Fractional growth consultant | ex-CDO. tweets about digital, systems & operations, ai, startup marketing.
Ireland
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Why is it we have to do all this work to get AI to not sound like AI… people can get a pretty good result using prompts like these so why not build it in? Its bizarre @sama @AnthropicAI @OpenAI @DarioAmodei
quarterly reminder to use this prompt to get your AI writing to sound better:
No antithesis. No corrective negation. No paragraph pinning. No parataxis. No summary beats. No rhetorical crutches. No negative parallelisms. No negative anaphoras. No contrasting pairs. No rule of three. No em dashes. No throat-clearing openers. No landing sentences. No setup/payoff constructions. No parallel sentence structures within a paragraph. Vary sentence length unpredictably. No stacked noun phrases. No filler intensifiers (genuinely, really, truly, actually). No corporate-register verbs (leverage, underscore, reflect). No nominalization. No hedging qualifiers. Write for the spoken voice. No performed enthusiasm.
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I found a place to play red alert from my Mac! And subsequently lost numerous hours going down memory lane. What a fantastic game
openra.net/download/
Last night I played 4 hours of the original Command & Conquer Red Alert with a friend.
I absolutely loved this game.
One of the first PC games I truly obsessed over.
Released in 1996. Still an incredible game.
DId you play it?
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This is great, Ayush! A little glossary of those SEO bits in case people are lost 😅
1. Zod-validated markdown in Git: All content lives in simple text files with version history. A tool automatically checks that every page has the required details before it goes live.
2. Auto-generated JSON-LD from markdown: Invisible tags that tell search engines and AI tools exactly what each page is about. These tags are created automatically from the content files instead of being written by hand.
3. Sitemaps that pull lastmod from Git commit history: A master list of all pages sent to Google. The “last updated” date comes straight from when the file was actually changed in Git -> always accurate.
4. /llms.txt file: A simple text file AI crawlers can read easily. It points them to the most important content so your pages are more likely to show up correctly in ChatGPT and Perplexity answers.
we just published a deep dive on how we rebuilt @dodopayments website. migrated entirely off @framer. rewrote everything in @astrodotbuild.
the old site: 200KB+ javascript bundles. pagespeed scores between 60-75. client-side rendering meant crawlers couldn't even see our content.
the new site: zero javascript by default. static HTML at build time. lighthouse above 95.
but the interesting part is the SEO infrastructure we built on top. zod-validated markdown in git. auto-generated JSON-LD from markdown patterns. sitemaps that pull lastmod from git commit history. /llms.txt so AI crawlers can actually read our content.
our pages now show up in chatgpt and perplexity responses.
biggest lesson: no-code builders are great for launching. not for scaling.
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There’s no denying it’s going to massively increase competition though. So not going to zero but enough of a squeeze to feel similar inside those companies. The coasty ZIRP days are over (thank god)
if the cost of software was truly going to zero
no one would invest in replit, lovable, cursor or any other software building platform
there will be more software than ever before
which means more problems to solve
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AI quality output is still an issue.
“It’s not output that’s the issue—it’s quality” /s
You can see this with your own eyes with text that has clearly been written or heavily influenced by AI. How do you see this in a field outside your own expertise? If you are using it in your own field, how much time are you spending reviewing and cleaning up?
It adds up
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19 great reasons why AI wont take all white collar jobs by tomorrow.
But also 19 great excuses you need to look out for if you're trying to get AI off the ground
I've been asking $100m+ company execs one question:
"What is the #1 thing slowing/stopping your company's AI transformation?"
A non-exhaustive list of responses:
1) Data quality and connectivity of systems. Plus systems that play nice with AI.
2) Lack of leadership buy-in and implementation
3) Data governance restrictions.
4) Willingness of staff to adopt AI.
5) Incurious culture. Lack of knowledge of the current state of AI
6) Tooling doesn't have API access; team is still learning how to use LLMs.
7) Industry regulation/privacy.
