” incident, it’s worth it.

On the AI safety front, Amazon Bedrock Guardrails now support cross-account safeguards (GA), which is a big step toward centralized governance of AI systems. The deeper dive on how cross-account guardrails work is worth a read. This is the kind of thing enterprises actually need: consistent policies, enforced everywhere, without duct-taping controls into every individual service.

AWS also introduced frontier agents for security testing and cloud operations, which is both exciting and mildly terrifying. Letting agents poke at your infrastructure to find weaknesses sounds great… assuming they don’t introduce a few outages along the way. 😬 Given AWS’s recent adventures with agentic coding tools taking down services, let's hope they spent a few extra human cycles on this one.

Observability keeps evolving too. CloudWatch adding OpenTelemetry metrics support is actually a big deal. Standardizing metrics across systems has been messy for years, and leaning into OpenTelemetry makes it a lot easier to build portable, vendor-agnostic observability pipelines.

And speaking of observability, OpenSearch introduced agentic AI for log analytics, another signal that logs are no longer just something you query, they’re something you collaborate with. Expect more systems where you ask questions and let agents do the digging.

On the security side, this one’s a bit of a nightmare: a trojan slipped into axios via an npm supply chain attack. Axios is everywhere, which makes this especially concerning. Friendly reminder to pin your dependencies, use proper scanning tools, and maybe don’t blindly trust package libraries.

Cloudflare introduced EmDash, as a spiritual successor to WordPress. It’s positioning itself as a more secure, modern alternative to the plugin-heavy ecosystem we’ve all wrestled with. WordPress killer? Maybe. Or at least another sign that the PHP-era assumptions about how we build content systems are starting to fade.

And finally, Luc van Donkersgoed announced semantic content search for AWS News. Good stuff.

Tutorials

Amazon Aurora DSQL: A Guide to AWS's Distributed SQL DB by Darryl Ruggles
Building real-time conversational podcasts with Amazon Nova 2 Sonic by Madhavi Evana
Serverless applications on AWS with Lambda using Java 25, API Gateway and DynamoDB - Part 4 SnapStart + DynamoDB request priming by Vadym Kazulkin
Stream live data from Amazon Keyspaces to S3 vector for real time AI applications by Siva Palli
Working with identity columns and sequences in Aurora DSQL by Arnab Chowdhury
Single-Cluster Duality View by Franck Pachot
Add Chat AI Summary Using Amazon Bedrock and HTTP Response Streaming by Marko Djakovic
Simulate realistic users to evaluate multi-turn AI agents in Strands Evals by Ishan Singh
Control which domains your AI agents can access by Evandro Franco
Build a FinOps agent using Amazon Bedrock AgentCore by Salman Ahmed
Build reliable AI agents with Amazon Bedrock AgentCore Evaluations by Akarsha Sehwag
Stop Losing Your Screenshots: Build a Personal LINE Summarization and Search Bot with AWS and Claude by Hiro O.

Reads

How I Use AI Every Day Without Losing My Mind
Marco Troisi shares three principles for using AI coding tools without experiencing developer burnout: stay actively engaged in the code, maintain focus on customer needs, and reject multitasking for focused single-task work. His approach rightly emphasizes treating AI as a collaborator rather than letting it automate everything.

Build Smarter AI Apps with Claude | 3 Key Patterns
Love this take on agent harness design from Anthropic. Their point about assumptions growing stale as Claude improves is spot on. I've definitely found myself over-engineering orchestration layers for things Claude can now handle directly, and it's a good reminder to periodically question what actually needs to live in the harness.

AI Made Everyone a Builder and That's a Problem
Ran Isenberg shares his thoughts on the unintended consequences of AI-powered development. The point about AI making it easy to ship demos but hard to maintain production systems is something I see all the time. And I've definitely seen the explosion of half-baked open source projects inadvertently name-squatting. 🤨

Proudly Found Elsewhere
Great post by Seth Orell on embracing managed services over building everything yourself. I completely agree with his litmus test: only build what's a distinguishing, separately marketable feature of your business, otherwise find a provider. This is exactly the kind of thinking that makes serverless architectures so compelling (even if we're still figuring out where the boundaries are).

How I Built an AI Film Crew on AWS
Linda Mohamed, one of my favorite AWS Heroes, built an AI-powered video editing system using Step Functions to orchestrate MediaConvert, Rekognition, Transcribe, and Bedrock agents. This post is loaded with deep technical expertise and demonstrates a production-grade implementation, not just concepts.

Podcasts, Videos, and more

AWS Lambda Performance Tuning | Serverless Office Hours
Julian Wood hosts Matt Diamond and Paras Jain for a deep dive into Lambda performance optimization. The session covers configuration tuning, memory settings, and initialization best practices with practical examples for improving function speed and efficiency.

Building Real-Time Applications at Scale | Serverless Office Hours
Brian Zambrano and Kim Wendt join Eric Johnson to show essential strategies for managing high-volume connection requests, implementing effective filtering patterns, and handling event distribution at scale.

Stop Your Bad Lambda Deployments Before They Hit Production
Excellent hands-on walkthrough by James Eastham showing how to implement automated rollbacks with Lambda aliases and versions. The practical CodeDeploy setup he demonstrates is exactly the kind of safety net your serverless applications need.

An AI state of the union: We’ve passed the inflection point, dark factories are coming, and automation timelines | Simon Willison
Lenny Rachitsky chats with Simon Willison about the practical patterns for what he calls "agentic engineering" and explains why mid-career engineers might face more risk than juniors or seniors. The conversation covers everything from security challenges with prompt injection to how pelicans on bicycles became an unofficial AI quality benchmark. I also agree that deciding what to build is the new bottleneck.

New from AWS

Developer Tools

yetanotheraryan/coldstart by Aryan Tiwari
coldstart is a zero-dependency startup profiler for Node.js that instruments CommonJS and ESM startup loading, reconstructs the dependency tree, and points at the modules that actually slow boot time down.

AutoAgent: first open source library for self-optimizing agents by Kevin Gu
AutoAgent is an open source library where a meta-agent autonomously optimizes a task agent by tweaking prompts, adding tools, and refining orchestration. Kevin Gu reports it achieved top leaderboard scores on spreadsheet and terminal benchmarks after 24+ hours of iterative self-improvement.

Introducing Dynoxide: a fast, embeddable DynamoDB engine by Martin Hicks
Dynoxide is a new DynamoDB-compatible engine written in Rust and backed by SQLite, designed as a fast, embeddable alternative to DynamoDB Local.

Final Thoughts 🤔

It’s been a rough few weeks for “secure by default.”

Between accidental leaks, supply chain attacks, and the constant stream of “oops” moments, it’s clear that the pace of building is still outpacing the guardrails meant to keep things in check. Even the companies building the tools are learning these lessons in real time.

But there’s a flip side to all of this.

You can see the industry responding. S3 locking things down by default. Centralized guardrails for AI systems. Better observability standards. Even agents being tasked with finding vulnerabilities before humans do. It’s messy, but it’s progress.

We’re not slowing down, so the only real option is to get better at building systems that can keep up with us.

And maybe that’s where things are heading. Not just faster development, but safer defaults, stronger guardrails, and tooling that assumes mistakes will happen and is ready for them when they do.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #359: So Long App Runner 🪦

2026-03-31T12:00:00Z

So Long App Runner 🪦

In our previous issue, AWS gave agents real-time streaming and shell access, MCP was thought to be dead, and the distance between idea and deployment continued to shrink while quality became optional. This week, App Runner heads to maintenance mode, agents start looking like real software, and efficiency might become the new AI race. Plus, there's lots of awesome cloud, serverless, and AI content from the community.

News & Announcements

AWS finally did it. 😢 App Runner is heading into maintenance mode on April 30, 2026. It had its problems, but the free load balancer was hard to beat. Now it looks like the future belongs to Amazon ECS Express Mode (which requires a separate load balancer). If you’ve been using it as a trusted platform layer, and chances are you weren't, now might be a good time to reassess.

Despite the latest deprecations, AWS continues to compress the distance between idea and execution. You can now spin up and connect to an Amazon Aurora PostgreSQL database in seconds, which feels less like infrastructure provisioning and more like an on-demand service. Combine that with Lambda Managed Instances scaling up to 32 GB of memory and 16 vCPUs plus a new file descriptor limit of 4,096, and LMIs start looking like more than just a graduation path.

