Pedro Silva

I'm a Fractional CTO and Technical Strategist.

I help companies adopt AI when they lack the technical leadership to do it well on their own.

I define the roadmap, and when needed, lead implementation directly or through a small team. Most engagements start with a technical review and grow from there. See my services.

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Writing

AGI Beefs
December 22, 2025
Every few months there's a new argument about AGI. We talk about "AGI timelines" like it's definitely coming, we just don't know when, while still arguing about what it even means. The latest: Demis Hassabis vs Yann LeCun.
LeCun says general intelligence is "complete BS" Human cognition is specialized for the physical world, and our feeling of generality is an illusion. We only seem general because we can't imagine what we're blind to. Hassabis disagrees. Brains are "approximate Turing Machines" capable of learning anything computable. We invented chess, mathematics, civilization.
I think they're both wrong. Not in a "truth is in the middle" way. They're having the wrong argument. Both treat intelligence as a function: something that takes inputs, produces outputs, gets measured on benchmarks, copied between substrates, scaled up. They disagree about whether this function is "general" or "specialized" but they agree on what kind of thing they're talking about. I think that's the mistake.
I get why the function frame is appealing:... [more]
Code Smells and Cameras
December 12, 2025
Most programmers will tell you about code smells. That ick you get from looking at messy, overly complex code. You can't always articulate why it's wrong, but you know something's off.
This intuition isn't unique to programming. Mathematicians talk about "elegant" proofs. Physicists get suspicious when equations get too complicated—simplicity is treated as weak evidence of truth. The whole lineage from Occam's razor to Kolmogorov complexity points at the same thing: compression and understanding are intimately related. If you truly grok a problem, you can express its solution minimally. Excess complexity signals excess confusion.
Which brings me to LLMs.
No doubt they've changed how I work. But they still generate code that smells. Not broken, just... bloated. Defensive boilerplate. Unnecessary abstractions. Cargo-culted idioms. Patterns that look like code because they were trained on code that looks like that.
Venkatesh Rao has this idea that LLMs are cameras, not engines. We think they're generating something, but they're actually photographing the statistical... [more]
On LLMs and Human Intelligence (2)
December 27, 2024
Thinking more about my earlier note on LLMs.
LLMs interpolate, they don't compose. They can't combine ideas into genuinely new structures because they have no mechanism for compositional reasoning, just proximity matching. Real composition might require consequences that happen to a continuous self, whereas LLMs rebuild from scratch each token. Humans can compose from sparse data.
Show a kid one lever, they'll start using sticks to flip things. LLMs need many examples to build a statistical manifold around "lever-ness." It's about composing from principles extracted from single experiences vs interpolating across massive experience-spaces. Just different kinds of cognition, not different points on the same scale.
AI tasks
December 18, 2024
Your periodic reminder: the big story isn't AI automating our jobs, it's AI revealing entirely new territories of thought, creativity, and opportunity
On LLMs and Human Intelligence
December 8, 2024
Someone recently tweeted about being in awe of LLMs while sensing they're missing something "ineffable yet essential" about general intelligence. I think maybe the fact that it's ineffable is a hint. That in fact there are no such things as general intelligences, and it's a whole slew of context-dependent, dynamic, embodied processes that emerge from continuous interaction between specific systems and their environments.
What irks us about LLMs is they're unreliable in a very inhuman way. When they fail, they violate our expectations of how minds work. We expect intelligence to come bundled with self-awareness, doubt, the ability to know what you don't know. LLMs show us intelligence decoupled from understanding, and that just doesn't feel right.
So I think it's a category error to compare human intelligence to LLMs, and asking "when will LLMs achieve human-level intelligence" is the wrong question. Maybe more interesting: what novel forms of cognition are these systems showing?
teamLab
November 28, 2023
Visited teamLab in Tokyo.
Made me think there's a whole lot to be explored in wonder/transcendence/psychedelic territory - especially for people not keen on diving into LSD or DMT.
The idea is to get a taste of "ecodelic insight" (see Richard Doyle's Darwin's Pharmacy), that moment when you get that you're not just an individual but a piece in a complex ecosystem.
Like a "grokking of Gaia", where you suddenly feel part of a much larger, interconnected life system.
May require a new approach to meaning, where you need to let go of the need to interpret and control and let the experience stand for nothing but itself (Leary's "non-symbolic patterns").
Efficiency in Germany vs Japan
October 28, 2023
Both Germany and Japan care about efficiency, but their approaches are shaped by different cultural backgrounds.
Japan: collectivist, values social harmony and consensus. Technology is adopted if it enhances collective well-being. The restrictive aspects come from a desire to maintain social cohesion.
Germany: individualistic, focus on precision engineering and planning. Less emphasis on collective consensus and more on functionality and standards.
Take the Shinkansen and Autobahn as metaphors:
Shinkansen: collective harmony through rigid protocols. There's a place and protocol for everything, and individual deviations aren't encouraged.
Autobahn: individual freedom within a framework of expertise and shared rules. Go as fast as you'd like on good roads, as long as you abide by the rules.
Misanthropes
August 28, 2022
As a collective, humanity has made itself healthier, safer, more equal, and more knowledgeable. We’ve built institutions that level the playing field. We’ve peeked into the microscopic world to make ourselves live longer, and we’ve peered beyond our blue dot and gasped at the weirdness of it all.
Our ability to understand and control the world has meant that, so far, we’ve steered away from the near-inevitable wave of rolling genocide that targets other species—ones that rely only on their genetic knowledge.
What we have achieved is only overshadowed by the possibilities of what we can do next. Yet there is a growing pessimism among some in our society. When faced with challenges like climate change, increased consumption in a world with limited resources, loss of biodiversity, or pollution, we jump to blaming ourselves and our way of life. If only we slowed down economic growth, limited air travel, and had fewer babies, everything would be fine.
The problem with this line of reasoning is that it achieves very little. We will always be faced with the question of how to plan for an unknowable future. We will never be able to afford to sit back and hope for... [more]
The Social Dilemma
April 12, 2021
I thought Netflix's The Social Dilemma was bad.
It portrays people as helpless automata under control of the algorithm, and massively overplays the influence of these tools. It is a manipulative horror film wrapped in the appearance of a serious documentary, using the same techniques in filmmaking that it calls evil.
By all means these are relevant warnings, and how to best balance information consumption with other aspects of life is important. But none of this is new or unique to social media.
We will never live in hermetically sealed bubbles where our information diet is exactly what the doctor ordered. The world is messy and takes critical thinking to navigate. Tech isn't the devil and it isn't the saviour either.
Fearmongering is counterproductive.

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