Tomasz Tunguz
Venture capitalist and founder of Theory Ventures, previously a partner at Redpoint. Writes a near-daily blog on startups, SaaS metrics, data and AI.
Tomasz Tunguz did not write this page.
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Their wordsThird, limitations in compute availability will encourage algorithmic innovation.
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Their wordsThere will consistently be an active ceiling on energized compute, which will keep structural upward pressure on GPU prices per hour.
- 1 day earlier
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Their wordsWith 40% to 50% of data center projects delayed3 & billions of dollars of GPUs sitting idle in warehouses waiting for power4, plus transformer & turbine lead times measured in years5, this supply pressure shows no sign of easing in the near term.
↗The Financial Engineering Essential for AI in 2027tomtunguz.com
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Their wordsIn 2027, the winners will be the labs that match the duration of their customers’ contracts to the duration of their compute.
↗The Financial Engineering Essential for AI in 2027tomtunguz.com
- 1 day earlier
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Their wordsRecursive self-improvement, AI models training better AI, has not yet bailed out the big labs.
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Our reading
The AI stack functions as a coupled, chaotic system where changes in one layer affect the others.
Their wordsLike a double pendulum20, the four layers form a coupled system : simple in each part, yet complex, chaotic, & unpredictable in motion.
- 4 days earlier
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Their wordsThe first $10t company will be the one that crosses the trillion dollar chasm before AI erodes its legacy profit pool. Who will be the first $10t company? The one that first crosses the trillion dollar chasm : building a $1t AI compute engine before AI erodes the legacy cash cow paying for the GPUs.
- 3 days earlier
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Their wordsAnthropic’s S-1 describes an AI company with an enviable business model, explosive growth, & increasing efficiency.
↗Anthropic S-1 Analysis: How 7 Key Metrics Stack Uptomtunguz.com
- 5 days earlier
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Their wordsOverall, they demonstrate that inference businesses can be quite healthy even at current prices & efficiencies.
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Their wordsThe economics of large scale inference suggest the business model is healthy at scale, & token factories benefit from more rungs to climb on the pricing ladder.
- 3 days earlier
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Their wordsAnthropic is considered an AI company, but it should be valued as a cloud.
- 5 days earlier
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Their wordsOverall, it is clear how quickly the ecosystem is evolving, & how much sophistication has permeated the enterprise, more quickly than any wave we have seen.
- 6 days earlier
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Their wordsIn a commoditizing market, the spoils do not accrue to the lab with a marginal benchmark lead, but to the platform that aggregates the volume.
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Our reading
Their wordsAI models have reached commodity status as prices fall 41% while token usage surges 50%.
- 2 days earlier
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Their wordsAI inference is set to surpass the database market to become the most important market in software, reaching ~$350b by 2027.
↗Inference Is the Most Important Market in Softwaretomtunguz.com
- 11 days earlier
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Their wordsSoftware engineering have evolved to systems architecture. That was always the destination. This is the new software engineering : designing the systems that let AI write code correctly at scale.
- 1 day earlier
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Their wordsMost business AI use is the messy middle: multi-step workflows that need a smart enough model at a price a company can afford. It is the most important part of the market today, & it is where the competition is fiercest.
- 6 days earlier
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Their wordsRouting to a cheap model is only safe if you know which tasks it clears, & that knowledge comes from watching ten thousand versions of the same work.
↗The Harness Margin Opportunitytomtunguz.com 1st of 2 in this piece
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LLMsmarket efficiencyAI agents
Their wordsMargins will not climb to 100%. As inference gets cheaper, buyers will ask more of their agents, shifting the equilibrium over time in response to competition.
↗The Harness Margin Opportunitytomtunguz.com 2nd of 2 in this piece
- 2 days earlier
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Our reading
What limits AI automating a workflow is how well the workflow is codified, not the underlying model
Their wordsThe bottleneck is not the model, it is the codified workflow.
↗When Inbound Sells Itselftomtunguz.com 1st of 2 in this piece
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Their wordsToday, AI is in a place where the original promises have now been kept.
↗When Inbound Sells Itselftomtunguz.com 2nd of 2 in this piece