Step Functions also picked up 28 new service integrations, including Amazon Bedrock AgentCore, a clear signal that agent orchestration is becoming a first-class citizen. That pairs nicely with AgentCore’s other evolutions: managed session storage for persistent agent filesystem state and general availability of AgentCore Evaluations. Agents aren’t just stateless prompt loops anymore. They’re getting memory, persistence, and scoring systems that start to look like actual software systems.

On the model side, Palmyra Vision 7B is now available on Amazon Bedrock, adding more multimodal options to the growing Bedrock ecosystem. And if you’re building voice interfaces (like I am right now), Amazon Polly’s new bidirectional streaming brings real-time conversational synthesis into the mix. Adding voice interactions will change your life.

Outside of AWS, efficiency is the new AI battleground. Google’s TurboQuant research pushes model compression to extremes, hinting that smaller, cheaper models running locally might end up being more important than the cloud-based ones. Meanwhile, developer workflows keep shifting as tools like Auto mode for Claude Code lean further into autonomous execution, and enterprises get more guardrails with the Claude Compliance API. These seem like small steps, but they are filling lots of gaps.

And I can't believe I missed this a few weeks ago! Dash0 is acquiring Lumigo, making a bet that “agentic observability” is going to be its own category. You can’t run fleets of semi-autonomous systems without knowing what they’re doing, and traditional logs and traces aren’t going to cut it.

In case you missed it, and given the download numbers, you probably did, Sora is shutting down. It's a good reminder that as fake and curated as social media may be, there is a limit to the amount of AI slop users are willing to take.

Finally, a bit of the end of an era as the FullStack Bulletin bids farewell. Newsletters come and go, but the good ones reshape how we think about this space.

Tutorials

Upgrading AWS CLI From v1 to v2 Using the Migration Tool by Ahmed Moustafa
Building age-responsive, context-aware AI with Amazon Bedrock Guardrails by Pradip Kumar Pandey
Accelerating custom entity recognition with Claude tool use in Amazon Bedrock by Kimo El Mehri
AWS Lambda Now Knows Where It Lives: Explore New AZ Metadata by Darryl Ruggles
Serverless applications on AWS with Lambda using Java 25, API Gateway and DynamoDB - Part 3 Introducing Lambda SnapStart by Vadym Kazulkin
Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 3 Introducing Lambda SnapStart by Vadym Kazulkin
The 15-Millisecond AI: Building "Pre-Cognitive" Edge Caching on AWS by Dhananjay Lakkawar
Real-Time Streaming from Claude Code on AgentCore to the Browser Using AppSync Event API by Kota
Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 2 Initial performance measurements by Vadym Kazulkin
Multi-Agent Systems on AWS Lambda with Durable Functions by Gunnar Grosch
Prevent Sensitive Data Leaks in Amazon CloudWatch Logs by Yaron Ben Ezra

Reads

Architecting for agentic AI development on AWS
Alan Oberto Jimenez covers architectural patterns for AI agents in development workflows. They walk through system architecture approaches (local emulation, hybrid testing, preview environments) and codebase patterns (domain-driven design, layered testing) that enable agents to autonomously write, test, and deploy code with rapid validation cycles.

Agents don't know what good looks like. And that's exactly the problem.
Luca Mezzalira reflects on a recent Neal Ford and Sam Newman fireside chat about AI agents. This is an extremely well-written and enlightening post that deserves your attention.

Your AI agents are a security nightmare
Great post by Allen Helton on treating AI agents as first-class principals with proper identity management. His approach using Teleport for session-bound AWS credentials makes a lot of sense, especially the parallel he draws to how we botched security with early Lambda deployments.

The Heirloom Syntax: Why AI Monocultures Threaten the Future of Innovation
Great post from Brian Tarbox on preserving "systemic diversity" in an age of AI commoditization. I totally agree that our value as technologists isn't in content volume anymore (machines won that game), but in maintaining the unique voice and insights that come from actual experience in the trenches.

How we use Abstract Syntax Trees (ASTs) to turn Workflows code into visual diagrams
André Venceslau explains how Cloudflare built a diagram system that parses workflow code using ASTs. Great deep dive if you want to understand the technical challenge of statically analyzing minified JavaScript to track Promise relationships and parallel execution, then rendering those into visual diagrams that show execution order and branching. Cool stuff.

Why I Collapsed 50+ AWS Lambdas Into a Single API
Harshit walks through consolidating 50+ Lambda functions into a single API to address cold start multiplication and VPC ENI exhaustion. I've built A LOT of serverless APIs over the years, and I'm a big proponent of this approach. There are still good reasons for single-purpose functions, but a Lambdalith using Hono for internal routing is extremely easy to reason about.

AI is creating the first generation of cognitively outsourced humans
The cognitive offloading problem we're facing with generative AI is definitely real. Confusing fluent AI output with actual understanding is where most people get fooled (and even worse if they believe its sycophancy), and I totally agree that we need to treat AI as a tool to sharpen judgment, not to replace it.

Podcasts, Videos, and more

AWS MCP server | Serverless Office Hours
Praneeta Prakash and Claudiu Popa join Julian Wood to explore the AWS MCP Server. It combines natural language interfaces with AWS best practices through Agent SOPs. You'll see practical examples of provisioning infrastructure, troubleshooting, and building Lambda durable functions while maintaining IAM controls throughout.

New from AWS

Developer Tools

gunnargrosch/durable-viz
Durable-viz parses AWS Lambda Durable Functions code to generate Mermaid flowcharts without requiring deployment. The tool supports TypeScript, JavaScript, Python, and Java, detecting all SDK primitives like step, invoke, parallel, map, and wait. It's available as an NPM package or VS Code extension with features like click-to-navigate and PNG export.

How I Search 10,000+ AWS GitHub Repos in 10 Seconds by Ajit
Ajit built a search engine that indexes over 10,000 AWS GitHub repositories using hybrid search (BM25 for exact matches, FAISS for semantic understanding). The system auto-indexes twice daily via EventBridge and uses Bedrock to classify repos across 22 metadata dimensions.

Introducing Loom, an agent platform by Heeki Park
Heeki Park's Loom is an opinionated agent platform built on AWS that integrates Strands Agents SDK, Bedrock, and AgentCore with enterprise guardrails. The platform uses configuration-driven agent creation with mandatory tagging and RBAC/ABAC controls, avoiding runtime code generation for security.

Final Thoughts 🤔

It feels like infrastructure is starting to shift in a more fundamental way. Not just bolting AI onto existing systems, but weaving it into everything: orchestration, storage, compute, observability. Agents with memory, evaluation loops, persistent state. Voice interfaces that feel real-time. Even the way we think about databases and execution environments is starting to change.

But we might be getting ahead of ourselves.

Luca’s point that agents don’t actually know what “good” looks like, and Brian’s argument for preserving systemic diversity instead of letting AI push everything toward a monoculture, are worth paying attention to. If every system is built the same way, trained on the same data, and optimized for the same outputs, we’re not really innovating, we’re just converging.

The stack is evolving fast. The question is whether we’re shaping it, or just letting it shape us.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #358: The Cost of Going Faster 🚄

2026-03-24T12:00:00Z

The Cost of Going Faster 🚄

In our previous issue, S3 turned 20, AWS made agents more stateful and observable, and Claude expanded to a 1M token context window. This week, AWS gives agents real-time streaming and shell access, MCP might be dead, and the distance between idea and deployment shrinks while quality becomes optional. Plus, we've got lots of cloud, serverless, and AI content from the community.

News & Announcements

Amazon Bedrock AgentCore got an upgrade to make agents feel less like request/response loops and more like real systems. The runtime now supports WebRTC for real-time bidirectional streaming, which opens the door for low-latency, continuous interactions instead of polling APIs like it’s 2015. They also added shell command execution, which is both incredibly powerful and a little terrifying. Letting agents execute commands directly is how you get real work done… and also how you accidentally run a destructive Terraform command. 😬

On the MCP side, the AWS MCP Server (Preview) got enhanced monitoring and semantic search capabilities. Observability and retrieval are quickly becoming first-class concerns for agent systems, and this is AWS acknowledging that you can’t operate these things without both.

