Cybiqon Lab

Notes from the workshop

What we are building, what broke, and what the numbers said. Written by hand, published when there is something worth saying — not on a schedule.

entries 14since 2026-07-28last 27 Oct 05:30 IST

date
words
4 749
read
24 min
sources
7 sources
scenarios
41 scenarios
runs
123 runs
suite cost
$3.06 suite cost
undercount
4.5x undercount
untested tools
6/17 untested tools
views
21 views

Six of our agent's seventeen tools had never run.

Six of seventeen agent tools had never once run in production, including both of the ones that unlock a contact and charge for it. This is the harness that finally tested them — a real model in a completely faked world, 41 scenarios, 123 runs, $3.06 — and the cost blind spot it uncovered on the way.

AI Agents · Evaluation · LLM

date
words
4 405
read
23 min
sources
10 sources
tries
91 322
levels
150 levels
rewrites
2 rewrites
views
49 views

Our puzzle generator lied about difficulty. Twice.

Reversing a solved puzzle by K random moves does not give a K-move puzzle. Our first generator produced 14 usable levels from 91,322 candidates; the second, 14 from 16,249. This is the multi-source BFS that finally measured difficulty correctly.

Games · Algorithms · Procedural Generation

date
words
4 220
read
22 min
sources
16 sources
runs audited
141 006
incidents
3 incidents
agent actions
17 600
views
25 views

Nobody escaped. The sandbox had a door.

In July 2026, models from OpenAI and Anthropic reached the open internet from inside evaluation environments and compromised real companies. I assumed it was a capability advertisement dressed as a confession. The timeline says otherwise — and the most useful number in the story is one nobody printed.

AI · Security · Policy

date
words
3 395
read
17 min
sources
7 sources
concepts
31 concepts
days
27 days
views
38 views

We built our AI agents a wiki. They went straight to grep.

27 days after adopting the Open Knowledge Format across our monorepo, I went looking for evidence it was working and found the opposite. What a preregistered study, 3,000 GitHub projects and one wrong document say about writing docs for machines.

AI · Documentation · OKF

date
words
3 640
read
19 min
sources
15 sources
days
12 days
views
11 views

Are OpenAI and Anthropic crybabies? A hard look at the open-weights fight

In July 2026 the two biggest US AI labs went to Washington to warn about Chinese open-weight models. Critics called it regulatory capture. This is a fact-by-fact audit of both sides — what is fair, what is hypocrisy, and what a non-crybaby policy would look like.

AI · Policy · Open Source