Researched Jun 2026 · 9 signals across 1 source
Software 3.0 Paradigm Framing
Karpathy's 'Software 3.0' vocabulary — LLMs programmed via prompts/context/tools, jagged intelligence, agentic engineering — entering builder mental models after Sequoia AI Ascent 2026.
Evidence strength
Calculated from how many high-quality signals exist for this trend across our 8 sources, weighted for recency and independence. A trend crossing 6.0 means enough evidence to take seriously. Above 60 is exceptional.
Source diversity
Probability that multiple independent platforms are seeing the same trend, not just one loud voice. A single source can be wrong; many sources agreeing reduces that risk.
Momentum
New signals arriving at a stable pace. The trend isn't cooling or spiking — it's solidifying.
Reasons this matters now
Our Why-Now rubric checks five things: a fresh catalyst, a primary source, a recent timing window, quantitative evidence, and multiple converging forces. The more present, the stronger the case for acting now.
Signal velocity over 90 days
How frequently new evidence has arrived for this trend.
Why now
The structural shifts our pipeline anchored this trend on.
- Platform shiftApr 2026
Karpathy's April 30, 2026 Sequoia AI Ascent talk publicly named and canonized the 'Software 3.0' paradigm — LLMs programmed via prompts/context/tools — giving builders a shared vocabulary for a shift they had experienced but not yet named. The three-generation framing (1.0/2.0/3.0) is spreading rapidly into pitch decks and hiring language.
Source - Capability unlockApr 2026
Sequoia AI Ascent 2026 documented that the three required ingredients for production-grade agent deployment — models, tools, and agentic harnesses — have finally converged, closing the last barrier that kept agentic engineering experimental.
Source
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Get notifiedHow we found this trend
Every trend on this page survives a four-step automated pipeline before we'll publish it. No hot takes, no "feels right" — only signals you can audit.
- Signal sources
- 20
- Signals analysed
- 10,023
- Trends tracked
- 95
- AI review
- ~39 min
The pipeline
- 1Fetch
Daily pull from 8+ sources
- 2Cluster
Semantic dedup into trend groups
- 3Score
Composite eligibility (CES)
- 4Why-Now
Enabler & cost-curve check
- 5Validate
Multi-step demand analysis
Where the signals come from
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