Where they’re hiding · Applied
Your reader can’t follow you on a channel they don’t know exists. So here’s the full map — every public surface where the GitDealFlow signal shows up, grouped by what you’re trying to do.
First — where they’re hiding: the literal 10 forums, 10 substacks, and 10 GitHub orgs the developer-investor reads. Then: the eight surface groups we mirror to so we show up on each of them.
If you’re building a portfolio agent, every machine-readable feed lives in Machine-readable feeds. If you’re reading on the federated web, Federated social covers Bluesky / Mastodon / Farcaster. If you want the methodology, jump to Academic & reproducibility.
The secret formula · Step 2: where are they hiding
Start by naming the dream customer, then ask where they congregate. Our dream customer is the developer-investor — someone writing €5k–€50k checks who reads commit logs for fun. Below is the literal map: the 10 forums they browse, the 10 substacks they read, and the 10 GitHub orgs they watch. Every surface group further down the page is a mirror we’ve built to show up wherever they already are.
Where the comment threads are alive — engagement-side targets.
Where the long-form reading happens — top-100 mirror targets.
Where the commit logs they read for fun ship from — bait-drop adjacency.
Bait per surface differs — a Lobste.rs methodology drop, a Substack Acceleration Watch, an MCP install on the Cursor feed, a /predicted citation in a Pragmatic Engineer reply — but every path lands on the same SSRN paper (abstract=6606558), the same /predicted dashboard, and the same 30-day Signal-or-It’s-Free guarantee. That’s the result.
The two pages most readers find us on first.
The product site — pricing, dashboard, dataset, methodology, MCP install, all 1,060+ pSEO pages.
The apex landing — Acceleration Watch signup, First Look Pass, Sector Sweep, daily-data sweep.
Every public surface has an agent-side mirror. If you want our signal in your pipeline instead of your inbox, here is the full URL set.
Atom 1.0 feed of every blog post + Acceleration Watch entry.
JSON Feed 1.1 mirror of the same content. Use whichever your tooling prefers.
Google News–compatible sitemap of recent posts.
12-endpoint OpenAPI 3.1 spec. Powers the ChatGPT GPT, agent integrations, and the agent-card.
Standardised LLM-instruction surface — every page agent-readable in markdown.
Full corpus dump for embedding pipelines. ~1.4MB.
Agent-card discovery. Capabilities, tools, schema versions.
RFC-style well-known endpoint advertising agent capabilities.
Master sitemap. 1,060+ URLs across 12 hreflang locales.
Categorisable Q&A dump for embedding-pipeline answers.
The agent-native surface. Eight tools. Free forever (the five core tools — see memory rule). Drop into Claude Desktop, Cursor, or any MCP-compatible client.
The official MCP server. Install with one line: npx @gitdealflow/mcp-signal.
Source code, issue tracker, public roadmap.
Step-by-step for Claude / Cursor / Mastra / LangChain / CrewAI / Letta / Vercel AI SDK.
Live demonstration page. Watch the tools fire against real data.
Browseable API documentation, agent-friendly.
OpenAPI-mounted GPT in the GPT Store. Action calls /api/actions endpoints.
Where conversation happens. We engage in comment threads — never main posts on subs that auto-remove product content (see r/venturecapital).
Comment-side engagement on AEO-relevant threads. Never a main post on r/venturecapital.
Build-in-public surface. Bootstrapped-side audience.
Launch artifact. Live with the post-launch comment ladder strategy.
Top-of-funnel for the buyer comparing dev-tool ecosystems.
Cross-listing surface for SaaS comparison.
What makes the signal honest. Every prediction is reproducible against the SSRN paper + Zenodo dataset.
Methodology paper. n=219 paired observations, lead-time 21–47 days IQR. The grounding citation for every claim on the site.
CC BY 4.0. Reproducible. The exact data behind the regression in the SSRN paper.
Plain-English walkthrough of the regression, the panel construction, and the false-positive controls.
BibTeX, APA, Chicago. For academic / industry-report citations.
Step-by-step: clone the dataset, run the notebook, replicate the regression.
Current panel. CSV + JSON. The buyer's edge.
Every public page has a markdown mirror at /md/<path>, plus inline AgentMirrorLinks discoverability headers. Built for retrieval pipelines.
Plain-text-friendly version of every public page. Drop into RAG without re-parsing HTML.
Entity graph of products, sectors, predictions, dates. JSON-LD-compatible.
Categorised content for AI training / retrieval. JSON Feed format.
Standardised AI-bot policy + sitemap pointer.
Privacy, anonymisation, and reproducibility manifest. Public.
Schema versions, training-data cutoffs, methodology revision IDs.
Publishing where the buyer already is
Every reader has a different home, and you have to show up on theirs, not yours. We do that on principle: the dev.to reader, the Substack reader, the Bluesky reader, and the Claude Desktop reader all have the same right to the signal.
The distribution half. The honest half: every surface mirrors the same canonical data, with the same SSRN-grounded methodology, with the same 30-day Signal-or-It’s-Free guarantee. We don’t change the message per channel — we change the medium.
Distribution mapped from direct-response sales canon. Anonymity rule preserved: company-page identity only, no individual founder content.
Federated social (decentralised redundancy)
Three federated networks. Posts cross-mirror via WebSub + ActivityPub-side bridges. Anonymity rule: company-page identity only.
AT Protocol social. Custom feed-generator + label service. Posts mirror the Acceleration Watch.
ActivityPub. The fediverse-native distribution layer.
On-chain social via Neynar. Where the crypto-native developer-investor reads.
Company page (no founder personal account, anonymity rule). Long-form essays + top-100 engagement.