Big Tech Innovation Stagnation

Arguments that Meta, Google, and other large tech companies haven't truly innovated in years, relying on monopoly positions and acquisitions. Discussion of how internal processes, performance reviews, and organizational bloat prevent meaningful new product development.

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Meta and Google both are companies that got lucky and managed to carve out a quasi-Monopoly in their space. Sure, they did a lot of things right at first and provided a popular product, but for the past years/decades they've been using their money to buy other companies, adding a veneer of "innovation" to their image, constantly coming up with "cool stuff" that they're unable to market successfully, but ultimately they're just milking their insanely profitable core product they came up with 20 or so years ago, like any legacy corp. I have no respect for either of those companies having to work with them in my day job, knowing how lazy and incompetent they are with the services that actually make them money.
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Meta and Google both are companies that got lucky and managed to carve out a quasi-Monopoly in their space. Sure, they did a lot of things right at first and provided a popular product, but for the past years/decades they've been using their money to buy other companies, adding a veneer of "innovation" to their image, constantly coming up with "cool stuff" that they're unable to market successfully, but ultimately they're just milking their insanely profitable core product they came up with 20 or so years ago, like any legacy corp. I have no respect for either of those companies having to work with them in my day job, knowing how lazy and incompetent they are with the services that actually make them money.
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Google has bad governance, same with many other big businesses in the tech related sector partially because of the extremely generous position founders were in during the 00s and interest rates. In industries with lower margins like chemical/material industry you don't get away with this because managers in these industries are way better at telling value from non-value. There's been activist investors ( e.g. Christopher Hohn) who tried getting Google to run a tighter ship but with the dual stock setup there's not much which can be done.
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Google has bad governance, same with many other big businesses in the tech related sector partially because of the extremely generous position founders were in during the 00s and interest rates. In industries with lower margins like chemical/material industry you don't get away with this because managers in these industries are way better at telling value from non-value. There's been activist investors ( e.g. Christopher Hohn) who tried getting Google to run a tighter ship but with the dual stock setup there's not much which can be done.
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I had a similar experience at Google, they were so convinced they were the only good engineering company in the world and had to protect themselves from all the wrong-thinkers outside and yet the only progress they made was via acquisitions.
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Good engineering isn't always about building new things, but making existing ones continue to work well. Funding new ideas is generally a hard problem for large organizations and that's not entirely an engineering culture problem. There are a lot of terrible practices out there in the world that you should stay wary of. Too many false positive alerts, flakey tests, not enough tests, not listening to users, taking a solution because it's easy and popular but not necessarily a good fit for your specific requirements, etc. Many of these practices are popular unfortunately. That's not to say others don't have great ideas, just don't copy them blindly.
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Good engineering isn't always about building new things, but making existing ones continue to work well. Funding new ideas is generally a hard problem for large organizations and that's not entirely an engineering culture problem. There are a lot of terrible practices out there in the world that you should stay wary of. Too many false positive alerts, flakey tests, not enough tests, not listening to users, taking a solution because it's easy and popular but not necessarily a good fit for your specific requirements, etc. Many of these practices are popular unfortunately. That's not to say others don't have great ideas, just don't copy them blindly.
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Having led engineering in SF big tech and now building my own startup, I’ve heard this exact argument countless times. I believe it is precisely why large tech companies are losing their ability to innovate. Engineering shouldn't be an academic pursuit of "good engineering" for its own sake. It is fundamentally a business function. The objective is to achieve real world goals and build things people actually want, even if that means the solution is scrappy and unpolished today, so long as it solves an important problem cheaply and effectively. In large organizations, accountability for actual value delivery is so diluted across the org chart that it practically disappears. Leaders gravitate toward building bloated "internal platforms" that offer little external utility. Engineers over-engineer simple problems because their performance reviews reward technical complexity, not business impact. It becomes a systemic shield, allowing the old guard to justify their headcount without delivering new value. Software engineering is uniquely plagued by this. Civil engineers understand their objective: build a bridge that safely carries traffic within a specific budget. They don't invent a novel, hyper-complex suspension architecture when a standard short-span bridge will do the job.
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Having led engineering in SF big tech and now building my own startup, I’ve heard this exact argument countless times. I believe it is precisely why large tech companies are losing their ability to innovate. Engineering shouldn't be an academic pursuit of "good engineering" for its own sake. It is fundamentally a business function. The objective is to achieve real world goals and build things people actually want, even if that means the solution is scrappy and unpolished today, so long as it solves an important problem cheaply and effectively. In large organizations, accountability for actual value delivery is so diluted across the org chart that it practically disappears. Leaders gravitate toward building bloated "internal platforms" that offer little external utility. Engineers over-engineer simple problems because their performance reviews reward technical complexity, not business impact. It becomes a systemic shield, allowing the old guard to justify their headcount without delivering new value. Software engineering is uniquely plagued by this. Civil engineers understand their objective: build a bridge that safely carries traffic within a specific budget. They don't invent a novel, hyper-complex suspension architecture when a standard short-span bridge will do the job.