8) Data quality and lack of a comprehensive AI system across the full company.
9) Unclear ownership across teams.
10) Time to actually build solutions.
11) Mixed AI literacy levels across teams.
12) No clear strategy / I'm starting the initiative from scratch.
13) Quality output.
14) Upskilling developers.
15) Silos.
16) Data Security and Security Guideline unclear.
17) Lack of training.
18) Data quality is unclear across multi-product teams.
19) Time.
What would your answer be to this question?
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How fast will AI actually get meaningfully implemented by large corps?
Global orgs with tens of thousands of employees have incredibly complex IT setups, restrictive permissions to access new tools and deep layers of bureaucracy.
You'll have 'AI-first' C-suite asking how much are we getting out of AI yet still have programs that run on MS-DOS. These infrastructure problems might be solved/improved with AI itself. But there is still a much bigger problem to get us to AI nirvana: people.
You need to train your 50,000 staff to use it, keep up with the weekly changes in the tool and don’t forget the six month procurement process that takes place to get OpenAI into a 50k company. People are slow, they dont like change and unfortunately (fortunately?) AI cant install itself just yet
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Duolingo will "gradually stop hiring contractors to do the work AI can handle".
Oof. Incidentally, I dropped my premium sub in the last few months. they focused too much on the sticky and not enough on language learning. alas
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Surprisingly few slop relies to this. Did @nikitabier pulling the plug on bots… work?! Amazing if so
lol Block/Square stock is up like 20% on laying off 40% of their headcount while growing and profitable.
The Faustian bargain that big tech made with society was by creating a nuevoaristocracy of laptop-class landed gentry, their founders and shareholders were allowed to become wealthy beyond all imagination with little government intervention past slaps on the wrist.
Google could cut 90% of the headcount and generate 90% of the revenue. But when this deal is broken, the displaced Baron’s will demand their own Magna Carta - tech leaders are too politically myopic to see this and so the more likely outcome is one of revolution. A rising of modern sans-culottes currently kept busy by the bread and circus’ of Doordash and TikTok but rallied to action by these displaced elites.
AI may be the excuse but this has always been an option. Salesforce employs 75,000 people. Including Matthew McConnaughey on over $1,000,000.00 a year. Most of this headcount can hit the road - Covid proved many jobs are ritualistic button pressing exercises in a circular loop of keep up appearances financed by a need for elite docility.
AI’s biggest disruption may be giving people the ‘excuse’ to finally break this pact. But I assure you the Maximilien Robespierre of today is not a puffed up perfumed Frenchmun. He’s a forty year old Stanford educated father of 4 who contributed to the Review about to lose his director role in Big Tech and enter the worst job market since the financial crisis. He will likely be equally as unforgiving if executives are not careful about how they carry themselves and their decisions in this coming shift.
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Good thing it will just be our Agents sub-agents dealing with this shitty software
It is true that it's never been easier to write great software.
It is also absolutely the case than in Feb 2028, there will be terrible software everywhere
Bad software to pay a parking ticket, dentists with terrible software, car dealers with awful CRM & paper everywhere
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And when we look back, $20 a month subscriptions gonna be like the $2 uber days. We’ll miss this period when AI VC money shits the bed
we’re still pricing ai tokens like software subscriptions but most companies will soon price them like labor
$200/month feels expensive because we compare it to saas
$50k/month will feel cheap when we compare it to headcount
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The doomsday vs ‘optimistic builder’ split on my algo seems to completely depend on whether there has been a ‘worlds gonna end’ article in the prior 72 hours.
Just a few days after @Citrini7 dropped and I’m back to seeing what people are building rather than reactive craziness
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I think we’re gonna see people using both. A single agent that has all your context and improves over time and plugs into the enterprise ones. The struggle for enterprise agents will be cost. Notions announcement yesterday fell flat when $ were spoken about
whats the future of personal agents?
one agent (openclaw) many skills
vs
many expert agents (Notion AI, Calendar AI, …)
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