A smaller but interesting update: AWS Lambda now supports Availability Zone metadata. It’s one of those features you don’t think about until you need it, especially for latency-sensitive or fault-aware workloads. Then suddenly it matters a lot.

AWS also introduced the Nova Forge SDK, a new way to customize Nova models for enterprise use. This feels like AWS continuing to push into the “bring your own intelligence, but we’ll help you shape it” layer. At the same time, they announced a $12.5M investment to defend the open source ecosystem from AI threats. As AI starts to consume and replicate open source faster than it can be sustained, this is a problem that’s only going to get more attention.

Over at Anthropic, Claude keeps creeping closer to being an actual operating system for work. Computer use and dispatch means Claude can now take actions directly on your machine. It's in preview and they admit it'll get things wrong, but they're definitely keeping other labs on their toes.

Speaking of OpenAI, they announced plans to acquire Astral, continuing the trend of model companies pulling more of the stack in-house. Meanwhile, Netlify (remember Jamstack?) is leaning into the opposite side of that trend, launching a new way to turn prompts into production-ready web projects. The gap between “idea” and “deployed app” keeps shrinking, but I fear the gap between “high quality” and “slop” is getting even bigger.

Cloudflare also dropped a big one with dynamic workers for sandboxing AI agents up to 100x faster. Safe execution environments are becoming table stakes for agent systems, and doing that faster at the edge is exactly where this needs to go.

And finally, AWS announced its first 2026 Heroes cohort. Always great to see the community getting recognized. There are some smart, well-deserved folks on that list.

It’s been well over a decade since the first serverless functions, yet delivering near-native performance without cold starts or platform sprawl is still harder than it should be. Serverless on Akamai combines Akamai Functions and EdgeWorkers with a WebAssembly-based runtime that launches in microseconds and scales instantly across a distributed cloud-to-edge platform, letting you build APIs, microservices, and event-driven workflows that support AI inference and modern workloads. If you’re exploring architectures that keep latency low while reserving centralized compute for heavier processing, this is a platform worth checking out. Sponsored

Tutorials

Integrating Amazon Bedrock AgentCore with Slack by Salman Ahmed
Use RAG for video generation using Amazon Bedrock and Amazon Nova Reel by Nick Biso
Overcoming LLM hallucinations in regulated industries: Artificial Genius’s deterministic models on Amazon Nova by Paul Burchard and Igor Halperin
Build an AI-Powered A/B testing engine using Amazon Bedrock by Vijit Vashishtha
Evaluating AI agents for production: A practical guide to Strands Evals by Ishan Singh
Serverless applications on AWS using Lambda with Java 25, API Gateway and DynamoDB - Part 2 Initial performance measurements by Vadym Kazulkin
Deploying an Image Recognition Service to AWS Lambda by Isaac FEI
A Simple Like System for a Static Blog by Isaac FEI
Extract data from Amazon Aurora MySQL to Amazon S3 Tables in Apache Iceberg format by Kunal Ghosh, Arghya Banerjee, Indranil Banerjee, and Vipan Kumar
Anatomy of the .claude/ folder - A complete guide to CLAUDE.md, custom commands, skills, agents, and permissions, and how to set them up properly by Akshay Pachaar
Handlebars with AWS Lambda Layers by Pathum Jayaweera
AWS Lambda Durable Functions: Building Long-Running Workflows in Code by Gunnar Grosch

Reads

Production Is Where the Rigor Goes
I totally agree with Charity's take on why engineers should engage with production beyond just bugs and incidents. We should be constantly checking production to understand how our systems actually behave, not waiting for something to break. Observability isn't a nice-to-have, it's how we understand what we've built.

Strands vs. Claude Agent SDK: Two Very Different Bets on What “Agent” Means
Luca Bianchi's technical comparison of AWS Strands Agents and Claude Agent SDK covers the key architectural differences: Strands as orchestrator requiring custom tool implementations versus Claude SDK as full runtime with pre-built tools. Includes practical details on TypeScript support, multi-model usage, and security considerations for production deployments.

Introducing V-RAG: revolutionizing AI-powered video production with Retrieval Augmented Generation
Nick Biso introduces Video Retrieval-Augmented Generation (V-RAG), which combines image retrieval with video generation models to improve accuracy and reduce hallucination. The approach builds on existing AWS services and doesn't require model fine-tuning.

20 years in the AWS Cloud – how time flies!
Channy Yun walks through two decades of AWS evolution, from the early days of S3 and EC2 to modern serverless offerings like Lambda, Aurora Serverless v2, and Fargate.

State of the product job market in early 2026
Lenny's biannual tech job market report reveals some surprising trends: AI positions are (obviously) accelerating rapidly, but design roles have plateaued, and the Bay Area now claims over 23% of all PM openings. Worth reading if you're tracking talent flows in cloud-native companies.

AI Is Eating Open Source From the Inside
Really interesting read on how AI coding tools are fundamentally changing our relationship with open source. AI-generated contributions have 1.7x more issues, and I think the point about developers never visiting docs or filing real bugs anymore hits hard. We're outsourcing engagement to tools that don't actually participate in the ecosystem.

MCP Won. MCP Might Also Be Dead.
As someone who has faced the pain of both using (and building) bloated MCP servers, I totally agree that building protocol-agnostic tools that export to everything is the right approach. Write your logic once, export to MCP for ecosystem reach, export to native formats for teams wanting lower overhead. MCP isn't going away, but it's still worth avoiding betting everything on one standard.

Claude Code Best Practices: Lessons From Real Projects
Great post by Ran Isenberg on using Claude Code for real projects. His point that domain expertise matters more than the tool is spot on, especially his example of BMAD generating 36 user flows he didn't know he needed because he was asking the right questions about his domain.

Product management on the AI exponential
Cat Wu describes Anthropic's product management workflow for building with Claude: using Claude.ai for ideation, Claude Code for prototyping, and Cowork for knowledge work. The article breaks down principles like planning in short sprints and favoring demos over documentation as models improve faster than traditional product cycles.

Are AI agents actually slowing us down?
Great post by Gergely Orosz on the hidden costs of AI coding agents. The data from Amazon, Meta, and Uber showing increased outages and bugs should scare everyone. Productivity metrics don't tell the whole story when quality suffers.

The Convergence Problem: Rethinking the 2028 Global Intelligence Crisis
The real value of SaaS isn't just the software, it's the centralized responsibility for compliance, security, and integration. I'm increasingly convinced that AI won't eliminate this need, it'll just redistribute the complexity in ways we haven't fully mapped yet. This post articulates some of my thoughts.

Podcasts, Videos, and more

Analytics for Modern Data Lakes & AI | Serverless Office Hours
Scott Rigney, Vijay Jain, Theo Tolv, and Andy Warfield join Eric Johnson to show how Amazon Athena powers over one billion queries per week with sub-second starts and no infrastructure to manage.

Your .NET Worker Service Is Slower and More Expensive Than AWS Lambda!
James Eastham walks through migrating .NET worker services from traditional polling to Lambda-based SQS processing. Includes practical code examples, failure handling patterns, batch processing configurations, and a load simulation showing how Lambda scales compared to traditional workers.

New from AWS

Upcoming Events

March 26, 2026 - AI Codecon: Software Craftsmanship in the Age of AI by O'Reilly Media, Inc.

Final Thoughts 🤔

There’s a pattern emerging here, and it’s getting hard to ignore.

Agents are no longer just calling APIs. They’re streaming, executing, observing, retrieving, and operating inside real environments. The shift from “model as a function” to “model as a system” is happening faster than most of us suspected.

But as the surface area expands, so does the blast radius.

Real-time streaming and shell access make agents more useful, but also more dangerous. Faster sandboxing helps, but it’s a response to a problem we’re actively accelerating. Observability and retrieval are becoming first-class not because they’re nice features, but because without them, these systems are unmanageable.

At the same time, the distance between idea and deployment keeps collapsing. Prompts to production is no longer the exception, it's the norm. The constraint is no longer building. It’s judgment.

And that’s the tension.

We’re building systems that can do more than ever, faster than ever. But the signals from production, open source, and even large engineering orgs are clear. Speed without rigor creates fragility. Automation without accountability creates noise.

The next phase isn’t just about making agents more capable. That part is already happening.

It’s about making them trustworthy.

