You’ve read the diagnosis. Now the prescription.

If you run — or are scaling — an AI-native, gaming-enabled, ad-tech or SaaS startup, the biggest operating risk isn’t product-market fit. It’s talent-market fit: selecting and shaping people who can build the future rather than repackage the present.

Here are practical, tactical rules I use at Blowtrumpet.

1. Treat hiring like product discovery

Don’t hire to fill a job description. Hire to discover whether someone can own a measurable outcome. Use an experiment framework:

• Hypothesis: Candidate X can ship feature Y in 6 weeks that increases retention by Z%.
• Experiment: 4-week paid apprenticeship with clear KPI and mentorship.
• Decision: Hire full-time, extend, or decline based on metric outcomes.

This both reduces bad hires and lets you evaluate real capability.

2. Use artifacts as primary signals

Ask applicants to submit:

• A one-page case study of a project they personally shipped (metrics preferred).
• A short “what I would build for Blowtrumpet” brief (500 words + 3 visuals or links).
• Links to real artifacts — functioning demos, prototypes, or repos.

These show whether the candidate can finish, measure, and iterate.

3. Evaluate reading and reasoning, not just skill lists

Ask questions such as:

• What three books or essays shaped your thinking in the last year?
• Explain Moore’s Law in your words; what does it mean for our product in five years?
• Given a sudden budget cut, how would you prioritize product features?

These questions test habits of mind, not memorized buzzwords.

4. Value on-site presence for early-stage building

Remote works for scale, but early-stage learning is amplified in person. On-site mentorship accelerates:

• Tacit knowledge transfer
• Quick iterations and hallway design critiques
• Cultural alignment

Make on-site a temporary but non-negotiable condition for apprenticeships. That weeds out those who want optics over growth.

5. Build structured, public apprenticeship programs

Design a short, paid apprenticeship where the candidate:

• Joins on-site 5–6 days/week for 4–8 weeks
• Is assigned a concrete, measurable deliverable
• Receives daily mentorship and weekly reviews
• Is evaluated on outputs and learning curves, not presence alone

This creates a robust funnel: the best convert to full-time; others leave with experience and goodwill.

6. Measure what matters

Track candidate performance on:

• Speed of iteration (cycle time to next version)
• Learning velocity (ability to incorporate feedback)
• Outcome impact (conversion, retention, output quality)
• Collaboration (clear communication, documentation, cross-team sync)

Use these metrics rather than interview charisma.

7. Make ESOPs meaningful and teach value

Early hires must understand what equity is — how Black-Scholes valuations, dilution, vesting, and liquidity events work. If someone demands FAANG cash immediately, they may be misaligned with the early risk/return structure. Teach them the trade-offs; reward them for demonstrable impact.

8. Don’t over-index on credentials — but don’t ignore them

Tier-1 design or engineering degrees matter insofar as they correlate with disciplined thinking and training. But the best signal is what the candidate built since graduation. Use credentials as a filter, not as a gate.

9. Look for “product empathy” and systems thinking

A designer or engineer who can’t explain how their work affects metrics or user behavior is incomplete for an AI × AdTech business. Prioritize systems thinkers.

10. Build a culture of public learning

Run internal retros, post-mortems, and public presentations. Invite candidates to attend a “show your work” day. Those who sit quietly and absorb will often make faster leaps in capability than those who only perform.

Screening Checklist for Candidate Triage (Quick)

1. Artifact? — Yes / No
2. Can explain product impact? — Yes / No
3. Written brief for company? — Yes / No
4. Willing to do on-site apprenticeship? — Yes / No
5. Mentorship experience? — Yes / No
6. Measured outcomes on past work? — Yes / No

Pass if 4/6 positive, with artifact & on-site being mandatory.

Final thought: build a talent machine, not a hiring funnel

In an age of noise, your company’s competitive moat will be your ability to find, train, and retain the rare few — people who will not only ship but invent. That talent pool will determine who wins the next decade of AI-native product markets.

If you’re a founder: design hiring experiments as product sprints.
If you’re hiring managers: insist on artifacts and short paid apprenticeships.
If you’re a candidate: bring something that works, not just a resume.

We cannot afford more performative work disguised as growth. We must invest in learning structures that reveal real makers — the builders who will transform tools into systems, and systems into new industries.

Call to action (for founders & hiring teams)

If you want a template I use at Blowtrumpet — apprenticeship brief, interview prompts, artifact scoring matrix, and a six-week on-site sprint plan — tell me and I’ll draft it next. If you’re a candidate and you’re serious about building rather than broadcasting, send an artifact and a short brief: show me what you’ve built and what you can build with us.