★ Earlier predictions
Calls from our earlier write-ups
163 predictions we pulled from our own summaries. The wording here is our paraphrase, not the speaker's exact words, and most have no deadline we checked. For calls in the speaker's own words, with a deadline and a link to the moment, see the Predictions Board.
- Whatnot's Gross Merchandise Volume (GMV) will reach 16 billion dollars this year.On 20VC with Harry Stebbings · by end of 2026 · source ↗
- Google will sell over 20% of its total TPU shipments between Q3 2026 and Q4 2027 to competitors such as Anthropic.On TBPN · by end of Q4 2027 · source ↗
- AirTable could generate $300 million in free cash flow within two years.On 20VC with Harry Stebbings · within 2 years · source ↗
- There will be a rapid shift towards agent-native identity, where agents will use specific 'personas' with segmented access.On Latent Space · within a few years (e.g., by 2029) · source ↗
- AI agents will transform mechanistic interpretability (mechan) from an ad hoc process into a true science by automating hypothesis testing.On Latent Space · within 5 years · source ↗
- Coding agents will enable the routine generation of highly secure code that would be too complex or tedious for human engineers.On Latent Space · within 5 years · source ↗
- There will be sustained inflationary pressures on AI hardware and services.On All-In Podcast · over the next 2-3 years (from 2026) · source ↗
- Companies that move fast and break things with AI infrastructure without community buy-in will invite future scrutiny and regulatory hurdles.On Latent Space · in the future · source ↗
- The primary engineering task for AI products will shift to removing complexity to improve user experience.On How I AI · within 3 years · source ↗
- Continuous Integration (CI) will become a strategic investment for velocity in AI product development.On How I AI · within 3 years · source ↗
- The AI product development cycle will become a constant loop of refining evaluations.On How I AI · within 3 years · source ↗
- Engineers who offload tasks below the agent line will consistently enter a 'maker schedule'.On How I AI · Once engineers offload tasks below the agent line using AI. · source ↗
- It will become significantly harder for US AI companies, including ambitious startups, to recruit and retain the highest-quality international talent.On TBPN · within 2 years · source ↗
- An AI oligopoly will form, dominated by hyperscalers (Amazon, Microsoft, Google) acting as trusted, regulated gatekeepers.On All-In Podcast · by end of 2031 · source ↗
- AI CEOs' public 'doom trolling' will inadvertently cause increased government intervention, leading to centralized control of AI by larger entities.On All-In Podcast · by end of 2031 · source ↗
- Future market leaders in semiconductors will not win by being generalists.On No Priors · by 2030 · source ↗
- Future market leaders in semiconductors will hyper-focus on one niche area, forge smart strategic partnerships, and deliver complete, full-stack solutions, from hardware to software.On No Priors · by 2030 · source ↗
- Intel will transform into an organization where AI is embedded across design, engineering, and every part of the business.On No Priors · by 2028 · source ↗
- By 2030-2032, people will begin to understand the significant product potential of Intel.On No Priors · By 2032 · source ↗
- Micron, a supplier of high-bandwidth memory (HBM), will become more valuable than Meta.On 20VC with Harry Stebbings · within 2 years · source ↗
- The AI infrastructure boom will undergo a massive, sustained expansion.On 20VC with Harry Stebbings · within the next 3-5 years · source ↗
- Enterprises will require ten times more data storage within the next three years.On All-In Podcast · by 2029-06-14 · source ↗
- Google will spend a billion dollars a month with XAI.On My First Million · monthly, ongoing from Q3 2026 · source ↗
- SpaceX will build data centers in space.On My First Million · in the future, as part of their space compute vision · source ↗
- Starship will achieve unprecedented rapid reusability.On My First Million · in the future, enabling the space compute vision · source ↗
- Anthropic's strict guardrails will stifle innovation.On TBPN · within 3 years · source ↗
- OpenAI and Anthropic's combined compute capacity is projected to reach 10 gigawatts by the end of 2026 and 20 gigawatts by the end of 2027.On TBPN · by end of 2026 and by end of 2027 · source ↗
- A tiny incremental cost will transform multi-billion dollar facilities, such as data centers, into welcome community assets.On My First Million · within 5 years · source ↗
- AI's next frontier will be in the physical world, encompassing robotics, manufacturing, and industrialization.On Lenny's Podcast · short to medium term · source ↗
- The shift of AI into the physical world will lead to unprecedented demand for physical components.On Lenny's Podcast · as the shift of AI into the physical world occurs · source ↗
- Memory prices for consumer hardware, robotics, and physical AI will significantly increase.On Lenny's Podcast · within the next 1-3 years · source ↗
- Early advancements in AI for CAD will more probably come from hobbyists or on-premise AI training systems than from large, established incumbents.On Lenny's Podcast · within 5 years · source ↗
- An LLM inference system operating without batching user requests will incur a per-token cost that is approximately one thousand times higher than an optimized system that utilizes batching.On Dwarkesh Podcast · Indefinite · source ↗
- Any future LLM service that experiences only a few sporadic user requests will inherently operate at smaller batch sizes, necessitating a sacrifice of cost efficiency for instant response.On Dwarkesh Podcast · Indefinite · source ↗
- Pipelining will dramatically reduce the memory capacity needed per rack for storing model weights.On Dwarkesh Podcast · within 1 year · source ↗
- Pipelining will not significantly reduce the memory footprint for the KV (Key-Value) cache.On Dwarkesh Podcast · within 1 year · source ↗