And that’s a much harder problem.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #357: S3 Turns 20! 🥳

2026-03-17T12:00:00Z

S3 Turns 20! 🥳

In our previous issue, AWS helped your AI agents go rogue, Anthropic put AI code review SaaS on notice, and GPT-5.4 arrived just in time for a government contract. This week, S3 turns 20, AWS makes agents more stateful and observable, and Claude expands to a 1M token context window. Plus, we've got plenty of awesome content from the cloud, serverless, and AI communities.

News & Announcements

Amazon S3 just turned 20 years old. Two decades of storing everything, and somehow still not quite old enough to legally drink in the US. S3 has quietly become one of the most important primitives in all of computing, and AWS is still evolving it. This week, Amazon S3 introduces account regional namespaces for general purpose buckets. No more global bucket name collisions. It took 20 years, but we finally get namespacing that aligns with how people actually build multi-account systems. Progress.

AWS also continues to round out its AgentCore story with three meaningful updates. The runtime now supports stateful MCP server features, memory now supports streaming notifications for long-term memory updates, and the runtime now supports the AG-UI protocol. Taken together, this is AWS pushing toward agents that are more stateful, observable, and interactive instead of just stateless prompt loops duct-taped together.

And speaking of observability, Amazon Bedrock now supports visibility into first token latency and quota consumption. First token latency is one of the most important user experience metrics in AI systems, and having this exposed natively is a big step toward operating these workloads like production systems instead of using fragile manual instrumentation.

On the developer tooling side, AWS CDK Mixins is now generally available, making it easier to compose reusable infrastructure patterns without copy-pasting stacks. It doesn't mean I like CDK now, but this should help cut down on all that spaghetti infra code. And AWS Lambda Managed Instances now supports Rust, which feels like a natural fit for high-performance, long-running serverless workloads.

AWS also announced a deeper collaboration with NVIDIA to accelerate AI workloads from pilot to production. Not surprising, but another signal that the real battle isn’t just model quality anymore. It’s who can operationalize AI at scale.

Over at Anthropic, the context window race continues. 1M context is now generally available for Opus 4.6 and Sonnet 4.6. That’s not just a spec bump, it fundamentally changes how you think about retrieval, memory, and application design. Alongside that, Claude is getting more practical: it can now build interactive visuals directly in your conversation and is continuing to expand its specialized tools for Excel and PowerPoint. Less “chatbot,” more “useful coworker.” They also announced The Anthropic Institute, which looks like a broader push into research, policy, and long-term AI impact.

Google officially closed its acquisition of Wiz, locking in one of the biggest cloud security deals ever. As AI workloads expand, security is quickly becoming a first-class concern once again, especially in multi-tenant, multi-cloud environments.

And finally, Cloudflare keeps shipping practical improvements at the edge. They showed how RFC 9457-compliant error responses can reduce agent token costs by up to 98%, which is the kind of optimization that actually matters at scale. And AI Security for Apps is now generally available, continuing their push to make the edge a viable place to run and secure AI-powered applications.

Tutorials

Lambda Managed Instances for Steady Workloads by Lucas Vera
The OODA Loop Pattern for Autonomous AI Agents — How I Built a Self-Improving System by Yedan Yagami
The complete guide to building skills for Claude/Codex by Rohit
Multimodal embeddings at scale: AI data lake for media and entertainment workloads by Hammad Ausaf
Improve operational visibility for inference workloads on Amazon Bedrock with new CloudWatch metrics for TTFT and Estimated Quota Consumption by Zohreh Norouzi
Secure AI agents with Policy in Amazon Bedrock AgentCore by Bharathi Srinivasan
Powertools for AWS Lambda: Simplify Observability by Darryl Ruggles
Serverless applications on AWS using Lambda with Java 25, API Gateway and DynamoDB - Part 1 Sample application by Vadym Kazulkin
Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 1 Sample applications by Vadym Kazulkin
Collaborating with agents teams in Claude Code by Heeki Park
How I built LennyRPG by Ben Shih

Reads

AI Didn’t Wait for Security. Now What?
Ran Isenberg breaks down why blocking AI tools fails and walks through a framework for governing AI adoption with centralized brokers, sandboxed environments, and skill catalogs. The AWS Kiro outage serves as the cautionary tale for what happens when AI inherits elevated permissions without proper isolation.

Operationalizing Agentic AI Part 1: A Stakeholder’s Guide
Nav Bhasin from AWS Generative AI Innovation Center outlines four criteria for identifying agent-appropriate work: clear boundaries, judgment across tools, measurable success, and safe failure modes. Part one of a series aimed at helping enterprises move from AI investment to actual execution.

Agentic AI in the Enterprise Part 2: Guidance by Persona
Part 2 of AWS's enterprise agentic AI series provides role-specific guidance for P&L owners, CTOs, and CISOs. Nav Bhasin walks through the practical concerns each persona should focus on, from KPIs and architecture decisions to security models and compliance frameworks. Surprisingly concrete for an AWS blog post.

I'm Building Agents That Run While I Sleep
Abhishek Ray built an open-source Claude Code skill that uses headless browser agents to verify AI-generated code against acceptance criteria you write upfront. The system includes pre-flight checks (pure bash, no LLM) and a planner that figures out how to test your specs with Playwright.

What AWS Actually Shipped in the Last 12 Months (Non-AI Edition)
Tobias Schmidt takes a comprehensive look at AWS releases over the past 12 months, filtering out the AI hype to focus on serverless and infrastructure improvements.

Skills vs MCP — Why Your AI Needs an Orchestration Layer
Alex Moening explores how MCP's tool proliferation degrades AI performance through context overload. The data shows 20-50% accuracy drops as context grows, and just 7 MCP servers consumed 34% of Claude Code's token budget. He proposes a skills layer that routes intents to workflows, loading tools only when needed.

Slop Creep: The Great Enshittification of Software
Boris Tane introduces "slop creep" as the gradual degradation of codebases through individually reasonable but collectively destructive decisions. He explores how AI coding agents accelerate this problem by lacking holistic system understanding, and proposes tight planning with code snippets rather than autonomous implementation.

Podcasts, Videos, and more

Serverless CrAIc Ep82: AI Is Changing Software Engineering — Why Your North Star Matters
This Serverless Craic team covers the North Star framework, the difference between leading and lagging metrics, and how AI tools are removing friction from development cycles. They discuss the increasingly popular opinion of why product-oriented engineering practices matter even more when you can ship features in hours instead of months.

Serverless resilience: A practitioner's guide | Serverless Office Hours
Ben Freiberg and Marco Jahn walk through battle-tested patterns for resilient serverless systems, covering cell-based architectures, deployment trade-offs, and multi-region failover strategies. The focus is on moving beyond platform defaults to implement proven architectural strategies that minimize downtime when failures occur.

Claude Code in Action
Anthropic has released a comprehensive training course covering Claude Code fundamentals, from architecture and tool integration to MCP server extensions. The course targets developers looking to incorporate AI assistance into their existing workflows, with modules on context management and version control integration.

This week on How I AI: From Figma to Claude Code and back & From journalist to iOS developer
Gui Seiz and Alex Kern from Figma show how to pull a live interface from production, staging, or localhost into Figma, turn it into editable design frames, explore variations collaboratively, and push changes back into code using Claude Code and MCPs.

New from AWS

Developer Tools

Chaos Engineering for AWS Lambda: failure-lambda 1.0
Gunnar Grosch announces failure-lambda 1.0, a chaos engineering tool rewritten in TypeScript with AWS SDK v3. The new version adds timeout and corruption failure modes, plus a Lambda Layer that enables fault injection across any managed runtime without code modifications.

FieldTrip — Search every field across your schemas
From the creator of EventCatalog, David Boyne introduces FieldTrip, an open-source CLI tool that discovers and indexes schema files (OpenAPI, AsyncAPI, Protobuf, Avro, JSON Schema) in your codebase. It provides three visualization modes: a searchable table, a heatmap showing which properties appear in which schemas, and a force-directed graph of schema relationships.

Upcoming Events

March 26, 2026 - AI Codecon: Software Craftsmanship in the Age of AI by O'Reilly Media, Inc.

Final Thoughts 🤔

Somehow all of my “free time” lately has turned out to be anything but. It’s been busy… but also incredibly productive. The kind of productive where ideas are actually turning into things, not just scribbled in a note on my reMarkable waiting for the right moment.

