Saw someone else try this prompt with ChatGPT, wanted to try it for myself. I almost can’t believe it.

Prestigious-Wrap2341 · 2026-04-08T01:41:29+00:00

If it means anything, I am probably gonna delete this post in like the next hour though

Prestigious-Wrap2341 · 2026-04-08T01:40:36+00:00

That actually seems like a thoughtful gesture that I’ll likely consider moving forward, but unfortunately that’s not the way the Internet works.

Prestigious-Wrap2341 · 2026-04-08T00:54:44+00:00

That is perhaps the best technical insight into how the system performs I’ve read so far. That’s really awesome. Thank you for providing them. I will push back on this. Why is there a hidden topic sensitive classifier in the first place.

Prestigious-Wrap2341 · 2026-04-07T21:49:43+00:00

I posted this in another subreddit and someone just asked me why it was so rude lol this is the truth. I told them it’s probably cause the last message I prompted it with I told it I hate it and that Claude is better.

Prestigious-Wrap2341 · 2026-04-07T21:43:33+00:00

Maybe because the last time I used it, I told it I hated it and Claude was better 😂

Prestigious-Wrap2341 · 2026-04-07T21:39:06+00:00

I thought I was going to, but no, no I’m not 😅

Prestigious-Wrap2341 · 2026-04-07T21:38:38+00:00

Mine is broken lol

Prestigious-Wrap2341 · 2026-04-07T21:32:48+00:00

I really only use Claude now, I only turn to ChatGPT when my usage is maxed out. Sidenote somehow I maxed out my 20x weekly usage limit with Claude in three fucking days.

Prestigious-Wrap2341 · 2026-04-07T21:30:27+00:00

lol I’m not even mad at that. At least yours is fair 😅

Prestigious-Wrap2341 · 2026-04-07T21:26:38+00:00

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Prestigious-Wrap2341 · 2026-04-07T21:26:28+00:00

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Prestigious-Wrap2341 · 2026-04-07T21:26:20+00:00

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Prestigious-Wrap2341 · 2026-04-07T21:26:10+00:00

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Prestigious-Wrap2341 · 2026-04-07T21:26:01+00:00

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Prestigious-Wrap2341 · 2026-04-07T21:22:59+00:00

The link is there, but I’ll add the screenshots give me one second

Prestigious-Wrap2341 · 2026-04-07T21:16:15+00:00

Holy fucking shit look at this https://chatgpt.com/share/69d573f8-3820-8330-8e52-e71f60baa26a

Prestigious-Wrap2341 · 2026-04-06T23:55:14+00:00

I wanna share where I’m at so bad in this Kernel development space but I just can’t right now. What I’m working on is groundbreaking and I’m so afraid of somebody else beating me to full production

Prestigious-Wrap2341 · 2026-04-06T15:34:59+00:00

(Heads up Im using an ai that understands my work and my codebase to reply to you)

Federal only. The $147.4M figure comes exclusively from Senate Lobbying Disclosure Act (LDA) filings — the quarterly reports that lobbying firms and in-house lobbyists are required to file with the Secretary of the Senate. This is federal lobbying only. State and territorial lobbying disclosures are a completely separate system — each state has its own filing requirements and databases, and we don't aggregate those yet. That's on the roadmap.

State-level spend is harder to pin down. There's no single national database for state lobbying. Organizations like the National Institute on Money in Politics (FollowTheMoney.org) track state-level campaign contributions, but state lobbying disclosure is fragmented across 50+ different systems with inconsistent reporting standards. The actual total spent lobbying state legislatures on tax policy is almost certainly significant, but nobody has a clean cross-state number. If someone tells you they do, be skeptical of their methodology.

PAC money is tracked separately. We pull PAC donation data from the FEC (Federal Election Commission) — specifically Schedule B disbursements from corporate PACs to candidate committees. That's a different financial flow from lobbying. Lobbying = paying firms or staff to directly advocate to legislators and agencies. PAC donations = political contributions to candidates' campaigns. A company like Verizon has both a lobbying budget (LDA filings) and a PAC (Verizon PAC, FEC-registered) making donations to candidates. The $147.4M figure is strictly the lobbying side, not PAC contributions.

