PhilipK Devblog

Vercel Workflow

Build durable, reliable, and observable applications and AI agents with the Workflow Development Kit (WDK).

Stories | Cyrus

Insights, tutorials, and case studies on AI-powered development workflows. Learn how teams use Cyrus with Linear and Claude Code to ship 20x faster.

Improving My Hardware Workflow With CI and Nix

One thing you might notice if you read my blog is that I do a lot of hardware projects. Generally, these include a board, some software, and possibly some extraneous components (like CAD design, such as a case). Software tooling is quite mature, but I find that hardware had traditionally lagged quite a bit behind. For a while, I just lived with this, but over the last few months I've put in a bunch of effort to improve my workflow.

Optimizing Agentic Workflows using Meta-tools

Agentic AI enables LLM to dynamically reason, plan, and interact with tools to solve complex tasks. However, agentic workflows often require many iterative reasoning steps and tool invocations,...

Vercel Labs

Tools for devs in the AI era

Inngest - Durable Execution for Workflows & AI

Build reliable background jobs, workflows, and AI agents without extra infrastructure. Automatic retries, flow control, and step-level observability.

Accelerate your developer workflow | Namespace

Namespace accelerates the development workflow of fast-moving software engineering teams. Best-in-class compute and development-supporting services that lead to 2x-10x faster builds, tests, and more.

Pacing consensus

Good development, huge challenge.

There's no reason for software to be slow anymore

The other day, I saw a viral tweet saying that people talking about how LLMs are causing slow, bloated, code are going to eat crow once they re-write everything in super-optimized assembly. We're not quite at the point where we want to write everything in assembly, but some variant of what Nolan Lawson said about testing, you can choose how many bugs you want now, which I less eloquently noted here, is becoming more true for performance.

What We Learned from Letting AI Posttrain AI

We built a posttraining task that runs for 20 hours with the Tinker API. The core bottleneck is research intuition.

Design systems in Storybook

A streamlined workflow for frontend developers

The Fastest Way to Run GitHub Actions | Blacksmith

Speed up your GitHub actions with Blacksmith. Run CI/CD 2x faster, download caches 4x faster, build Docker images 40x faster, and eliminate queue times. Start free today.

Improving LM Studio's MLX Engine for Agentic Workflows

mlx-engine v1.8.5 dramatically improves performance for repeated, long-context agentic workflows by checkpointing your KV cache.

Trying the Software factory pattern.

One of the interesting challenges of the AI ecosystem in 2026 is that new, effective patterns emerge faster than I can adopt them. I’ll find a handful, get back to work, and realize a month later that I’d missed four or five more. The adoption cycle for Imprint this year has been something like: January: get every engineer onto Claude Code every single day March: ok, let’s also get everyone else onto Claude Code or Claude Cowork every single day April: local development is bottlenecked on checkout and worktree model, instead create ~10 local workspaces which each have an independent checkout of every repository, and operate at the workspace level, not at the repository level, so it can generate cross-repository pull requests across frontend, backend, infrastructure and data monorepos June: oh boy, agent-driven development is heavily constrained by lack of a common task management system with higher visibility and less permission complexity than Jira, so let’s migrate the entire company over to Linear and hard stop on Jira July: yikes, now we have visibility into all these tickets, many of them are trivial but managing them through local development isn’t scaling, let’s roll out an orchestrated harness which internally we call “Agent Fleet”, along the lines of Stripe’s Minions The most recent question for me has been figuring out how to adopt the software factory pattern. (After some light research, the specific AI-context origin of this term is slightly messy to attribute, but I think it might be Justin McCarthy in February 2026’s Software Factories And The Agentic Moment.)