AI Stack for Pre-Seed Founders

One vertical tool for your highest-leverage workflow — $0-50/mo

Pick the one workflow you do 10+ times a week. Get the best vertical AI tool for that. Examples:

• Content / SEO: a writing tool that knows your brand voice.
• Sales: a prospecting tool that pulls signal from intent data.
• Support: an AI inbox that drafts replies from your knowledge base.

Don't subscribe to verticals for workflows you do twice a month.

Wait until seed

Multi-tenant inference platforms

Until you have ≥1k paying users and a fine-tuning need that's blocked by the model provider's APIs, dedicated inference is overkill. The latency / cost economics rarely beat off-the-shelf for low-volume early use.

Custom model hosting

You don't need a fine-tuned model for product features yet. The frontier base models are good enough for 95% of use cases. The 5% where you genuinely need fine-tuning is rarely the first 12 months.

Voice agent infrastructure

The cost-per-minute economics still don't work for most pre-seed companies. Either you're a voice-AI startup (in which case you're the platform, not the customer), or you can wait 12 months for the price to halve again.

Vector databases

Use the model provider's built-in retrieval (OpenAI file search, Anthropic Files API) until you hit the 5,000-document or 100MB ceiling. A managed vector DB is 4 hours of setup and an extra service to monitor — you don't need that complexity at pre-seed.

Workflow / agent orchestration platforms

For most workflows, a 50-line script and a cron job beats an orchestration platform. Add an agent framework when you have 5+ workflows that share infrastructure, not before.

How to evaluate any AI subscription

Three filters, in order:

1. Time saved per week × your hourly cost > monthly subscription × 2. The 2x is your hurdle rate; AI tools have switching costs that aren't on the receipt.
2. Does the workflow already exist? If you're not already doing the task manually, an AI tool to do it faster is a fake productivity gain — you're just spending faster on the thing you weren't going to do.
3. Can you cancel after 60 days without losing data or workflow? If not, the lock-in cost is hidden. Avoid until you're certain.

If a tool doesn't pass all three, cancel after the trial.

Three traps to avoid

Trap 1: AI sprawl

Stacking subscriptions creates context in 7 places, expertise in none. Pick one primary model. Make it the spine. Everything else is supplementary.

Trap 2: Treating AI output as final draft

Reviewing AI output well takes 50-80% of the time it would take to do the work yourself. The actual productivity gain is in the first-draft step. If you can't critically review the domain (legal, medical, financial), don't ship AI-generated work in that domain. Hire a human for the review.

Trap 3: Buying the hype tool of the month

Every two weeks a new AI tool trends. Most don't survive 6 months. Wait 90 days before adopting anything that became famous in a launch tweet. The signal will get clearer.

What the stack looks like by stage

Solo founder, pre-MVP: 1 frontier model + 1 code assistant. ~$60/mo.

2-3 person team, MVP shipped: + transcription, + one vertical tool. ~$150-200/mo.

3-5 person team, first 10 customers: + a second model for diversity (different strengths), + a low-end paid tier on prospecting or support. ~$300-450/mo.

5+ people, post-seed: workflow platform makes sense, custom hosting if usage justifies. ~$1k+/mo, but each line has a job.

What to cancel today

Open your subscriptions. For each AI tool:

• When did you last use it? If >14 days, cancel.
• Did the last use save you 1+ hour vs the alternative? If no, cancel.
• Could you achieve 80% of the value with your spine model + a custom prompt? If yes, cancel.

Most pre-seed founders cut 30-40% of their AI spend with this exercise. The remaining budget goes further when there's less to manage.