5 min read3 weeks ago
There has never been a better time to build software. Today, you can describe an idea to AI and have a working application before lunch. That’s an incredible shift, and it’s exactly why “vibe coding” has become part of the engineering conversation. For prototypes, internal tools, and validating ideas, it’s one of the most exciting […]
5 min read2 months ago
How the “Grill Me” method became a key part of Project Weaver’s approach to AI-assisted software development. In previous articles, we’ve shared some of the thinking behind Project Weaver—the internal engineering framework we’ve developed at profiq to help our teams and AI work together more effectively. Rather than treating AI as a magic code generator, […]
6 min read2 months ago
One of the most interesting things about the current wave of AI-powered software development is that it has dramatically lowered the barrier to creating a working prototype. That’s a good thing. Founders can validate ideas faster, test assumptions earlier, and communicate product concepts in ways that would have required significant engineering investment just a few […]
7 min read2 months ago
We wanted to do another quick recap of the Weaver journey so far for those of you who are just learning about the project, from the first idea through the latest automation and workflow experiments.
10 min read4 months ago
Build a scalable auto-annotation pipeline for object detection using SAM3, DINOv2, and MLPs. Reduce manual labeling, improve dataset quality, and speed up computer vision workflows.
6 min read5 months ago
Learn how Project Weaver helps profiq build custom software, internal tools, and scalable backend systems faster through AI-assisted development.
10 min read5 months ago
There are two ways we’ve explored automating Weaver so far. The first is the obvious one: use GitHub Actions and the second Temporal for Time Travel.
8 min read6 months ago
In the last couple of posts, we talked about planning and documentation as foundations of reliable AI-assisted development.
8 min read6 months ago
A priority is 'Documentation', as a practical way to make coding agents more accurate, more consistent, and far less likely to drift into outdated assumptions. This post explains why documentation matters so much for AI coding workflows, what tends to go wrong with “just search the web” approaches, and why Weaver treats documentation as a first-class citizen inside the repository.
10 min read7 months ago
Why a key AI development capability is workflow planning: the ability for an agent to take a problem, ask the right questions, propose implementation steps, and only then move into execution.
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