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About this tool
Fill in your company details once and generate ready-to-paste founder prompts for strategy, hiring and investor updates.
The Founder Prompt Pack turns a library of twelve founder prompts — positioning, OKRs, pre-mortems, pricing tests, investor updates, pitch narrative, objection prep, hiring scorecards, interview design, 30/60/90 plans, discovery scripts and churn diagnosis — into briefs that already contain your company, product, customer and funding stage. You fill one context form; every prompt substitutes those details into its placeholder slots and flags anything left blank so nothing reaches the model half-written. It is built for founders and operators at bootstrapped through Series A companies who want a structured brief rather than a blank chat box.
Open Founder Prompt Pack on AltFTool — it loads instantly in your browser.
Add your input to the workspace.
Adjust the options until the result looks right.
Copy or download the output and put it to work.
Company, product, customer and stage flow into every prompt in the pack automatically.
Unfilled placeholders are listed by name and shown as [field] so you can see the gap before pasting.
Each build reports characters, words and an approximate token count at roughly four characters per token.
Specific context and an explicit output structure. A prompt that names your stage, customer and the exact sections you want back removes the model's need to guess, which is why every prompt here carries your company details and a fixed deliverable format.
Any current general-purpose chat model handles them; they are plain text with no tool calls or system-prompt tricks. Longer prompts such as the pitch narrative and objection prep run to roughly 200-300 tokens of instruction, well inside every model's input limit.
No — treat every figure as a draft. The investor update prompt deliberately instructs the model to insert [TBC] rather than estimate a missing number, because a fabricated metric in an investor email is far more damaging than a gap.
Add a real situation in the context box. Prompts that include a concrete detail — a churn figure, a lost deal, a specific hire — produce concrete answers, while an empty context field leaves the model with nothing but the category to work from.