Experiments that do not need permission to be useful.
Benchmarks, prototypes, tiny utilities, comparisons and things that may never become a polished product.
Graph-aware coding context
Comparing agent answers with and without a generated code graph to see whether structure actually improves repository understanding.
Model routing tests
Provider quality, uptime, rate limits, model availability and how much “free” access survives real usage.
Agent harness benchmarks
Real intentionally broken projects, issue discovery, repair quality, token usage and generated tests.
Tiny developer tools
Small utilities that solve one annoyance well enough to keep around, even if they never deserve a full product page.
AI product trials
Testing claims made by AI products against actual workflows instead of repeating feature lists.
Useful dead ends
Ideas that looked promising and then failed the “would I actually use this?” test.
Graph-aware coding context
The experiment compares the same repository-understanding task with and without graph-derived context. The useful question is not whether a graph looks impressive, but whether it helps an agent find the right files, boundaries and request path with less wandering.
Model routing tests
I test providers as infrastructure rather than a model list: availability, real free quota, authentication friction, endpoint compatibility, uptime and what happens when the preferred route disappears.
Agent harness benchmarks
Benchmarks use intentionally broken projects so an agent has to discover issues, reason about them, make repairs and prove the result with tests. Token usage and failure modes matter as much as a final “success”.
Tiny developer tools
Some ideas are useful long before they deserve a roadmap. This is where small utilities, prototypes and one-purpose helpers get to exist without pretending to be products.
AI product trials
The test starts from a task, not a feature checklist. If a product claims to build, reason, automate or save time, I want to see what survives contact with an actual workflow.
Useful dead ends
Not every prototype deserves continuation. The useful part is recording why it stopped: weak reliability, bad ergonomics, duplicated value, cost, or simply failing the “would I keep using this?” test.