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Friday, October 16, 2026· 7456 stock ideas· 217 writers·
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Convequity on X

3D chips could create more room for specialist EDA startups. We are not convinced that more difficult chip design automatically translates into a large revenue windfall for $SNPS, $CDNS and Siemens. Fine-pitch stacking changes decisions that used to be made within one die. Put a circuit upstairs and its wires may get shorter, but its heat affects the circuit below. Placement, signal timing and power delivery have to be optimized together across the stack. That creates a reason for $AVGO and $NVDA to build custom tools around their architectures. Broadcom already describes a proprietary design flow built on industry-standard tools. Nvidia publishes its own research on assigning connections across tiers in 3D chips. Our inference is that the chip designers will keep some of the most differentiating optimization work in-house. A startup that solves a costly gap in cross-die planning or optimization could also win business without replacing an entire EDA suite. The incumbents still supply implementation, verification and manufacturing sign-off tools, and they are developing 3D capabilities themselves. Internal tooling is evidence that customers need more than the standard flow; it does not establish that incumbent spending falls. We see a more interesting startup opportunity where a tool can shorten repeated design iterations or improve the resulting chip enough to earn a separate budget. That is the part of the 3D transition we would investigate before assuming the largest EDA vendors capture most of the upside.
@convequity

Convequity on X

We think $MNDY needs to make its platform verifiable to lead work management. MNDY has not disclosed its AI ARR in dollars. Our recent SaaS Survival Scorecard report estimates it at about $20 to $30 million as of the end of Q2 2026. Leading AI-native startups in other fields are far larger. In coding, Cognition reported crossing $1 billion in annualized revenue run rate on 25 September 2026, company-wide across Devin and Windsurf. In legal work, Harvey reported on 1 October 2026 that it crossed $400 million in ARR during Q3 2026. We think MNDY has long been highly adaptive, with great leadership and a strong recent cadence of features and products. But revenue growth has slowed, and in our view it has gained little from AI so far, because work management is a hard area for AI. In our view, coding agents suddenly became highly effective around early 2026, and work management has not yet had its own coding moment. Verifiability is the key difference: code can be tested, while most work management outcomes are hard to check. Rather than wait for that moment, how can MNDY make work management more verifiable? It could track and measure the actions taken on its platform and their outcomes, so that everything that happens there is verifiable. MNDY can learn from Palantir. Palantir launched AIP in 2023, its AI platform built on its ontology, and we think that ontology helped Palantir succeed with models much weaker than today's. Could MNDY build a similar substrate or ontology for work management in order to make the work done on its platform more verifiable? We do not claim to have the answer. Our view is that to thrive, and not only survive, MNDY needs to lead work management by making its platform verifiable, however it chooses to do that.

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