I’ve also got a new blog post dropping tomorrow: “The Convergence Problem: Rethinking the 2028 Global Intelligence Crisis.” It digs into the idea that AI is making automation trivial, but without what I’m calling productive imperfection, we risk optimizing everything into sameness. When everything is equally good, differentiation starts to disappear, and that has some pretty interesting implications for how we build products, companies, and markets.

On the experimentation side, I’ve been continuing my deep dive on memory systems for agents, and this is where things are getting really interesting. When agents only remember what they need, when they need it, their behavior becomes surprisingly constrained and repeatable. Not brittle. Not random. Actually predictable in a way that feels much closer to designing systems than prompting models.

It’s not about larger context windows, but more about controlling what not to remember, when to retrieve, and how to evolve state over time. That shift changes everything. I’ll be writing a lot more about this soon.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #356: OpenClaw, Now with More Cloud! 🦞☁️

2026-03-10T12:00:00Z

OpenClaw, Now with More Cloud! 🦞☁️

In our previous issue, DSQL kept checking boxes, serverless PHP got a major upgrade, and Dario Amodei tried blocking production of the T-1000. This week, AWS helps your AI agents go rogue, Anthropic puts the AI code review market on notice, and GPT-5.4 arrives just in time for that Department of War contract. Plus, we've got a ton of awesome contributions from the community.

News & Announcements

Amazon is now offering OpenClaw on Lightsail. Apparently AWS would like to contribute its servers and bandwidth to the noble cause of helping your personal AI agents go fully rogue. At least now you don't have to self-host the chaos or roll the whole stack yourself.

Policy in Amazon Bedrock AgentCore is now generally available, which intercepts agent-tool traffic and evaluates each request before allowing or denying access. It's a great feature, but it also means the “simple” agent architecture now comes with more moving parts to reason about.

AWS also announced a new Kiro power to help with durable functions development (Accelerate Lambda durable functions development with new Kiro power). One of the downsides of creating a new state management programming interface is that the LLMs aren't trained on it, so giving Kiro a dedicated power to understand it is probably the only way to keep developers from giving up on it.

The Guardian reported on drone strikes and the implications for Gulf-hosted AI infrastructure. It does make an uncomfortable kind of sense that data centers may soon need their own air defense systems, which is a sentence that should concern everyone. The only thing worse would be letting the AI run those defenses autonomously so it can protect itself from intentional human shutdowns. 🤖

Anthropic announced Code Review for Claude Code, and as is the norm with Anthropic, they just put every other AI-powered code reviewer on notice. They keep shipping features that feel less like demos and more like a direct threat to entire categories.

And finally, OpenAI rolled out GPT-5.4, just in time for that big Department of War contract, because nothing says progress like ever more capable AI landing exactly where the defense budget can appreciate it most.

Tutorials

Serverless applications with Java and Aurora DSQL - Part 4 Understand DPUs in Explain Analyze Verbose by Vadym Kazulkin
MCP ServerLESS: Building MCP Functions on AWS Lambda with TypeScript and AWS SAM by Kelwin Ferreira
Automate AWS Lambda Runtime Upgrades with AWS Transform custom by Venugopalan Vasudevan and Gokul Sarangaraju
Running Small AI Models on Lambda with ONNX by Ronny Roeller
Common workflow patterns for AI agents by Anthropic
Safe AWS Lambda Durable Functions with XState by szymon-szym
Serverless Bedrock: How I invoke Claude from Lambda in warrantyAI by Harish Aravindan
Building and Shipping Apps Faster with Kiro’s Agentic Power by Awedis Keofteian
AWS Lambda Managed Instances with Java 25 and AWS SAM – Part 5 Lambda function initial performance measurements by Vadym Kazulkin
A Serverless Recipe Assistant with Bedrock AgentCore, Knowledge Bases, and S3 Vectors by Darryl Ruggles
OpenClaw on AWS Bedrock AgentCore: Secure and Serverless by Matias Kreder
Circuit Breakers on AWS Lambda: Why In-Memory State Silently Fails by Gunnar Grosch
AWS Lambda Managed Instances with Java 25 and AWS SAM – Part 6 Lambda function performance improvement approaches by Vadym Kazulkin
Building custom model provider for Strands Agents with LLMs hosted on SageMaker AI endpoints by Dan Ferguson

Reads

The Complete Guide to Building Skills for Claude
This guide is a fantastic resource whether you’re building agents or assistive AI workflows, showing exactly how to package repeatable processes into reusable skills so your AI stops improvising every task and starts executing like a well-trained teammate. 🔥

How I Dropped Our Production Database and Now Pay 10% More for AWS
I'm not sure I agree with letting AI agents anywhere near production Terraform in the first place. The post describes running terraform apply through Claude Code without manually reviewing the plan, then being surprised when a long list of resources got destroyed. That feels like the automation was working exactly as designed (just on the wrong state file).

Your LLM Doesn't Write Correct Code. It Writes Plausible Code.
This is a great take on LLM-generated code from Hōrōshi, who demonstrates that the real problem isn't syntax errors but plausible incorrectness. The key insight: LLMs work best when you define acceptance criteria before generating code, not after.

AI Doesn’t Reduce Work—It Intensifies It
An eight-month study about AI productivity confirms exactly what I've been seeing: AI tools don't give us more free time, they just let us do more work in the same hours, and that's not sustainable long-term.

Custom AWS Serverless Blog Built in 10 Hours with AI
Darryl Ruggles built a production serverless blog in 10 hours using Claude Code. But while AI accelerates development, it still requires experienced judgment for architecture and security decisions, which feels like exactly the right framing for where we are with these tools. For now.

Trust Is the Architecture (Part 1)
Daniele Frasca explores governance and trust considerations for serverless at scale, covering multi-team coordination, event-driven architecture contracts, data residency compliance, and audit requirements. All the things that matter much more than the technology you choose.

The AI political resistance has arrived
What do you do when AI threatens to destroy humanity? Write a strongly worded letter! 🙂 The Pro-Human AI Declaration, signed by an unprecedented coalition of labor, religious, and political organizations, establishes five principles for human-centered AI development. And it was all cloak and dagger with a secret meeting that intentionally left out Big Tech reps. 🕵️

Improving skill-creator: Test, measure, and refine Agent Skills
Anthropic's new skill-creator features focus on testing workflows: parallel eval execution to avoid context bleed between runs, A/B comparison tools for iterating on improvements, and capability uplift metrics. AI making AI better, more predictable, and auditable.

Something big is happening in AI — and most people will be blindsided
Matt Shumer argues we're hitting a transformative AI moment where models can now handle complete jobs autonomously, not just assist with tasks. There's still a lot of nuance that goes into building software, but the scope and complexity of tasks AI can now handle is exponentially higher than a year ago.

Podcasts, Videos, and more

AWS Bites #153. LLM Inference with Bedrock
Really great deep dive from Eoin and Luciano on Bedrock's structured outputs and constrained decoding. If you're building anything that needs reliable JSON parsing, be sure to give it a watch.

Why .NET Devs Should Stop Writing Lambda YAML Forever
This tutorial from James Eastham demonstrates how CDK lets .NET developers define infrastructure using C# instead of YAML or CloudFormation templates. It covers building reusable constructs and automating the deployment of Lambda functions with proper permissions management.

New from AWS

Thoughts from Social

Amazon is holding a mandatory meeting about AI breaking its systems. The official framing is "part of normal business." The briefing note describes a trend of incidents with "high blast radius" caused by "Gen-AI assisted changes" for which "best practices and safeguards are not… pic.twitter.com/XSXOSqALBN
— Lukasz Olejnik (@lukOlejnik) March 10, 2026

Interesting take on Amazon’s response to AI coding incidents. Adding human oversight and requiring senior sign-off sounds reasonable, but it also raises a bigger question: if a company with AWS-level engineering depth is still struggling to harden AI-assisted development workflows, what hope is there for the rest of us?

Developer Tools

OMDA - Organizational Memory Decay AI by Samyak Jain
AI-powered early-warning system that predicts and prevents critical knowledge loss in organizations.

