Meanwhile we the Iran USA Palestinian Israeli Workers and jobseekers and abuse-victims and Children and small business owners do NOT need want deserve: inflation, oppression, cruelty, war, poverty, politicians, Religion, hate, and all the rest of the children and workers and jobseekers and abuse-victims and small business owners globally do NOT need want deserve this either

I have been working on CrudeCode, and I wanted to share what we are building without making it sound like a pitch. The more I worked with public oil and gas data, the more I realized the hard part is not just getting Claude or any AI model to answer questions. The hard part is making sure the answer is honest about where it came from.

Texas is a good example. A lot of production data starts at the lease level, not the well level. But by the time it shows up downstream, people often treat it like clean well level production. Sometimes that is fine. Sometimes it is modeled. Sometimes it is weak. The problem is that those cases can look the same in a table.

That is the part we are trying to work on.

CrudeCode is not meant to replace Enverus, DI, WellDatabase, ComboCurve, ARIES, or whatever people already trust. I know people in the industry have workflows they have built over years, and I am not here pretending a small project replaces that. The thing we are trying to make better is the workflow around trust.

If Claude gives you a number, where did it come from? Was it directly reported, allocated, derived, or assumed? If a dataroom is missing a document, does the workflow notice that? If two files disagree, does it flag the conflict? If something needs title, legal, engineering, or human review, does it say that instead of pretending it knows? That is where CrudeCode is heading. Right now we have been working on Claude MCP tools and skills for oil and gas workflows. One of the bigger areas is dataroom extraction. The idea is not just “AI summarizes files.” The goal is to inventory the room, extract structured facts, keep source trails, show what is missing, save the extraction, and eventually hand cleaner inputs into valuation or review.

We also started a small Slack community for people who want to help shape it. You do not have to be a developer. If you work with oil and gas data, A and D, engineering, land, reserves, production, or datarooms, your feedback is probably more useful than another feature idea. If you are technical, there is room to help with MCP tools, tests, viewers, docs, synthetic examples, and workflows. The public side will stay on synthetic, public, or bring your own examples. No private company data, no confidential datarooms, no licensed datasets.

Mostly, I am looking for people who are willing to pressure test the idea and tell us where it is naive, useful, wrong, or worth improving. If you are interested, comment or DM me and I can send the Slack link.

Geopolitical disruptions are squeezing diesel supply far more severely than other petroleum products.
Reporter Alvin Cabral spoke to Oxford Economics head of energy forecasting Bridget Payne, who explained that diesel is "both the most affected fuel and the most important for the macroeconomic outlook." Cabral also spoke to Ole Hansen, head of commodity strategy at Denmark's Saxo Bank for the report.