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Considering the large increases in revenues bug tech extracts year over year, the maintenance and small improvements are not necessarily completely disregarding the business side of things. You cannot keep sustained performance without proper practices. Too much short term thinking like you see in startups leads to loss of confidence that new changes won't break existing customers, or hellish on call that no one wants to be part of. There is a lifecycle to product development and different phases require different tradeoffs. You sound like you align with the builder phase and that's great. I will also note that most civil engineering is about maintaining existing structures and roadways, not building new ones.
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Considering the large increases in revenues bug tech extracts year over year, the maintenance and small improvements are not necessarily completely disregarding the business side of things. You cannot keep sustained performance without proper practices. Too much short term thinking like you see in startups leads to loss of confidence that new changes won't break existing customers, or hellish on call that no one wants to be part of. There is a lifecycle to product development and different phases require different tradeoffs. You sound like you align with the builder phase and that's great. I will also note that most civil engineering is about maintaining existing structures and roadways, not building new ones.
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Dremel/big query Spanner Borg Chrome None of those were acquisitions
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Waymo too
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V8 that backs Chrome and NodeJS
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These things can accumulate and ruin lives. I'm surprised that there haven't been more class action lawsuits against "errors" like these. Because it might seem like a benign accident -- but how many people have lost important parts of their lives – banking, photos of their children and more – because "computer says no?" Eventually, these systems will be mostly artificially generated, and perhaps the machines will have fewer error rates than the humans. Perhaps not. But how many humans will understand the machines well enough to ask these questions in the first place? Machines were supposed to free us from bureaucracy. Not freeze it everywhere with few avenues for escape. I have had an encounter with something like this via Wise / Transferwise. It has been half a decade and nada. And I estimate that it has cost me north of $20k+ over that time. Google, Wise and heck Maps were started with the ambition of adding something to the world — e.g. Google's original "organize all knowledge" mission - but over time cruft accrues and these companies rapidly accumulate negative side effects / drift away from their core mission. When was the last time Google / Alphabet / whatever did something that involved improving access to the world's knowledge? They've degraded their search to the point of uselessness and beyond. Slowly alienated their best researchers and engineers. And done their best to turn away from the entity that made Google Books — "we'll scan all the books for the good of all humankind."
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These things can accumulate and ruin lives. I'm surprised that there haven't been more class action lawsuits against "errors" like these. Because it might seem like a benign accident -- but how many people have lost important parts of their lives – banking, photos of their children and more – because "computer says no?" Eventually, these systems will be mostly artificially generated, and perhaps the machines will have fewer error rates than the humans. Perhaps not. But how many humans will understand the machines well enough to ask these questions in the first place? Machines were supposed to free us from bureaucracy. Not freeze it everywhere with few avenues for escape. I have had an encounter with something like this via Wise / Transferwise. It has been half a decade and nada. And I estimate that it has cost me north of $20k+ over that time. Google, Wise and heck Maps were started with the ambition of adding something to the world — e.g. Google's original "organize all knowledge" mission - but over time cruft accrues and these companies rapidly accumulate negative side effects / drift away from their core mission. When was the last time Google / Alphabet / whatever did something that involved improving access to the world's knowledge? They've degraded their search to the point of uselessness and beyond. Slowly alienated their best researchers and engineers. And done their best to turn away from the entity that made Google Books — "we'll scan all the books for the good of all humankind."
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Google Cloud has a solid product, not sure about internal engineering culture.
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brain was grown in house and likely deserves as much or more credit than open ai for the current llm boom
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They literally would have kept the entire thing to themselves and never productized it. Think about how much investment capital and human capital OpenAI poured onto this by having their big "hello world" with ChatGPT.
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They literally had a productionized transformer model (translate) which was the inspiration for all of this. The famous paper was written about a productionized ML Model. They also had a productionized LLM in search (known as 'mums') before the whole "AI Chatbot" craze. They also had a chat-tuned LLM chatbot (LaMDA) in testing internally. It was shown off over a year before ChatGPT was created (2021)... and later released as an app (AI test kitchen) before ChatGPT was announced. ChatGPT may have been the big industry moment, but Google was releasing LLMs to production before OpenAI.
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In other words, Meta (excepting maybe the bought departments) has become just like any other traditional mega-corporation. Ugly, inefficient and disorganized, but terribly good at doing the one thing that makes it money.