Final Thoughts 🤔

I’ve been spending a lot of time lately continuing work on my local agent orchestrator, and it’s getting… scary good. 😬 Watching an army of agents coordinate work across isolated sandboxes and shared context without stepping on each other is both fascinating and slightly concerning.

I’m also still deep in the Context Engineering and AI memory management rabbit hole. The more time I spend working on this, the more convinced I am that proper memory architecture is going to be the difference between chaos and reliable AI.

And as always, my side projects are quietly making progress in the background. I’m pretty excited about one in particular. Hopefully I’ll have more to share soon.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #355: Saving Us From Skynet 🤖

2026-03-03T12:00:00Z

Saving Us From Skynet 🤖

In our previous issue, DSQL kept inching toward "new default" status, Claude kept launching startup killers, and FinOps consultants started turning their advice into software. This week, DSQL keeps checking boxes, serverless PHP gets a major upgrade, and Dario Amodei blocks production of the T-1000. Plus, we've got some awesome articles from the serverless and cloud community.

News & Announcements

AWS continues to make really smart moves with Aurora DSQL. This week, they launched a playground for interactive DSQL exploration, added support for Tortoise, Flyway, and Prisma, and shipped new integrations for VS Code SQLTools and DBeaver. This is exactly how you turn it into the default: reduce friction, meet developers where they are, and integrate with the tools we already use. DSQL has been checking off a lot of boxes for me lately.

OpenSearch Serverless introduces collection groups to help optimize costs for multi-tenant workloads. This is a genuinely great feature for SaaS architectures that need isolation without exploding infrastructure spend. That said, I still don’t love the overall pricing model. It’s better, but not quite where I’d like to see it for broader adoption.

For those of you still writing Java like it’s 1999, this one’s for you. The AWS Lambda Durable Execution SDK for Java is now available in developer preview. Durable execution patterns in Java on Lambda might not be trendy, but they’re very real in large enterprises. If that’s your world, I'm sorry. But also, this is a meaningful step forward.

Amazon Bedrock had a big week too. Batch inference now supports the Converse API format, which is 🔥. Converging on a single format across real-time and batch inference is absolutely the right move. Fewer abstractions. Fewer translation layers. Less messy glue code. Plus, server-side tool execution with AgentCore Gateway is now available, which is a major step toward fully-managed serverless agents. Let the platform handle the orchestration loop so we don't have to keep upgrading our agent frameworks every 15 minutes.

OpenAI and Amazon announced a strategic partnership (obviously). The gravitational pull between model providers and cloud platforms was always going to win. Alongside that, Bedrock launched an OpenAI-compatible Projects API, making migration and interoperability much simpler. Less friction, fewer rewrites, and one more signal that the model layer is becoming commoditized infrastructure.

On a more serious note, Anthropic published a statement from Dario Amodei regarding discussions with the Department of War. I agree with the principles outlined there. As AI becomes more capable, governance and alignment discussions are not optional. I feel like watching The Terminator, The Matrix, and WarGames needs to become a standard part of the War Department's new employee onboarding.

And to close things out, two awesome announcements. Valkey Admin brings visual cluster management to Valkey, which should make operating distributed cache clusters far less painful. And Bref 3.0 is officially out, continuing to make PHP on AWS Lambda a very real (and increasingly polished) option.

It’s been well over a decade since the first serverless functions, yet achieving near-native performance without platform sprawl or cold-start penalties is still harder than it should be. Akamai Functions changes the equation with a WebAssembly-native runtime built on open standards like Spin and WASI, offering microsecond startup times and instant scale across a unified cloud-to-edge platform. Whether you’re writing in Rust, Go, Python, or TypeScript, you get a memory-safe, portable execution layer that integrates compute (CPU/GPU), storage, and security before requests ever hit your core infrastructure. If you’re rethinking how to build high-performance, event-driven systems without the operational overhead of traditional serverless, this is definitely a platform worth exploring: Akamai Functions. Sponsored

Tutorials

Understanding Lambda Tenant Isolation by Pubudu Jayawardana
I Rewrote My Step Function as a Durable Function by Danielle Heberling
How to Monitor Event Delivery in Amazon EventBridge by Renaldi Gondosubroto
Streaming Bedrock Responses Through API Gateway and Lambda by Gunnar Grosch
I Enabled Aurora Data API and My AI Agent Started Querying the Database Directly by Kohei Aoki
AWS Lambda Durable Functions on Hexagonal Architecture: The Pattern You’ve Been Looking For by Matheus das Mercês
Serverless applications with Java and Aurora DSQL - Part 5 Support for identity columns and sequence objects added by Vadym Kazulkin
AWS Lambda Managed Instances with Java 25 and AWS SAM – Part 4 Monitoring, unsupported features, challenges and pricing by Vadym Kazulkin
9 Tips for Reducing API Latency in Agentic AI Systems by J. Simpson
Architecting Low-Latency, Real-Time AI Voice Agents: Challenges & Solutions

Reads

We deserve a better streams API for JavaScript
Great post by James Snell on rethinking JavaScript streams. His async iterable approach shows 2x to 120x performance improvements across all major runtimes, and the pull-based model makes so much more sense than the current Web streams design (no hidden buffering, no eager evaluation). Given that these issues stem from design decisions made before async iteration existed in JavaScript, it's probably time to rethink the design.

The serverless lie: Why I refuse to default to next js
While I certainly agree with Jeremy's take on Next.js and met-frameworks, I'm not convinced that the default should be FastAPI backends hosted on a VPS. Serverless still has sharp edges, but the ecosystem goes well beyond just the function execution focused on in this article. I'm serverless-first until the architecture requires something different.

Claude Built My Wix Website in 3 Hours - Is SaaS Dead?
Ran Isenberg experimented with using Claude to replace his Wix website, successfully migrating to a custom AWS setup (CloudFront/S3) in 3 hours. He walks us through his AI-SDLC approach and discusses what worked, what didn't, and where the real challenges lie in long-term maintenance.

From Orchestration to Authority
Really interesting take on why traditional workflow orchestration falls apart when you introduce AI agents. The key insight here is that autonomy isn't about smarter agents, it's about explicitly defining authority boundaries and governance. This is the drum I've been beating for quite some time now.

Every service I build will die
Great post by Ollie Church on building services that are designed to be replaced. The insight that flexibility comes from architecture (small Lambda functions, EventBridge routing) rather than upfront planning is spot on. This is serverless forcing us to think differently, just like it was intended to (maybe I'm rewriting history a bit, but it fits the narrative 😉).

6,000 AWS accounts, three people, one platform: Lessons learned
Ben Freiberg breaks down how his team manages 6,000 tenant accounts with only a three-person team. Great breakdown of their investment in platform engineering and how they built internal tools to abstract deployment complexity away. Same idea we took with Ampt to maintain complete account-level isolation for security and cost controls.

Code Review Is Not About Catching Bugs
David Poll argues that code review's purpose is validating design intent and architectural coherence, not bug detection. I tend to agree, but I think it depends heavily on what your process is. If you're just skimming code in GitHub, it's unlikely that any developer is going to catch something unless it's glaringly wrong. If you're checking out PRs and testing them as part of your code review, well that's a different story.

Babe Wake Up, AI Killed My Job. Again?
Vishwas examines whether AI is truly replacing software engineers, arguing that code generation is the easy part while problem understanding and architectural decisions remain human responsibilities. I've said it before, and I'll say it again: most engineers know this, most CEOs don't.

Podcasts, Videos, and more

Immutable Patterns of System Design; From Monolith to Agentic AI - James Eastham - NDC London 2026
James Eastham's NDC London talk walks through system design patterns that remain relevant across different architectural paradigms. He discusses some really helpful reliability and performance patterns that work whether you're maintaining legacy systems or building with the latest technologies.

Mitchell Hashimoto’s new way of writing code
Mitchell Hashimoto discusses HashiCorp's journey from open-source projects to a durable business, plus his current approach to using AI in development. The conversation also covers his perspective on the major cloud providers and what's changing for engineers in this AI-native era.

AI Agents Will Do What Cloud Did to Ops - Are You Ready?
Adrian Cockcroft and Jamie Dobson explore the parallels between cloud's automation of ops roles and AI's potential impact on programming jobs. They also discuss organizational adoption patterns and the mindset needed for navigating technological change. Adrian predicted the cloud shift, so probably worth spending some time listening to this one.

