A failure worth fixing once
Three teams worked around the same broken integration environment.
18
checkout
16
billing
13
data
Your AI bill doubled.
Can you say why? We can.
Here is how.
Your bill, split by project, person, task type, and model. Then the seats to cancel and the plans to upgrade.
When the bill doubles,the reasonslook like this:
Marketing started using Claude Code
A team you didn’t expect found a use for the tools.
Heavy work with Fable 5
The default model got smarter, and pricier.
Security fixes before the audit
The work ran hot for three weeks because you asked it to.
Fix the problems. Find good practices.
Cost tools only find things to cut. Quesma also finds problems recurring across teams, and the skills, tools, and routines used in one part of the company but nowhere else.
A skill worth sharing
deploy-preview worked for one team. Others had never seen it.
Platform12/12
Payments7/12
Web2/12
Datanot yet
Instructions agents misread
One repository rule sent every session down the same wrong turn.
“Always run the full e2e suite before committing”
- #4821 fix typo in tooltip → full e2e suite38 min
- #4837 rename a variable → full e2e suite41 min
- #4859 update README → full e2e suite44 min
31 sessions took the same wrong turn
Dependencies nobody decided on
context7-mcp spread until more than half the company relied on it.
10 teams · 50%
Our track record
BinaryAudit
Can coding agents find backdoors in compiled binaries using Ghidra and radare2?
Frontier-model training
We built training environments for difficult, multi-hour agent tasks. The work required reading full trajectories: prompts, tool calls, failures, retries, and results.
Independent audit
We audited Blitzy's 66.5% SWE-Bench Pro result, reviewing the environment, required changes, and final score.
Read the independent auditTerminal-Bench 3.0
Quesma contributed to Terminal-Bench 3.0, a benchmark for testing agents on practical terminal tasks.
View the contributorsOpenAI-cited research
OpenAI cited our Baba Is Bench work while examining what makes agent evaluations succeed.
Read the citationLatest from the blog
HN I gave Opus 5.5 one prompt and six hours to visualize Invisible Cities
Claude Opus 5.5 vs GPT-6 Astra one-shot Invisible Cities by Italo Calvino in Three.js: AI design, UX, data visualization and explorable explanations.
Your agent session transcripts are precious, keep them
AI vendors collect every coding session they can, yet most teams discard their own. Quesma Shipper collects them into Amazon S3.
Token economics in Amsterdam: Inside the first Tokenomicon
The Linux Foundation expands its FinOps work with a Tokenomics organization focused on AI spend. It held its first in-person conference in Amsterdam.
Bring clarity to your AI coding budget
Early access opens soon. The open-source collector runs in your environment and the session data stays in your cloud. Contact us to be one of the first teams.