🚀 How to work with design partners

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3 tactics to work with design partners

🔎 Select for these 3 qualities

• Representative:

  • Target partners whose workflows, systems, data and pain points mirror your ideal customer profile

  • Avoid overfitting to outliers or extreme early adopters

  • Include partners from both cold and warm intros

  • Run 10–30 discovery calls for every design partner to prevent bias

• Urgency:

  • Choose partners feeling pain and having a real need now—those actively seeking a solution and evaluating alternatives or using temporary fixes internally

  • Focus on segments that move fast: hit the hardest by a technology transition or the legacy solution has key limitations; 

  • Avoid larger enterprises that require many approvals for implementation and early-stage startups with frequent requirements shift

• Capacity:

  • Partners must be willing to experiment and inform you about implementation details and buying decisions

  • Has technical fit: right data, systems, and software stack to implement the product

  • Has personnel fit: an internal champion with authority to influence adoption and time to give regular feedback

👂 Structure for real feedback

• Secure double buy-in from both the buyer (decision-maker) and the actual user

• Time-box the partnership (8–12 weeks, up to 6 months) and demand real commitment—if a partner won’t pay in dollars at the start, they must pay in time and effort (e.g. weekly check-ins, pulling in live workflows and data, unfiltered feedback, thoughtful introductions to other potential partners)

• Optimize for having recurring feedback on product iterations by asking:

  • How well does the product work? 

  • How does it interact with their existing workflow and tools? 

  • What are the potential hurdles to get it set up? 

  • Does the MVP match your expectations for what was promised? 

• Focus on identifying a repeatable wedge workflow (that naturally progresses towards a system of record) and early wins from baseline metrics (e.g. measurable time savings, improved accuracy, revenue life)

💰 Prove willingness to pay

• Replace some of the time investment from design partners with money to validate if the wedge case is a real pain worth paying for 

• Keep custom asks limited

• Calculate ROI from baseline metrics and structure pricing to reflect long-term model (e.g. per workflow, per case, or hybrid models like minimum + usage tied to business outcomes); If unclear, start with a nominal platform fee to test seriousness

2 traps to avoid

🚨 Focusing on pricing too early with design partners

• Focus on receiving feedback, discovering repeatable pain points, and understanding how value is perceived, instead of optimizing for a perfect pricing and contract value

• If design partner contract already has a dollar value -> upgrade it into a proper sales contract

• If design partner did not pay to use your product -> explore their willingness to pay

🚨 Selling technical expertise instead of product value

• Design partners may value founders’ technical skill set more than the product itself, and pay to retain that expertise

• Scaling becomes a challenge when adoption depends on founder expertise, not product value

• Continuous hands-on consulting may hide product gaps and block discovery of missing features

1 tool to leverage

📖 Best practice on working with design partners

• Start with 5-10 high quality design partners even if inbound interest is high; convert the rest into early customers once the product is market-ready

• More design partners = more conversations, expectations, and coordination headaches

• Use this design partner agreement template by Jake Stein, Co-founder and CEO of Common Paper, to start working closely with your first few early believers.

Bonus: 1 trend to spark startup ideas

📈  Construction is burning billions on manual processes

• The $1.8T US construction market spends just $1.8B on AI

• Construction productivity improved by only 0.4% annually between 2000 and 2022, compared to a 2% annually for the total economy and 3% percent annually for the manufacturing sector

• Workers waste 20% of time hunting for data and projects routinely run over budget because of fragmented workflows, manual scheduling, and reactive problem-solving that catches issues only after they become expensive

• Further, 41% of the US construction workforce will retire by 2031, creating labor shortages and urgent demand for automation

• Three breakthrough opportunities:

  • Automated project planning: AI analyzes historical data to create realistic schedules and predict delays, replacing manual planning that misses bottlenecks

  • Real-time progress monitoring: Computer vision compares actual construction against models, catching deviations instantly instead of weeks later during inspections

  • Predictive equipment maintenance: ML algorithms analyze sensor data to prevent breakdowns, reducing equipment downtime