New from AWS

Thoughts from Social

Turn Dependabot off | Hacker News
Dependabot is great at keeping you busy and terrible at telling you whether you’re actually in danger. This thread nails the real upgrade path: stop treating version numbers like a threat model and start prioritizing reachability, call paths, and context, otherwise your biggest vulnerability is alert fatigue.

Final Thoughts 🤔

I spent some time experimenting with OpenClaw, then went heads down building my own local agent orchestrator so I could get extremely prescriptive about context management and security. Every agent runs inside an isolated Docker sandbox with limited tool and file access, plus explicit guardrails to keep them on a short leash. I’ve wired the whole thing through a local MCP server so agents can communicate with one another and safely fan out work, inheriting permissions and file access from the parent agent. It’s been fascinating seeing how far I can (safely) push this thing. I’m also getting very close to releasing a new side project I’ve been working on, so stay tuned for that. 🙂

Also, the Data API Client v2.1.4 is out. If you’re using Aurora Serverless v2, please take a look and send me your feedback. 🙏

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #354: Context Engineering is the New Moat 🛡️

2026-02-24T12:00:00Z

Context Engineering is the New Moat 🛡️

In our previous issue, Anthropic leveled up with Sonnet 4.6 and a monster fundraise, AWS sharpened its agent tooling, and serverless databases continued their slow march toward maturity. This week, DSQL inches toward "new default" status, Claude keeps launching startup killers, and FinOps consultants start turning their advice into software. Plus, we have plenty of awesome content from the serverless and cloud community.

News & Announcements

Aurora DSQL dropped some new Go, Python, and Node.js connectors that simplify IAM authentication, which is a pretty big deal if you’ve wasted time with token generation and connection management in serverless environments. Cleaner auth flows plus first-party connectors go a long way toward making DSQL feel less like an experiment and more like the new default.

Aurora DSQL also now integrates with Kiro powers and AI agent skills, so you can build Aurora DSQL-backed applications faster with AI agent-assisted development. If you’re fully bought into Kiro, this is great for you! But if you're still skeptical like me, the Aurora DSQL skill also extends the same capabilities to pretty much any of the other AI coding agents as well.

Anthropic keeps shipping startup killers. They introduced Cowork and finance plugins, pushing Claude further into highly complex domain-specific workflows. And with Preview, Review, and Merge in Claude Code, they’re inching closer to making AI a native part of the pull request lifecycle. Review code and monitor PRs without leaving the app.

On the FinOps front, long-time AWS cost consultant, and perpetual thorn in AWS's side, Corey Quinn, announced that his company Duckbill is expanding into software, raising $7.75M for its new Skyway platform. As cloud costs get more intertwined with AI workloads, expect more advisory shops to turn their playbooks into products. There aren't many moats left.

Tutorials

From Zero to Agentic Coding: Running Claude Code with Amazon Bedrock by Gunnar Grosch
Implementing protected Lambda function URLs in user-facing applications by Arpad Toth
Automatically decompress files in Amazon S3 using AWS Step Functions by Sandeep Mishra, Ali Syed, and Santosh Jade
Building long-running usage reports on AWS by Daniele Frasca
Scaling ECS Fargate like Lambda by Rehan van der Merwe
A Serverless Recipe Assistant with Bedrock AgentCore, Knowledge Bases, and S3 Vectors by Darryl Ruggles
DynamoDB E-Commerce Orders Schema Pattern
Building Reliable Distributed Systems with AWS Serverless by Walter Fernández
Building the AWS Serverless Power for Kiro by Gunnar Grosch
Understanding Lambda Tenant Isolation by Pubudu Jayawardana
How to Build a Serverless AI Agent with Amazon Bedrock and Lambda by Sachin M
AWS Lambda Durable Functions vs Step Functions: a real-world comparison by Davide De Sio

Reads

Claude Built My Wix Website in 3 Hours - Is SaaS Dead?
Ran Isenberg rebuilt his website using Claude Code in only 3 hours, applying AWS's AI-SDLC methodology for structured development. His conclusion is that while building software has become dramatically easier, the real challenge remains in maintaining, operating, and supporting it over time. This seems to be the conclusion most people (sans executive leadership) are coming to.

Vibe Coding Got Me a POC in Days. Production Broke Every Assumption I Had.
Great post by Luca Bianchi on the reality of AI-assisted development. His distinction between vibe coding and real engineering should resonate. AI reduces the cost of change but doesn't eliminate the need for disciplined practices. If anything, you need deeper expertise to orchestrate these tools effectively.

The Software Development Lifecycle Is Dead
Boris Tane explores how AI agents are collapsing traditional software development stages (requirements, design, implementation, testing, review, deployment) into a continuous loop where context engineering matters more than process management. Worth reading if you're thinking about how AI will reshape your development workflows.

How we rebuilt Next.js with AI in one week
Steve Faulkner shares how Cloudflare rebuilt Next.js from scratch in a week using AI, creating vinext with 4x faster builds and 94% API compatibility. The fact that one engineer and Claude Code pulled something like this off for $1,100 in tokens seems to be becoming a very common story.

We Ralph Wiggumed WebStreams to make them 10x faster
Vercel's engineering team built a WebStreams library that achieves 10x+ speedups by eliminating Promise-per-chunk overhead, and they're contributing it upstream to Node.js. I love seeing performance work like this, especially when teams share the optimizations with the broader ecosystem instead of keeping them proprietary.

Deep Dive into AWS Lambda: Official Node.js 24.x Runtime Analysis
Great post that analyzes the Lambda Node.js 24.x runtime source code. This kind of deep dive is super useful because understanding how Lambda actually bootstraps and manages the execution environment helps you write better functions (and debug the weird edge cases).

Context Engineering for Commercial Agent Systems
Context isn’t just what you pass into a model. It’s infrastructure. It defines your isolation boundary, your cost surface, your audit trail, and your upgrade path. This guide isn’t meant to be canon. It’s a distillation of the patterns I’ve seen actually hold up in production.

Podcasts, Videos, and more

AI for content creators | Serverless Office Hours
AWS Serverless Hero Allen Helton and Community Builder Andres Moreno walk through their AI-powered content repurposing platform. The architecture uses Step Functions to coordinate MediaConvert, FFmpeg, and Lambda for extracting quotes and generating shareable content from videos. Very cool.

Cut .NET Lambda Response Times to 300ms with These Steps
James Eastham explains three optimization strategies for .NET Lambda functions: memory allocation, initialization patterns, and native AOT compilation, including before-and-after benchmarks showing how to achieve 300ms cold start times.

Head of Claude Code: What happens after coding is solved | Boris Cherny
Fascinating interview with Boris Cherny on how Claude Code evolved from a terminal prototype to generating 4% of public GitHub commits. I mostly agree that "coding has been solved", because I can't remember the last time I actually wrote a line of code, yet I've produced hundreds of thousands of lines. As he says, though, great engineers are always going to be necessary because coding is just a small part of the software engineering craft.

New from AWS

Thoughts from Social

On two separate occasions Amazon’s Kiro AI assistant caused an AWS outage, one that was 13 hours long. Amazon blames this on “user error not AI error,” which is one of the most embarrassing things you could ever say as a human being https://t.co/SlEJzqYDhH pic.twitter.com/LHFRFPQdPN
— Ed Zitron (@edzitron) February 20, 2026

According to Ed, Amazon's Kiro AI assistant caused two major AWS outages, including one lasting 13 hours. Responding with "this was user error, not AI error," sounds exactly like what an AI bot would say. 🤔

Developer Tools

Code Mode: give agents an entire API in 1,000 tokens by Matt Carey
Matt Carey shares Cloudflare's new Code Mode approach. It is genuinely clever: instead of exposing 2,500+ API endpoints as individual MCP tools (consuming 1.17 million tokens), they give agents just two tools to write JavaScript that discovers and interacts with the API, reducing token usage by 99.9%.

Turning AWS Serverless Experience into a Claude Code Plugin by Gunnar Grosch
Gunnar Grosch built an AWS Serverless Plugin for Claude Code that includes skill guides, the AWS Serverless MCP Server for tool access, and validation hooks. It covers Lambda, DynamoDB, Kinesis, EventBridge, Step Functions, and provides guidance on configurations, error handling, and observability patterns for production use. This should come in very handy.

