Market size is often presented as the main reason a startup can succeed. In early-stage evaluation, timing frequently matters more. A large market does not help if adoption is not plausible now. How evaluators think about timing What changed recently that makes adoption possible? Why will users switch now instead of later? Are enabling conditions […]

Founder misalignment is one of the highest-risk patterns evaluators look for. It often appears as inconsistency: different answers, different priorities, or unclear ownership of responsibilities. Common misalignment signals cofounders describe the problem differently cofounders disagree on the target user ownership of key workstreams is unclear priorities change depending on who is speaking Why it matters […]

At the earliest stage, metrics are often unstable or misleading. Qualitative signals can reduce uncertainty earlier because they show what users do, why they do it, and what changes when your solution exists. Examples of useful qualitative signals clear patterns from user interviews documented experiments and outcomes consistent user pain and willingness to adopt What […]

Traction at the earliest stage is rarely revenue or scale. Evaluators often look for evidence that the team is learning quickly and moving toward validated behavior. Early traction is often qualitative consistent user conversations with clear insights repeated patterns in feedback pilot commitments or active usage in a small group Why traction is stage-dependent What […]

Application questions often look straightforward, but they are usually proxies for deeper evaluation dimensions. Understanding what is being tested helps founders answer more effectively. Common question types and what they test Problem: clarity and specificity of pain and user. Solution: coherence and feasibility at the current stage. Market: awareness of alternatives and adoption constraints. Team: […]

Founders often view application forms as a formality. For reviewers, forms are an efficient way to filter startups before spending time on calls or interviews. What forms make easy to assess clarity of the problem and user stage fit and eligibility coherence of the team basic learning and progress signals Why clarity dominates at this […]

Accelerators reject many startups that could succeed. This is not always a statement about quality. It is often a consequence of capacity limits, cohort design, and fit constraints. Common reasons strong startups are rejected Stage mismatch: too early or too late for the cohort. Fit mismatch: misalignment with the program thesis. Clarity issues: reviewers cannot […]

Selection committees are where many accelerator decisions are finalized. While each program differs, committees tend to follow similar patterns: they compare startups under constraints and optimize for cohort composition and fit. What committees do in practice review notes from screeners and interviews resolve disagreements and uncertainty rank startups relative to each other balance the cohort […]

In many programs and organizations, a startup is reviewed by more than one person. This changes how evaluation works, because consistency becomes a core requirement. Why multiple reviewers are used to reduce individual bias to scale review volume to compare perspectives across domains What happens when reviewers disagree Disagreement often comes from different interpretations of […]

Founders often expect programs and investors to publish clear evaluation criteria. In practice, criteria are frequently implicit, partially defined, or applied differently depending on stage and context. Why criteria stay implicit Context changes: what matters depends on stage, cohort, and constraints. Comparative decisions: criteria evolve as reviewers compare startups. Operational limits: formal criteria can slow […]