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Get Started Free →Get the first 50 real users through channels the user's ICP already uses. Use when the product shipped and nobody came, the user is "posting more" with no result, or is reaching for paid ads before product-market fit.
.claude/skills/aidevgtm-first-50-users/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 21% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 21% | 0% |
| case-04 | ✓→✓ | = Same ✓ | -13% | 0% |
| case-05 | ✓→✓ | = Same ✓ | 19% | 0% |
> You don't get your first 50 users by posting more. You get them by going where your users already discover tools, and, at the start, by doing things that don't scale.
Use this when: you launched to silence, you're spraying every channel hoping one works, or you're about to buy ads to fix a problem ads can't fix.
Every developer audience has an existing technology-discovery loop: the specific places they already go to find new tools. Your job isn't to invent demand; it's to position yourself inside that loop. And your first cohort is hand-to-hand: the TAB members from talk-to-users are your first users.
Then Evaluation decides everything (see know-if-its-working): can a new dev get value over a weekend, from docs and Stack Overflow, with no support call? If not, more traffic just fills a leaky bucket.
Pre-PMF (you are here for the first 50): unscalable, direct, high-touch.
launch-it), not ten shallow ones.Post-PMF (later): content/SEO, community, dev-influencer partnerships, then paid to amplify what already converts, never to discover it. And once the first 50 are in and retention holds, the hand-to-hand work graduates: build the self-reinforcing engine in growth-loops.
From talk-to-users question 7 ("where do you go to stay current?"), you already have the answer. Rank channels by where your specific ICP is, and go deep on one before adding a second.
Is your ICP concentrated somewhere specific (a subreddit, a Discord, a conference, a tag)?
├─ YES → go all-in there first. Depth beats spread at 0→50.
└─ NO → your ICP may be too broad → tighten it in `who-is-this-for`.talk-to-users Q7).Built from real dev-tool GTM experience, with frameworks from Adam Frankl (The Developer-Facing Startup) and Jakub Czakon (markepear.dev). When a framework can't make the call, that's what a human is for: The DevTool GTM Company.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 21,145 | 16,663 | -21% | 1 | 1 | 0% | 3,046 | 3,615 | +19% | 0 | 0 | — |
case-02 | fail→fail | 27,624 | 24,314 | -12% | 1 | 1 | 0% | 3,842 | 4,571 | +19% | 0 | 0 | — |
case-03 | fail→fail | 29,816 | 20,149 | -32% | 1 | 1 | 0% | 4,142 | 3,862 | -7% | 0 | 0 | — |
case-04 | pass→pass | 34,234 | 23,558 | -31% | 1 | 1 | 0% | 4,899 | 4,245 | -13% | 0 | 0 | — |
case-05 | pass→pass | 32,308 | 23,361 | -28% | 1 | 1 | 0% | 3,657 | 4,362 | +19% | 0 | 0 | — |
case-06 | pass→pass | 19,301 | 18,457 | -4% | 1 | 1 | 0% | 2,847 | 3,462 | +22% | 0 | 0 | — |
case-07 | pass→pass | 18,268 | 15,955 | -13% | 1 | 1 | 0% | 2,744 | 3,406 | +24% | 0 | 0 | — |
case-08 | pass→pass | 14,675 | 14,868 | +1% | 1 | 1 | 0% | 2,097 | 3,173 | +51% | 0 | 0 | — |
case-09 | fail→pass | 19,973 | 16,144 | -19% | 1 | 1 | 0% | 2,656 | 3,106 | +17% | 0 | 0 | — |
case-10 | pass→pass | 17,361 | 14,229 | -18% | 1 | 1 | 0% | 2,474 | 3,075 | +24% | 0 | 0 | — |
case-11 | fail→pass | 18,165 | 14,424 | -21% | 1 | 1 | 0% | 2,631 | 3,192 | +21% | 0 | 0 | — |
case-12 | pass→pass | 17,550 | 15,990 | -9% | 1 | 1 | 0% | 2,383 | 3,251 | +36% | 0 | 0 | — |
case-13 | pass→pass | 20,043 | 12,260 | -39% | 1 | 1 | 0% | 2,841 | 2,815 | -1% | 0 | 0 | — |
case-14 | pass→pass | 17,217 | 14,311 | -17% | 1 | 1 | 0% | 2,373 | 2,949 | +24% | 0 | 0 | — |
case-15 | pass→pass | 14,306 | 9,927 | -31% | 1 | 1 | 0% | 2,437 | 2,311 | -5% | 0 | 0 | — |
case-16 | pass→pass | 15,336 | 16,682 | +9% | 1 | 1 | 0% | 2,210 | 3,114 | +41% | 0 | 0 | — |
case-17 | fail→pass | 16,875 | 13,608 | -19% | 1 | 1 | 0% | 2,215 | 2,691 | +21% | 0 | 0 | — |
case-18 | pass→pass | 16,011 | 11,213 | -30% | 1 | 1 | 0% | 2,140 | 2,714 | +27% | 0 | 0 | — |
case-19 | fail→fail | 14,937 | 14,356 | -4% | 1 | 1 | 0% | 2,059 | 2,851 | +38% | 0 | 0 | — |
case-20 | pass→pass | 18,260 | 17,763 | -3% | 1 | 1 | 0% | 2,681 | 3,682 | +37% | 0 | 0 | — |
case-21 | pass→pass | 17,755 | 18,450 | +4% | 1 | 1 | 0% | 2,529 | 3,373 | +33% | 0 | 0 | — |
case-22 | pass→pass | 16,468 | 13,751 | -16% | 1 | 1 | 0% | 2,758 | 2,977 | +8% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +14 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.