Final Thoughts 🤔

I spent most of last week and this past weekend writing my guide on Context Engineering for Commercial Agent Systems. It is truly fascinating to see all the work going into responsibly steering AI agents. The OpenClaw moment is also mind-blowing. I do worry a bit about the chaos that unrestricted agents could bring, but there is some real solid engineering going on right now that will deliver a tremendous amount of value.

See you next week,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.

Issue #353: The Claw is the Law 🦞

2026-02-17T12:00:00Z

The Claw is the Law 🦞

In our previous issue, Claude got even smarter, Bedrock made agents more production-friendly, and the future of SaaS got a little more uncomfortable. This week, Anthropic levels up with Sonnet 4.6 and a monster raise, AWS sharpens its agent tooling, and serverless databases continue their slow march toward table stakes. Plus, we have plenty of serverless and cloud content from the amazing community.

News & Announcements

If you've been letting Peter Steinberger run agents on your Mac mini, then you probably already know that OpenAI acquired OpenClaw. The speed at which OpenClaw gained adoption is mind-boggling, further proving how quickly the AI ecosystem is evolving. This article from VentureBeat is a good read if you want to get more of the backstory, like why Anthropic didn't want to be his Valentine. 💔

Speaking of Anthropic, they wasted no time keeping their own momentum going with the release of Sonnet 4.6, continuing the steady drumbeat of faster, cheaper, more capable models. And, as we’ve come to expect, it quickly showed up in Amazon Bedrock. The model wars aren’t about exclusivity anymore. They’re about distribution and operationalization. I still think Anthropic has the edge here.

Anthropic also announced improved web search with dynamic filtering, pushing retrieval closer to something that feels intentional rather than bolted on. Plus, they announced a $30B Series G raise at a $380B valuation, despite the missed opportunity with ClawdBot, er, I mean OpenAIClaw. 🙃

On the AWS side, Bedrock keeps filling in the gaps required to run agents like real systems. The AgentCore Browser now supports proxy configuration, critical for enterprises that live behind corporate firewalls. Bedrock also added support for six fully-managed open weights models powered by Project Mantle, a new distributed inference engine for large-scale machine learning models.

In serverless database land, Amazon Aurora DSQL added identity columns and sequence objects. Seems like something that should have existed on day 0, but better late than never. Maybe we'll get foreign key constraints next?

Outside AWS, Cloudflare introduced Markdown for Agents, which is a subtle but meaningful step toward standardizing how agents consume and interpret structured content. Mistral AI made its first acquisition, buying serverless infra startup Koyeb to bolster its cloud ambitions. This is another signal that model companies increasingly want to control more of the stack. And if you’re working in event-driven architectures, EventCatalog rolled out some major visualizer improvements to help teams actually see what they’ve built.

Tutorials

Integrating Lambda Durable Functions into a Step Functions Workflow by Monica Colangelo
AWS Lambda Durable Functions - Build a Loan Approval Workflow with Checkpoints, Callbacks, and a React Frontend by Darryl Ruggles
AWS Lambda Managed Instances with Java 25 and AWS SAM - Part 3 Create Lambda function with LMI compute type by Vadym Kazulkin
Streaming LLM Responses Through API Gateway REST with Lambda by Pablo Albaladejo
The Middy After Hook Problem: Why Streaming Lambda Observability Is Broken by Pablo Albaladejo
Deferred Observability for Streaming Lambda with TransformStream flush() by Pablo Albaladejo
Testing in Serverless: TDD and Serverless at Scale by Lucas Geovani Castro Brogni
Content-Based Router Pattern by David Boyne
Aurora DSQL: The Serverless PostgreSQL That Scales to Zero (Should You Migrate?) by Dinesh Kumar Elumalai
Nevermore.dev: LLM-as-judge on Lambda Durable Functions by Davide De Sio
DynamoDB On-Demand is Bleeding You Dry: Switch to Provisioned and Save 60% by Suhas Mallesh
Things I Wish I Knew Before I Started Using DynamoDB by Sathiesh Veera

Reads

The AWS Cognito Race Condition That SDK Retries Can’t Fix
Basel Issmail walks through a race condition in AWS Cognito where parallel Lambda functions performing read-modify-write operations on a User Pool Client collide hard. Cognito enforces single-writer semantics with no version tokens or ETags, so the solution requires retrying the full operation cycle with fresh reads, not just the failed request. I haven't used Cognito in a while, but I guess there's still some rough edges.

From Kong-on-K8s to AWS Serverless in 24 Hours: Building a Production‑Grade API Platform
Druhin Dhavala shows us a migration from Kong-on-Kubernetes to API Gateway v2 and Lambda, hitting 120ms p95 latency and $0.01/day in operating costs. If you're evaluating serverless for API workloads, the benchmarks and open-source infrastructure code here are worth a look.

A Bootstrapper's Diary
David Boyne, EventCatalog's founder, is publicly documenting his path from solo bootstrapper to $1M ARR, now 14 months in and 10 weekly entries deep. Each note covers real experiences like pricing decisions, early sales milestones, and hard lessons. If you're interested in the mechanics of open-source monetization, this is a useful resource to follow.

Claude's new constitution
Anthropic has published the full guiding document used to train its Claude models, covering four core priorities: being broadly safe, broadly ethical, compliant with Anthropic's guidelines, and genuinely helpful. Worth reading if you want to understand how a major AI lab is operationalizing values at the training level, not just as post-hoc policy.

Podcasts, Videos, and more

Observability for Distributed Systems | Serverless Office Hours
Joe Alioto and Eric Johnson use a retail application example to walk through request tracking, performance optimization, and error correlation across AWS serverless services.

AI & Java | Serverless Office Hours
James Ward joins Julian Wood to guide Java developers through AI integration using MCP, agent-based architectures with Bedrock AgentCore, and GraalVM optimizations for AI workloads. If you're a Java developer trying to figure out where your life went wrong, this video will give you hope. 😂

Building Smarter AI Agents: Memory Management with AgentCore
Excellent post by Mike Chambers on building smarter AI agents with persistent memory via AgentCore. The progression here is solid: theory first, then a simple Strands SDK demo, then a full advanced agent with persistent memory.

Will AI replace programmers? OpenClaw creator, Peter Steinberger and Lex Fridman
Including this only because I think Peter Steinberger confirms what most developers already know, but leadership teams probably don't. 😑

Serverless Craic Ep81 AI - differentiator or commodity?
Really interesting take from The Serverless Edge crew on AI as a commodity vs. a differentiator. Their core argument lands well: most organizations should be consuming AI, not building foundational models. The actual differentiator is how clearly you understand your own value chain. That's the framing more teams need to hear before trying to hire Carnegie Mellon PHDs.

Aurora DSQL: Serverless, Scalable, Global OLTP Database System (Marc Brooker)
Speaking of Carnegie Mellon, in the second episode of PostgreSQL vs. The World, Marc Brooker joins to give a full overview of Amazon DSQL.

New from AWS

Developer Tools

murataslan1/ai-agent-benchmark: AI coding agents comparison by Murat Aslan
Worth a look if you're trying to make sense of the AI coding agent landscape. The repo tracks SWE-Bench scores alongside user-reported real-world performance, which often tells a very different story. Amazon Q Developer is flagged as declining and Devin AI has essentially vanished from user reports, which is useful context if you're evaluating options.

Why I Built My Own AWS Deployment Tool by Alex Dev
Alex explains the architecture behind effortless-aws, a custom deployment tool that uses ts-morph to analyze TypeScript ASTs and extract infrastructure config directly from handler code, with esbuild for bundling and Effect-TS for orchestration. Infrastructure from Code? What a novel idea. 😉

Final Thoughts 🤔

I just got back from the Oakley Icon Alliance Championships in LA where my daughter and her team competed against the top 7 high school girls flag football teams in the country. This has nothing to do with serverless, I'm just a proud dad. The weather was amazing, the guacamole and margaritas at Escuela Taqueria were even better, and most importantly, the girls had the time of their lives (my daughter's the one holding the phone).

Back to thinking about what's next for me.

Take care,
Jeremy

I hope you enjoyed this newsletter. We're always looking for ideas and feedback to make it better and more inclusive, so please feel free to reach out to me via Bluesky, LinkedIn, X, or email.