Ehsan Jahandarpour
AI Growth Stack Model (AGSM)

AI Growth Stack Model (AGSM): AGSM for Tool Category Comparison

Using AGSM layer placement as a key comparison dimension when evaluating competing AI tools in the same category.

How to Apply

1

Which AGSM layer does this tool category belong to? This determines what dependencies the tool has.

2

Score your current readiness in the layer below. If it scores below 7, investing in this layer is premature.

3

Among competing tools, evaluate which integrates best with your existing tools in adjacent layers.

4

The best tool is the one that both consumes data from the layer below and feeds data to the layer above most cleanly.

Expected Outcomes

  • ✓ Tool selection based on stack architecture, not feature lists
  • ✓ Better integration outcomes
  • ✓ Reduced stack fragmentation

Real-World Examples

Common Pitfalls

⚠Choosing the tool with the most features regardless of stack fit
⚠Ignoring the integration quality with adjacent layers

Ehsan's Insight

Feature comparison tables are the worst way to evaluate AI tools. I have seen teams spend weeks building elaborate spreadsheets comparing 47 features across 5 vendors. They pick the tool with the most green checkmarks. Six months later, the tool is shelfware. The AGSM approach is different: forget the features. Ask three questions. First, which layer does this tool belong to? Second, how well does it consume data from the layer below? Third, how well does it feed data to the layer above? A tool that scores 10/10 on features but 3/10 on layer integration will underperform a tool that scores 7/10 on features but 9/10 on integration. Every time. I have never seen an exception in 50+ stack evaluations.

EJ

Ehsan Jahandarpour

AI Growth Strategist & Fractional CMO

Forbes Top 20 Growth Hacker · TEDx Speaker · 716 Academic Citations · Ex-Microsoft · CMO at FirstWave (ASX:FCT) · Forbes Communications Council

Frequently Asked Questions

When should I use AI Growth Stack Model (AGSM) for tool evaluation?
Using AGSM layer placement as a key comparison dimension when evaluating competing AI tools in the same category.
What are the steps in AGSM for Tool Category Comparison?
There are 4 key steps: Determine the layer, Check layer readiness, Compare integration depth, Score cross-layer data flow.
What results can I expect from AGSM for Tool Category Comparison?
Tool selection based on stack architecture, not feature lists. Better integration outcomes. Reduced stack fragmentation.
What are common mistakes with AGSM for Tool Category Comparison?
Choosing the tool with the most features regardless of stack fit. Ignoring the integration quality with adjacent layers.