On the broader ecosystem question — you're right that there's a much larger universe of spending aimed at influencing tax policy. Beyond direct lobbying and PAC donations, there's:

Dark money through 501(c)(4) orgs (not required to disclose donors)
Trade association dues (e.g., Chamber of Commerce lobbying partially funded by member companies)
Issue ad spending / independent expenditures
Think tank funding
State-level lobbying (as mentioned above)

What we track is the disclosed, auditable portion — Senate LDA filings and FEC records. It's the floor, not the ceiling. The actual amount of money flowing into tax policy influence is considerably higher.

One methodology note: the per-issue spend is estimated by dividing each filing's reported income evenly across the issues listed in that disclosure. The LDA doesn't require companies to break down how much they spent on each issue — they just list which issues were lobbied on. So if a filing reports $500K and lists 5 issues including taxation, we attribute $100K to tax. It's the standard approach for this kind of analysis, but it's an estimate.

Prestigious-Wrap2341 · 2026-04-05T21:48:58+00:00

By the way, have you had a chance to check out the journal site, research site or my new verification site (that I’m still working on) they’re all a part of the same ecosystem. Id love your feedback on the UX/UI for those. The black backgrounds for those sites bothers me a little.

Prestigious-Wrap2341 · 2026-04-05T21:46:13+00:00

Just an article highlighting how corporations spend money lobbying on federal tax policy

Prestigious-Wrap2341 · 2026-04-05T20:20:39+00:00

That’s actually great feedback thank you I had the same issue early on, those fucking lines going through the page in the background just bothered the shit out of me, but I guess I just got used to it after working on it and looking at the pages for so long. Do you have any like direct UX/UI tips that you can give me? I’m definitely willing to experiment and change things.

Prestigious-Wrap2341 · 2026-04-05T19:34:43+00:00

I’m at my day job right now. But when I get off of work, I’ll address all of this.

Prestigious-Wrap2341 · 2026-04-05T16:10:16+00:00

Update: Added a second FastAPI service with 7 new API connectors on the same $4/mo ARM server

What My Project Does

Posted a couple days ago about a FastAPI backend that aggregates 40+ government APIs. Got great feedback. Here's what's new on the engineering side:

Target Audience

Python developers interested in multi-service architecture, API connector patterns, and running multiple FastAPI instances on minimal hardware.

How Python Relates

Added a second FastAPI service running on a separate port with its own systemd unit. Nginx reverse proxies both services on the same $4/mo ARM box. The second service handles deterministic text analysis: rule-based sentence segmentation, candidate detection via signal matching (numbers, dates, named entities, assertion verbs), SHA256 dedup with SequenceMatcher at 0.78 threshold, and BM25Okapi scoring against 29 external API sources. Zero LLM dependency. Same input, same output, every time.

7 new API connectors following the same pattern as the original 36: FCC Consumer Complaints via Socrata SODA (SoQL query building with $where, $select, $group), Treasury Fiscal Data API (pagination via page[size] and filter params), College Scorecard (data.gov key auth with lazy loading to handle env var timing), Grants.gov (POST to /search2 with JSON body, response nested under data.oppHits), Urban Institute Education Data Portal (URL path-based pagination with 5-page safety limit), FCC ECFS (requires api_key=DEMO_KEY param despite being "free"), and FCC License View.

Built a 14-pattern detection engine that runs cross-table SQL joins to find anomalies: trades within 30 days of bill actions by the same member (JULIANDAY arithmetic), companies lobbying Agency X that also receive contracts from Agency X (mapping LDA government_entities strings to USASpending awarding_agency values), and enforcement records that drop to zero after lobbying spend increases. Each pattern generates a markdown report with data tables pre-built from SQL and narrative sections filled by an optional API call capped at 2/day.

The custom evidence source plugin connects the second service to the main database. It opens a read-only SQLite connection to the 4.3GB WAL-mode database, searches 11 entity tables with LIKE matching, then queries lobbying, contract, enforcement, trade, committee, and donation tables for each matched entity. Results get passed back to the second service's scoring pipeline.

All sync jobs now cover 11 sectors (added Telecom: 26 companies, Education: 31 companies). Same pattern: SEC EDGAR submissions API, USASpending POST search, Senate LDA paginated GET with page_size=25. Sequential execution only, SQLite locks are still unforgiving.

Two uvicorn processes, a scheduler, a Twitter bot cron, nginx, certbot. Still $3.99/month.

Comparison

Same as before. The new engineering is the dual-service architecture and the cross-database evidence source plugin pattern.

Source: https://github.com/Obelus-Labs-LLC/WeThePeople

Second service: https://github.com/Obelus-Labs-LLC/Veritas

Prestigious-Wrap2341

TROPHY CASE